The role of structural characteristics of soft sediment on absorption of total hydrocarbon content (THC) and physicochemistry due to human induced pollution in the lower bonny estuary were studied in a bid to measure the danger of human actions along the catchments on the estuary. Samples were collected and analyzed from five sampling stations representing fuel depot site, garbage dump, fishing spots, living quarters and an upstream station far removed from direct human impacts (control). Sediment samples were collected for six months representing wet and dry seasons. Samples were analyzed for THC, Organic Carbon, phosphate (PO4), Electrical conductivity (EC), and pH. Sediment particle was also determined by the hydrometer method. Result from the investigation reveal that there were significant seasonal differences in measured parameters (p<0.05). pH and THC and EC in wet season>dry season. While Organic Carbon and PO4 in wet season < dry season. Sample stations did not show any significant difference (p>0.05). Soil sediment analyses reveal that percentage of sand in sediment was uniform throughout the wet and dry season and all sample stations. Clay content was constant in all stations in dry season but fluctuated in the wet season between stations. Silt content in sediment fluctuated between stations in both wet and dry seasons. THC and physico-chemical parameters did not have any direct correlation with sediment characteristics.Station 5 (control) revealed lower values in almost all measured. parameters compared to other stations, implying greater ecological stability in the control station. The findings of this work is suggestive of the fact that Bonny estuary is under a subtle threat from land-based activities.
Department of Biological Sciences, Niger Delta University, Amassoma, Bayelsa State, Nigeria.
Iderima, S.T.
Institute of Geosciences and Space Technology, Rivers State University of Science and Technology, Port Harcourt, Rivers State, Nigeria.
**1. A. Baran and M. Tarnawski (2013) Phytotoxkit/Phytotestkit and Microtox as tools for toxicity assessment of sediments. Ecotoxicology and Environmental Safety. 98: 19-27.
2. NEDECO (1961) The Waters of the Niger Delta. Netherland Engineering Consult, The Hague, 112 p.
3. A.J Walkley and I.A Black (1934) Estimation of soil organic carbon by the chromic acid titration method. Soil Sci. 37, 29-38.
4. C.T.I Odu,, O.F. Esuruoso, L.C Nwoboshi and J.A Ogunwale (1985). “Environmental study of the Nigerian Agip Oil Company operational areas”. In: Proceedings of the soils and fresh water vegetation conference, Milan (Italy).
5. G.J. Bouyoucos (1951) A recalibration of the hydrometer method for making mechanical analysis of soils. Agron. J. 43; 435 - 438.**
Alagoa, K.J and Iderima, S.T., "The Role of Structural Characteristics of Soft Sediment on Absorption of Total Hydrocarbon Content (THC) and Physicochemistry Due to Human Induced Pollution in The Lower Bonny Estuary, Rivers State, Nigeria" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.12 issue 5, May 2023, pp.01-08 URL: https://doi.org/10.51583/IJLTEMAS.2023.12501
Non-verbal communication refers to the use of body language, facial expressions, gestures, and the tone of voice to convey meaning without the use of words. Non-verbal cues can include things like eye contact, posture, hand movements, and facial expressions. These cues can often communicate more information than verbal communication alone, and can also convey emotions, attitudes, and intentions. Non-verbal communication is a crucial aspect of human communication and can greatly influence how we perceive others and how we are perceived in return. It is also an important area of study in fields like psychology, anthropology, and communication studies. This research aims to psychologically investigate non-verbal communication differences between females and males in Sri Lanka. For this study, 100 girls and boys between the ages of 20 and 25 were selected from the two main faculties of the University of Sri Jayawardenepura, Sri Lanka, The Faculty of Management and Commerce and the Faculty of Humanities and Social Sciences. A sample of 50 girls and 50 boys was selected from each faculty using the random sampling. The observation method was used to collect data from students. In this research, a qualitative analysis method was used for data analysis. According to this study, same-sex and mixed-sex students randomly observed their communications with each other. During the data collection, students observed non-verbal communication methods such as hand and foot movements, eye contact, facial expression and, standing posture, distance during the conversation, and touching each other. Every part of this study, which was conducted using male and female university students, confirmed that women were ahead of men in non-verbal communication. Although academics have offered sociological, biological, and psychological reasons why women use more non-verbal communication tactics compared to men, according to the study, psychological reasons are more common. Accordingly, it was recognized that women use these non-verbal communication strategies to satisfy the natural characteristics of women, such as female attraction, the need to talk more, and the desire to join groups.
**1. Brackett, M. A., & Mayer, J. D. (2003). Convergent, discriminant, and incremental validity of competing measures of emotional intelligence. Personality and Social Psychology Bulletin, 29(9), 1147-1158.
2. Carney, D. R., Hall, J. A., & LeBeau, L. S. (2005). Beliefs about the nonverbal expression of social power. Journal of Nonverbal Behavior, 29(2), 105-123.
3. Carney, D. R., & Mason, M. F. (2010). Expecting to be judged by others can exacerbate social anxiety: The ironic effects of interpersonal cues. Journal of Experimental Social Psychology, 46(1), 216-221.
4. Charalambous, A., & Karageorghis, C. I. (2010). Nonverbal behavior and academic success: An examination. Journal of Applied Social Psychology, 40(5), 1055-1073.
5. Derntl, B., Windischberger, C., Robinson, S., Kryspin-Exner, I., Gur, R. C., Moser, E., & Habel, U. (2009). Facial emotion recognition and amygdala activation are associated with menstrual cycle phase. Psychoneuroendocrinology, 34(4), 556-563.
6. Dovidio, J. F., Ellyson, S. L., & Kiesler, C. A. (1988). The role of nonverbal cues in the communication of power. Journal of Personality and Social Psychology, 54(4), 488-498.
7. Fiske, A. P. (1993). Controlling other people
8. Hall, J. A., & Matsumoto, D. (2004). Gender differences in judgments of multiple emotions from facial expressions. Emotion, 4(2), 201-206.
9. Henningsen, D. D., & Henningsen, M. L. (2009). College students’ perceptions of immediacy behaviors in the classroom. Communication Education, 58(3), 369-391.
10. Keltner, D., & Ekman, P. (2000). Facial expression of emotion. In M. Lewis & J. M. Haviland-Jones (Eds.), Handbook of emotions (2nd ed., pp. 236-249). New York: Guilford Press.
11. Klineberg, O., & Hull, D. B. (1979). Nonverbal communication and culture. Current Anthropology, 20(2), 309-322.
12. LaFrance, M., Hecht, M. A., & Paluck, E. L. (2003). The contingent smile: A meta-analysis of sex differences in smiling. Psychological Bulletin, 129(2), 305-334.
13. Matsumoto, D., & Hwang, H. S. (2013). Evidence for training the ability to read microexpressions of emotion. Motivation and Emotion, 37(2), 375-385.
14. Tickle-Degnen, L., & Rosenthal, R. (1990). The nature of rapport and its nonverbal correlates. Psychological Inquiry, 1(4), 285-293.**
Niromi Gunarathne, "A Psychological Study of Non-Verbal Communication Differences Between Men and Women in Sri Lanka " International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.12 issue 5, May 2023, pp.09-14 URL: https://doi.org/10.51583/IJLTEMAS.2023.12502
Dr Peter Raila Agwanda PhD, Dr Charles Ondoro·May 2023·pp. 15-68
Globally and in Kenya to be specific, there has been a challenge on cost of manufacturing. Manufacturing cost has been rising for; a status report from the Sugar Directorate indicates that wholesale price of sugar in February 2017 was at average Sh 5, 352 per 50 kg, compared with Sh 4, 432 in the same period last year. In Kenya, sugar cane production decreased from 6.7 million tons in 2013 to 6.5 million tons in 2014 as reported in Economic Survey of 2014. Moreover, despite reporting increased cane delivery in 2015, supply chain in sugar firms remained dismal indicating inefficient firm processes and overall poor performance due to high cost of production. Its argued that supply chain(SC)s may use Electronic data interchange integration(EDII) to mitigate on cost and improve firm performance.SRM is management of all interactions with suppliers, while SCP performance means responsiveness, timeliness and reliability However; studies have not addressed this adequately. The purpose of this study was to determine the effect of supplier relationship management on the relationship between electronic data interchange integration and supply chain performance among sugar firms in western Kenya, the study established effect of electronic data interchange integration on supply chain performance; effect of supplier relationship management on supply chain performance; and effect of supplier relationship management on the relationship between electronic data interchange integration and supply chain performance. This study was anchored on resource based, transaction cost analysis, and social exchange theories. Correlation research design was used. Target population was 300 supply chain employees from 10 sugar manufacturing firms in western Kenya. A sample of 169 was drawn using cluster, purposive and simple random sampling. 10% of the sample was used to pre-test the questionnaire. Questionnaire and interview guides were used to collect primary data. Secondary data was obtained from Company’s’ records. The study concluded that EDI, SRM have significant effects on SCP and that SRM has moderating effect on the relationship between EDI and SCP. The study recommends that adopted EDII in SCP should be implemented consistently for improved performance and because SRM has a significant relationship between EDII and SCP it should been enhanced for increased performance. Findings may provide useful information for policy formulation for faster decision making in enhancing increased customer service level in the sugar firms and availability of research literature for further research
Jaramogi Oginga Odinga University of Science and Technology, Kenya
Dr Charles Ondoro
Jaramogi Oginga Odinga University of Science and Technology, Kenya
**1. Antonelli C. Ed, (1988). New Information Technology and Industrial Change: The Italian Case., EEC, Dordrecht / Boston / London, Kluwer Academic Publishers .
2. Avery, S.L. Swafford, P.& E.L. (2014). Impact of supplier relationship management practices on buying firm performance: comparison of the United States and China. Operations Management Research, 7(1–2): 36–48
3. Abdullahi, S. R. (2013). Efficiency of Credit Risk Management on the Performance of Banks in Nigeria A Study of Union Bank PLC (2006-2010). Global Journal of Management and Business Research Administration and Management, 3(4), 1-12.
4. Baraldi, A. N., & Enders, C. K. (2010). An introduction to modern missing data analyses. Journal of School Psychology, 48(1), 5-37.
5. Beamon, B. (1999). Measuring supply chain performance. International Journal of Operations and Production Management,19(3):275–292.
6. Bruhn, Manfred (2003), Relationship Marketing, Harlow, England: Prentice Hall. Buttle, Francis (1996), Rela Buttle, Francis (1996), Relationship Marketing. Theory and Practice, London: Paul Chapman Publishing
7. Ballou Ronald H, Gilbert Stephen M. and Mukherjee Ashok (2000): “New Managerial challenges For Supply Chain Opportunities”. Industrial Marketing Management vol. 29 pp. 7-18
8. Burja, C. (2011). Factors influencing the company’s profitability. Annales Universitatis Apulensis Series Oeconomica, 13(2): 215-22.
9. Chau, Y. K. and Jim, C. F. (2002). Adoption of electronic data interchanges in small and medium enterprises. Journal of Global Information Management, 10(4): 61-85.
10. Chopra, S., Meindl, P., 2001. Supply Chain Management. Prentice-Hall, New Jersey.
11. Chopra, S., & Meindl, P. (2004). Supply Chain Management, 2nd ed., New Jersey: Prentice-Hall
12. Christopher, M. (1994). Logistics and supply chain management, Richard D. Irwin.Financial Times, New York, NY.
13. Cristescu et.al (2010). Efficiency, effectiveness and performance of the public sector. Romanian Journal of Economic Forecasting – 4.
14. Cohen,M.A. & Moon,S. (1990). Impact of production scale economies, manufacturing complexity, and transportation costs on supply chain facility networks. Journal of Manufacturing and Operations Management,3,269-92.
15. Chakrabortya, S., Bhattacharyab ,S., & Dobrzykowski , D.D.(2014). Impact of Supply Chain Collaboration on Value Co-creation and Firm Performance: A Healthcare Service Sector Perspective. Procedia Economics and Finance, 11 ( 2014 ): 676 – 694 .
16. Choe, J-M.(2008). The effects of EDI usage on production performance through the changes of management control systems. Journal of Production Planning & Control,19(6) :577–589
17. Cramer, D. & Howitt, D. (2004). The SAGE Dictionary of Statistics. London, Routledge: SAGE Publications
18. Council of Supply Chain Management Professionals. (2010). Supply Chain Management Terms and Glossary. Retrieved August 2, 2013, from http://cscmp.org/sites/default/files/user\_uploads/resources/downloads/glossary.pd
19. Croom, S., Romano P., & Giannakis, M. (2000). Supply Chain Management: an Analytical Framework for Critical Literature Review. European Journal of Purchasing and Supply Management, 6(3): 45-60
20. Chwelos, P., Benbasat, I., & Dexter, A. S. (2001). Research report: Empirical test of an EDI adoption model. Information Systems Research, 12(3), 304–321.
21. D. Power and A. Simon (2004) Adoption and diffusion in technology implementation: A supply chain study. Int. J. Oper. Prod. Management, 6(11), 42-51
22. Dwyer, F. Robert, Paul H. Schurr, and Sejo Oh (1987), “Developing Buyer-Seller Relationships,” Journal of Marketing, 51, 2, 11-27
23. Davis, T. (1993). Effective supply chain management. Sloan Management Review
24. De Vries, M. ( 2017).EDI Basics eBook: How Successful Businesses Connect. GXS inc.
25. Elbaz, D. (1998). Electronic data interchange: an assessment of the factors leading to EDI adoption. Concordia University: Master Thesis Emmelhainz 1994
26. Faulhaber G., E. Noam and R. Tasley Eds, (1986), Services in Transition: the Impact of Information Technology On the Service Sector, Ballinger, Cambridge, Mass.
27. Frohlich, M. T. & Westbrook, R. (2001). Arcs of integration: an international study of supply chain strategies. Journal of Operations Management, 19: 185-200.
28. Fisher, M. L. (1997), What is the right supply chain for your product? Harvard Business Review, March-April:105-116.
29. Fawcett S.E., Magnan G.M. (2002). The rhetoric and reality of supply chain integration. International Journal of Physical Distribution & Logistics Management, 32(5): 339-361.
30. Flynnet at 2010 what is the right supply chain for your product? Harvard Business Review, March-April:105-116.
31. Gibson, B. J., Mentzer, J. T., & Cook, R. L. (2005) Supply chain management: The pursuit of a consensus definition. Journal of Business Logistics, 26(2): 65-74.
32. Gupta, Sunil, Donald R. Lehmann, and Jennifer Ames Stuart (2004), “Valuing Customers,” Journal of Marketing Research, 41, 1, 7-18
33. G. Johnson, K. Scholes, and R. Whittington, Exploring Corporate Strategy., 8th ed. Prentice Hall, 2007.
34. Gunasekaran, A. and Ngai, E.W. (2004) Virtual Supply-Chain Management. Production Planning & Control: The Management of Operations,
35. Gunasekaran, A. & Kobu, B. (2007).Performance measures and metrics in logistics and supply chain management: areview of recent literature (1995-2004) for research and applications. International Journal of Production, 6(11), 34-43
36. Green et.al 2006 Green, Paul E., Analyzing Multivariate Data, Hinsdale, Ill.: Dryden Press, 1978. 58. Green, Paul E., and Carmone, F.J., Multidimensional Scaling in Marketing Analysis, Boston: Allyn & Bacon, Inc., 1970.
37. Gimenez & yentura 2005 Performance measures and metrics in logistics and supply chain management: a review of recent literature
38. Gerrit J{2014} Performance measures and metrics in logistics and supply chain management Allyn & Bacon, Inc., 1970.
39. Grensing .Pophal {2013} Whittington, Exploring Corporate Strategy., 8th ed. Prentice Hall, 2008.
40. Gimenez &Yentura {2003} Investigating the Impact of Suppliers Relationship Management on Firms’ Performance: A Multiple Case Study Approach on Manufacturing Companies in Egypt.
41. Gerrit, J. (2011). Electronic Data Interchange: from its Birth to its New Role in Logistics Information Systems. International Journal on Information Technologies and Security. 3. 45-56.
42. Greene, B. A., & DeBacker, T. K. (2004). Gender Multidimensional Scaling in Marketing Analysis, Boston: Allyn & Bacon, Inc., 1970.
43. Ghaith M. Al-Abdallah, G.M., Abdallah, A.B., & Hamdan, K.B.(2014). The Impact of Supplier Relationship Management on Competitive Performance of manufacturing Firms. International Journal of Business and Management,9( 2): 192-216.
44. Grensing-Pophal, L. (2013). Benefits of Online Ordering Go Beyond Increased Sales. Retrieved from https://hospitalitytech.com/benefits-online-ordering-go-beyond-increased-sales
45. Han, J. H., Wang, Y.,& Naim, M.(2017). Reconceptualization of information technology flexibility for supply chain management: An empirical study. International Journal of Production Economics, 187(2017): 196-215.
46. Hdm bery {2000} A theory of the relationship between individual differences and information processing. Psychological Review, 91(2), 153¯184. Hunt, D. E., & Sullivan, E. V. (1974). Between Psychology and Education
47. Hair, Jr, J.F, Black, W.c, Babin, B.J &Anderson, RE {2010} Proceedings of the 2015 International Conference on Operations Excellence and Service Engineering Orlando, Florida, USA, September 10-11, 2015
48. Harink, J. (2003). Internet-technology in inkoop: De kinderschoenen ontgroeid. Dissertation, Universities Twenty. Netherlands 1-256
49. Humphreys, M. S., & Revelle, W. (1984). Personality, motivation, and performance: A theory of the relationship between individual differences and information processing. Psychological Review, 91(2), 153¯184. Hunt, D. E., & Sullivan, E. V. (1974). Between Psychology and Education
50. Hughes, Jonathan (April 2010). What is Supplier Relationship Management and Why Does it Matter?. DILForientering. Retrieved 26 January 2012
51. Han, J. H., Wang, Y.,& Naim, M.(2017). Reconceptualization of information technology flexibility for supply chain management: An empirical study. International Journal of Production Economics, 187(2017): 196-215.
52. Hand"eld, R.B., Nichols, E.L., 1999. Introduction to Supply Chain Management. Prentice-Hall, USA.
53. Hair, Jr. J.F., Black, W.C. Babin, B.J. and Anderson, R.E. (2010). Multivariate Data Analysis, 7th Edition. Pearson Prentice Hall.
54. Ishii, K., Takahashi, K., & Muramatsu, R.(1988). Integrated production, inventory and distribution systems.
55. J. Barney(1991). Firm Resources and Sustained Competitive Advantage.Adv. Strategic Management. 17:203–227
56. Jacobs F.R., Weston Jr. F.C.T. (2007), “Enterprise resource planning (ERP) – A brief history. Journal of Operations Management, 25:357-363
57. Jaklic J., & Kovacic A., (2003). Towards E-government - The Role of Simulation Modeling.15th European Simulation Symposium: Simulations in industry. 257-262, Delft, Netherlands: Computer Simulation Society.
58. Kim, shank C. M., & Keller, J. M. (2008). Effects , 114. British Journal of Psychology, 41, 68¯80. Using a whole-class token economy and coaching of teacher skills in a pre
59. Kalakota, Ravi, and Andrew B. Whinston, Electronic Commerce: A Manager's Guide Addison-Wesley, 1997
60. Kalakota, Ravi, and Marcia Robinson, E-Business: Roadmap for Success Addison-Wesley, 1999 See EBStrategy.com
61. Kothari, C. R. (1997). Research Methodology. New Delhi: Wishwa Prakashan, 181-.182Kothari, C.R., Quantitative Techniques, 2nd ed., New Delhi: Vikas Publishing House Pvt. Ltd..
62. Kenya Medical Research Institute, Centers for Clinical Research, National Cancer Registry Co-Authors: Gakunga R.1 , Okerosi N.1 , Buziba N.2 , Karagu A.3 , Rochford R.4 , Gitungo H.5 , Parkin M.6 , Kaduka L. 7, Muniu E. 7, Dawsey S.8
63. Kosgei, R. C. & Gitau, R. (2016). Effect of supplier relationship management on organizational performance: A case study of Kenya Airways Limited. International Academic Journal of Procurement and Supply Chain Management, 2 (2), 134-148
64. Kraajenbrink, J., Spender, C. & Groen, A. (2010). The Resource-Based View: A Review and Assessment of its Critiques. Journal of Management 36: 349. Kuhnert, K. & Lewis, P. (1987). Transactional and Transformational Leadership: A
65. Kabir, M., Saidin, S. & Aidi, A. (2015). Adoption of e-Payment Systems: A Review of Literature
66. Kahn K.B., Mentzer J.T. (1998), “Marketing’s integration with other departments”, Journal of Business Research, 42(1):. 53-62.
67. Kulik, C. T., & Roberson, L. (in press). Diversity initiative effectiveness: What organizations can (and cannot) expect from diversity recruitment, diversity training, and formal mentoring programs. In A. P. Brief (Ed.), [accessed Oct 15 2018].
68. Krajewski, Larry P. Ritzman Operations Management (9th Edition)tps://www.amazon.com/Operations-Management-9th-Lee Krajewski/dp/0136065767
69. K. a. Patterson, C. M. Grimm, and T. M. Corsi(2003). Adopting new technologies for supply chain management. Transport. Res., E 39: 95–121,
70. Katz M. L. and C. Shapiro, 1985, Network Externalities, Competition and Compatibility, American Economic Review,75(3): 424-440
71. Kekre, S., and T. Mukhopadhyay. 1992. Impacts of electronic data interchange on quality improvements and inventory reduction programs. International Journal of Production Economics,28 ( December): 265–282.
72. Kremic. T, Tukel. I.O & Rom. O.W (2006). Outsourcing decision support: a survey of benefits, risks, and decision factors. Supply Chain Management: An International Journal 11(6) 467–482
73. Kosgei, R.C. & Gitau, R. (2016). Effect of supplier relationship management on organizational performance: a case study of Kenya Airways Limited International Academic Journal of Procurement and Supply Chain Management ,2(2): 134-148
74. Kabir, M., Saidin, S. & Aidi, A. (2015). Adoption of e-Payment Systems: A Review of Literature
75. Krejcie and Morgan, C. (2007). Supply network performance measurement: future challenges? International Journal of Logistics Management, 18(2), 255-73.
76. Lin, Y. & Zhou, L. (2011). The impacts of product design changes on supply chain risk: A case study. International Journal of Physical Distribution & Logistics Management. 41. 162-186. 10.1108/09600031111118549.
77. Lee, G.L., Oakes, I.K., 1996. Templates for change with supply chain rationalization. International Journal of Operations and Production Management 16 (2), 197}209.
78. Lee, H., 1996. Elective inventory and service management through product and process redesign. Operations Research 44 (1), 151}159.
79. Lee, H.L., Billington, C., 1993. Material management in decentralized supply chains. Operations Research 41 (5), 835}847.
80. Lyons, T., Krachenberg, A.A., Henke, J., 1990. Mixed motive marriages: what’s next for buyer}supplier relations? Sloan Management Review29}36.
81. Lee, H.L., Billington, C., 1993. Material management in decentralized supply chains. Operations Research 41 (5), 835}847.
82. Lee, H.L., Billington, C., 1995. The evolution of supply chain management models and practice at Hewlett-Packard. Interfaces 25 (5),42}63.
83. Lummus, R. R. and Duclos, L. K. (1995). Implementation of EDI systems. Journals of System Management. 45(5): 4-10.
84. Lau, H.C.W., Lee, W.B., 2000. On a responsive supply chain information system. International Journal of Physical Distribution and Logistics Management 30, 598–610.
85. Langlois, R.N., 1992b. Transaction-cost economics in real time. Industrial and Corporate Change 1 (1), 99–127. Langlois, R.N., 1997. Cognition and capabilities: opportunities seized and missed in the history of the computer industry. In: Garud, R., Nayyar, P., Shapira, Z. (Eds.), Technological Learning, Oversights and Foresights. Cambridge University Press, New York.
86. Lin, Y. & Zhou, L. (2011). The impacts of product design changes on supply chain risk: A case study. International Journal of Physical Distribution & Logistics Management. 41. 162-186. 10.1108/09600031111118549.
87. Lim, D., & Palvia, P. C. (2001). EDI in strategic supply chain: Impact on customer service. International Journal of Information Management, 21(3), 193–211.
88. Mukhopadhyay, T., & Kekre, S. (2002). Strategic and operational benefits of electronic integration in B2B procurement processes. Management Science, 48(10), 1301–1313.
89. Mukhopadhyay, T., Kekre, S., & Kalathur, S. (1995). Business value of information technology: A study of electronic data interchange. MIS Quarterly, 19(2),137–156.
90. Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., & Zacharia, Z. G. (2001) Defining supply chain management. Journal of Business Logistics,
91. Mettler, T, & Rohner, P. (2009). Supplier Relationship Management: A Case Study in the Context of Health Care. Journal of Theoretical and Applied Electronic Commerce Research, 4 (3): 58–71.
92. Mettler T, Rohner P (2009). Supplier Relationship Management: A Case Study in theContext of Health Care. Journal of Theoretical and Applied Electronic Commerce Research. 4 (3): 58–71.
93. Maraka, K. ,Kibet, Y. ,& Iravo, M.(2015). Effects of Supplier Relationship Management on the Performance of Organizations in Selected Sugar Companies in Western Kenya. Journal of Economics and Finance,6( 3): 28-35
94. Magutu, P.O., Lelei,J.K., & Nanjira A.O. (April, 2010) The benefits and challenges of Mugenda, and Mugenda (2003). .Research Methods: Quantitative and Qualitative Approaches. Nairobi: Acts Press.
95. Morgan, C. (2007). Supply network performance measurement: future challenges? International Journal of Logistics Management, 18(2), 255-73.
96. Malone, Tates & Benjamin 1987electronic data interchange implementation and application at Kilindini Water Front Project in Kenya. African Journal of Business & Management (AJBUMA), 1, 25
97. Ngai, E. W. T. and Gunasekaran, A. (2004). Implementation of EDI in Hong Kong: an empirical analysis. Industrial management and Data System.104(1):88-100.
98. Nazish, A. (2016). Adapting E-Invoicing: Benefits, Challenges and Future Strategies to Overcome Challenges. A comparative case study of Finnish Companies (Degree project). vaasan ammattikorkeakoulu university of applied sciences
99. Ndambuki, D. (2013). Supply chain integration and supply chain performance of international humanitarian organizations in Kenya. University of Nairobi.
100. Oginni, Oyewole & Gambo, Jibreel & Abba, Mohammed & Ezekiel Onuh, Michael. (2013). Electronic Payment System and Economic Growth: A Review of Transition to Cashless Economy in Nigeria. International Journal of Scientific and Engineering Research. 2. 913-918
101. Potapenko, T. (2010). Transition to e-invoicing and post-implementation benefits. Exploratory case studies (Master’s Thesis). Aalto University school of Economics
102. Penrose, E. (1959), the Theory of the Growth of the Firm, Billing & Sons, London. Person, U. (1997), “A conceptual and empirical examination of the management concept supply chain management”, licentiate thesis, Division of Industrial Logistics, Lulea ‘University of Technology, Lulea
103. Ramamurthy, K., Premkumar, G. & Crum, M. R. (2009). Organizational Interorganizational Determinants of EDI Diffusion and Organizational Performance: A Causal Model. Journal of Organizational Computing and Electronic Commerce, 9(4)
104. Reio, T.G & Shuck, B (2014). Exploratory Factor Analysis. Implications for Theory, Research, and Practice. SAGE Journals
105. Singh, R. J.& Sohani, N. (2011).Recent advances in manufacturing engineering & technology. Proceedings of the National Conference on January 10-11, 2011
106. Spanic, D., Ristic, D. & Vrdoljak, B. (2011). An Electronic Invoicing System. 11th International Conference on Telecommunications (ConTEL), Graz, Austria
107. Stevens, J. (2002). Applied multivariate statistics for the social sciences.(4th ed.).
108. Tabachnick B.G. & Fidell, L.S. (2007). Using multivariate statistics (Fifth edition). New York, NY: Pearson Education, Inc.
109. Tabachnick, B. G., & Fidell, L. S. (2013). Using Multivariate Statistics, 6th ed. Boston: Allyn and Bacon.
110. Van der Vaart, J. T. & Van Donk, D. P. (2006). Buyer-focused operations as a supply chain strategy: identifying the influence of business characteristics. International Journal of Operations & Production Management, 26( 1). 8-23.
111. Verbeek, M. (2012), A Guide to Modern Econometrics, John Wiley and Sons Ltd., Great Britain
112. Williamson E. A., & Jordan M., (2004). Information Systems Development within Supply Chain Management. International Journal of Information Management,6(11): 30-40
113. Wang, J., Zhang, Y. & Goh, M. (2018). Moderating the Role of Firm Size in Sustainable Performance Improvement through Sustainable Supply Chain Management. Journal of Sustainability 10, 1654; doi:10.3390/su10051654
114. Wins, M. (2017). Effective E-sourcing: How to get started and achieve sustainable benefits? Retrieved fromhttp://www.procurement-academy.com/effective-e-sourcing-achieve-sustainable-benefits/
115. Wachira, R.W. (2013) Supplier relationship management and supply chain performance in alcoholic beverage industry in Kenya. http://erepository.uonbi.ac.ke**
Dr Peter Raila Agwanda PhD, Dr Charles Ondoro, "Effect of Supplier Relationship Management on the Relationship between Electronic Data Interchange Integration and Supply Chain Performance in Sugar Manufacturing Firms in Kenya" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.12 issue 5, May 2023, pp.15-68 URL: https://doi.org/10.51583/IJLTEMAS.2023.12503
Florence Wamboi & Mary Mwenda (PhD)·May 2023·pp. 69-79
Decent work and economic growth is outlined as one of the seventeen sustainable development goals which is framed on ensuring that all the individuals in the world as a whole are socio-economically empowered irrespective of their status or their countries as outlined in the United Nations Sustainable Development Goals in 2015. Cash transfers programs are proven to be a powerful poverty-reduction instrument, with positive impacts on poverty, dietary diversity, school attendance, investment in productive assets, child labor and empowerment indicators. The study purposed to establish the effect of cash transfer program on socio-economic empowerment of communities in Dadaab refugee complex, Kenya. The study objectives were: to examine the influence of funding of cash transfer program on socio-economic empowerment, to examine the influence of governance of cash transfer program on socio-economic empowerment, to examine the influence of needs assessment on recipients transfer program on socio-economic empowerment and to examine the influence of monitoring and evaluation of cash transfer program on socio-economic empowerment of communities in Dadaab refugee complex, Kenya. The study adopted universalism theory and theory of change and cash transfer programs to underpin this study. The research design used was descriptive survey design. The study targeted a population of 27,285 comprising of cash transfer officers, key informants and refugee households. A sample size of 427 of the respondents was carefully selected using probability sampling. The research relied on interview guides and research questionnaires as tools for data collection which were subjected to reliability and validity tests to ensure they achieved the recommended status before they were used in the actual study. Descriptive statistics such as percentages, standard deviations and means and also inferential analysis such as Pearson correlation coefficient and regression analysis were used to analyze the collected data. The study established that established that there was positive relationship between funding of cash transfer program and socio-economic empowerment, there was positive relationship between governance of cash transfer program and socio-economic empowerment, there was positive correlation between needs assessment and socio-economic empowerment. Lastly, the study revealed that there was positive relationship between monitoring and evaluation of cash transfer program and socio-economic empowerment. The study concluded that both funding of cash transfer programs, governance of cash transfer programs, needs assessment on recipients and monitoring and evaluation of cash transfer programs had positive and significant effect on socio-economic empowerment of communities in Dadaab refugee complex. The study recommends that there is need to ensure that more stakeholders are brought to board so as to ensure funding is well achieved and that the organizations have adequate funds to reach all the refugees that may be needy. The stakeholders should also come up with various strategies and programs to ensure the beneficiaries are educated on financial literacy as well as providing coaching and mentorship to apply in the various economic activities that promote economic empowerment. There is also need to ensure that more professionals are engaged by the support groups to ensure that there is proper governance and that the cash transfers only reach the intended and needy beneficiaries. Finally, the study recommends that through monitoring and evaluation of cash transfer programs, the support groups should ensure that any shortcomings that may result from the programs are quickly traced and proper correction measures undertaken for the benefit of the beneficiaries. The intention of this article is also for resource mobilization for refugees in Dadaab refugee camp, Kenya, as well as for other marginalized communities in the world.
MA Project Planning and Management, University of Nairobi, Kenya
Mary Mwenda (PhD)
Lecturer, Faculty of Business and Management Sciences, University of Nairobi Kenya.
**1. Abdi, Y. A. (2019). Effect of National Government Cash Transfer Programme on Level Poverty in Kenya: A Case Study of Cash Transfer Projects in Wajir County.
2. Amanda, K. M. (2017). Effects of older persons cash transfer funds on the well-being of the elderly in Kibera, Nairobi County, Kenya. Nairobi: Kenyatta University: Unpublished MA Thesis.
3. Amina, I. A. (2015). Cash transfer programming in the ASALs of Kenya. Cash Learning Partnership.
4. Amy Slaughter. (2017). The Case for Measuring Self-Reliance. Retrieved on January 2020 fromhttp://europeanevaluation.org/sites/default/files/ees\_newsletter/ees-newsletter-2017- 10-october-r10\_web.pdf
5. Anne, E., Charlotte, B., & Raquel, T. (2019). How can cash transfer programmes work for women and children:A review of gender- and child-sensitive design features. Brasilia: International Policy Centre for Inclusive Growth (IPC-IG).
6. Anjini, M. (2017). What works and what doesn’t for children in humanitarian and development contexts. London: Save the Children UK.
7. Ayinkamiye, R. (2015). Strategies used by State and non State Actors in Empowering the Refugees in Kenya. University of Nairobi.
8. Baird, S., Ferreira, F., Ozler, B., & Woolcock, M. (2012). Relative effectiveness and cost- effectiveness of conditional and unconditional cash transfers for schooling outcomes in developing countries: a systematic review. The Campbell Collaboration.
9. Balley, S., & Harvey, P. (2015). State of Evidence on Humanitarian Cash Transfers: Background Note for the High-Level Panel on Humanitarian Cash Transfers. Overseas Development Institute.
10. Barrientos, A. (2011). Social protection and poverty. International Journal Of Social Welfare, 20 (3), 240-249.
11. Bastagli, F., Hagen, Z. J., Harman, L., Barca, V., Sturge, G., Schmildt, T., et al. (2016). Cash transfers: what does the evidence say? A rigorous review of programmeprogram impact and of the role of design and implementation features. Overseas Development Institute.
12. Benjamin, D., Sudhanshu, H., Nicola, H., Natalia, W. R., Paul, W., & Jennifer, Y. (2020). From Evidence to Action: The story of cash transfers and impact evaluation in sub-saharan Africa. The Food and Agricultural Organization of the United Nations and The United Nations Children's Fund and Oxford University Press.
13. Betts, A. (2018, August 1). Empowering Refugees in Times of Crisis. (R. J. Rodriguez, Interviewer).
14. Browne, E. (2011). Theories of change for cash transfer. Birmingham, UK: GSDRC, University of Birmingham.
15. CFR. (2019, August 1). Retrieved February 12, 2021, from Empowering Refugees in Times of Crisis: Crisis: http://www.cfr.org
16. Creti, P. (2015). The Impact of Cash Transfers on Local Markets: A Case Study of Unstructured Markets in northern Uganda. Oxford: Cash Learning Partnership.
17. Fan, L., Hongmei, Y., Yingquan, S., & Linxiu, Z. (2016). The impact of conditional cash transfers on the matriculation of junior high school students into rural China's high schools. Journal of Development Effectiiveness, DOI: 10.1080/19439342.2016.1231701
18. IRC. (2018). Dreams Deterred: Opportunities to Promote Self-reliance for Somali Refugee Youth in Kenya
19. Jessica, H. Z., Martina, U., Rebecca, H., & Zina, N. (2017). Cash transfers for refugees: The economic and social effects of a programme in Jordan. London: ODI.
20. Kamau, D. M., & Mwenda, M. N. (2021). Empowerment of Urban Refugee Youths in Nairobi County, Kenya: A Socio-Economic Perspective. European Jourbal of Business Research Management, 6 (1).
21. Kothari, C. R. (2013). Research Methodology: Methods and Techniques. New Delhi: H.S.
22. Mbugua, L., & Gachunga, H. (2015). Challenges in management of older persons cash transfer programme in Kenya, case study of ministry of labour, social security and services. The strategic journal of business and change management, 2 (3), 35-51.
23. Menashy, F. &Zakharia, Z. (2017). Investing in the crisis: Private participation in the education of Syrian refugees. Educational International Research. Retrieved from HYPERLINK "http://download.ei-ie.org/Docs/WebDepot/EI\_Research\_Syria\_final.pdf"http://download.ei- ie.org/Docs/WebDepot/EI\_Research\_Syria\_final.pdf
24. Mugenda, O. M., & Mugenda, A. G. (2012). Research Methods: Qualitatitive and Quantitative Approaches. Nairobi: ACTS.
25. Njeru, T. M., & Minja, D. (2019). Determinants of implementing cash transfer program for orphans and vulnerable children; A Case of Isiolo County, Kenya. International Academic Journal of Law and Society, 1 (2), 411-434.
26. Odenyo, C., & Rosemary, J. (2018). Influence of Resource Mobilization on Sustainability of Women Group Projects in Vihiga County, Kenya. International Journal of Economics, Business and Management Research, 2 (4), 127-141.
27. Orodho, AJ (2017). Techniques of writing Research Proposals and Reports in Education and Social Science. Nairobi: Kanezja Publisher.
28. Romero, M., Sandefur, J., & W. Sandholtz. (2017). Can outsourcing improve Liberia’s schools? - working paper 462. Preliminary results from year one of a three-year randomized evaluation of partnership schools for Liberia. Center for global development. Working paper 462. Retrieved from https://www.cgdev.org/publication/partnership-schools-for-liberia
29. Sytnik, S. (2016). Rights Displace: The effects of long term encampment on the human rihts of refugees. London: London School of Economics and Political Science.
30. UNHCR. (2016). Retrieved February 3, 2021, from Cash for education:A global review of UNHCR programs in refugee settings.
31. UNHCR. (2018). Her Turn: Its time to make refugee girls' education priority. Geneva: UNHCR.
32. UNHCR. (2018). Living on the Edge: A Livelihood Status Report on Urban |refugees Living in Nairobi Kenya. Geneva: UNHCR.
33. Wangui, G. K. (2019). Influence of corporate governance on performance of saccos in Nairobi County, Kenya. Unpublished MBA report, United States International University-Africa
34. Wanjiru, G. M. (2017). The role of cash transfer programs in promoting sustainable development goals for the urban poor woman in Nairobi. Nairobi: USIU-Africa.
35. Weiss, J. W. (2009). Business Ethics: A Stakeholder & Issues Management Approach. Mason, OH: South-Western Cengage Learning.
36. Wekesa, J. M. (2018). Influence of Parental Involvement on Refugee Girls' Participation in Secondary Schools in Kakuma Refuge Camp, Turkana County, Kenya. Nairobi: University of Nairobi: Unpublished MED Project.
37. Women Refugee Commission. (2018). Retrieved Feb 2020, from Building Livelihoods: Guidance and tools for programming: http://wrc.ms/S3jGQdziJ**
Florence Wamboi & Mary Mwenda (PhD), "Cash Transfer Program and Socio-Economic Empowerment. A Study on Communities in Dadaab Refugee Complex, Kenya" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.12 issue 5, May 2023, pp.69-79 URL: https://doi.org/10.51583/IJLTEMAS.2023.12504
Road transportation in rural areas is one of the main means of conveying people, farmers, farm implements and farm produce from the rural dwellings and farms unfortunately the dearth of investment and maintenance of road infrastructure in rural communities and also the growing use of these roads has made the plying of such roads to be worrisome because of its implication on the safety of those using the road. The consequence of the badly rutted, sandy or muddy roads is the increase in the cost of transporting agricultural produce to farm which will inevitably contribute to increasing food prices. The need to make sandy rural road to have a suitable wearing course necessitated the collection of sand samples from a community in Yewa South Local Government Area of Ogun State Nigeria. Particle size distribution, in-situ density, compaction, relative density, relative compaction and California bearing ratio (CBR) were conducted on the sand samples. The soil profile was 300mm thick at the point the sample was obtained. The results obtained from the tests indicated that; the sand was well graded (SW) in accordance to the unified soil classification system. The CBR values obtained were 23.23% and 22% and the result of relative compaction was 65% which is less than the 90-95% stipulated by relevant standard and this can be attributed to the natural compaction of the soil done by the flowing water as against when a compactive effort is applied. For the sandy road to be plied all year round, the moisture content of the sand should be kept at a value well above 1.3% and the thickness of the wearing course should not be less than 300mm.
Department of Civil Engineering, Federal Polytechnic, Ilaro
Ayegbusi Olufunke Adewunmi
Department of Civil Engineering, Federal Polytechnic, Ilaro
Oguntade Omotolani Idowu
Department of Civil Engineering, Ogun State Institute of Technology Igbesa
**1. Omar, H. M., Zentar, R., Akacem, M., Mekerta, B., & Mouli, M. (2022). Co-valorization of Tuff and Sandy Residues in Roads Construction. Civil Engineering Journal, 8(5), 1029-1045.
2. Paige-Green, P. (2014). Sustainability issues surrounding unpaved roads. Climate Change, Energy, Sustainability and Pavements, 335-351.
3. Paige-Green, P. (2007). New perspectives of unsealed roads in South Africa. Road & Transport Research: A Journal of Australian and New Zealand Research and Practice, 16(3), 56-62.
4. Salhi, R., & Messaoudi, K. (2021). The Effects of Delays in Algerian Construction Projects: An Empirical Study. Civil and Environmental Engineering Reports, 31(2), 218-254.
5. Santoni, R. L. (2003). Enhanced coastal trafficability: Road construction over sandy soils. ENGINEER RESEARCH AND DEVELOPMENT CENTER VICKSBURG MS GEOTECHNICAL AND STRUCTURES LAB.
6. Sharaky, A. M., Mohamed, N. S., Elmashad, M. E., & Shredah, N. M. (2018). Application of microbial biocementation to improve the physico-mechanical properties of sandy soil. Construction and Building Materials, 190, 861-869.
7. Metcalf, J. B., & Wylde, L. J. (1984). A reexamination of specification parameters for sandy soil roadbase materials. Bulletin of the International Association of Engineering Geology, (30).**
Adegbesan Ololade Oluwatosin, Ayegbusi Olufunke Adewunmi, Oguntade Omotolani Idowu, "Investigating Sand as Wearing Course in Rural Roads" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.12 issue 5, May 2023, pp.80-87 URL: https://doi.org/10.51583/IJLTEMAS.2023.12505
Student engagement is one of the important constructs that is used to understand the behavior of the student towards the teaching-learning process, and it determines the students’ academic performance. The aim of this study is for predictive analytics to work on the comprehension of student commitment and scholarly execution and anticipate students who are in danger of low execution or commitment right on time before the evaluation to work with conceivable mediation to further develop the learning results in advanced education. This research adopts the process of machine learning such as linear regression, decision tree, naïve Bayes, KNN, Kmeans in order to identify the most effective determinants for student academic performance prediction. The result of this study shows that after testing the five attributes, we discovered so far that the attributes that has impact on student evaluation are their Race/Ethnicity and Parental level of Education. Thus, the early prediction of student performance can trigger educators to track student dropouts in a particular course at an early stage. The model can also be used as an early warning system to identify failure students in the classroom by the course coordinators and educators, to take strategic decisions to improve student performance.
Department of Computer Science, Federal Polytechnic Oko.
Obayi Adaora Angela
Department of Computer Science, University of Nigeria, Nsukka.
Oloruntobe Samson Abiodun
Department of computer science, caleb university, imota, lagos.
Agbo Jonathan Chukwunike
Department of Computer Science, University of Nigeria, Nsukka.
Cassia Anwar C.
Department of Computer Science, Federal Polytechnic Nekede Owerri.
**1. Anderson, T. and Anderson, R. (2017). ‘Applications of Machine Learning To Student Grade Prediction in Quantitative Business Courses’, Global Journal of Business Pedagogy, 1(3), pp. 13–22.
2. Alamri, R.; Alharbi, B. (2021) ‘Explainable student performance prediction models: A systematic review. IEEE Access, 9, 33132–33143. [CrossRef]
3. Akçapınar, G.; Altun, A.; A¸skar, P. (2019), ‘Using learning analytics to develop early-warning system for at-risk students. Int. J. Educ. Technol. High. Educ. 16, 40. [CrossRef].
4. Akram, A.; Fu, C.; Li, Y.; Javed, M.Y.; Lin, R.; Jiang, Y.; Tang, Y. (2019). ‘Predicting students’ academic procrastination in blended learning course using homework submission data. IEEE Access 2019, 7, 102487–102498. [CrossRef]
5. Behr, A.; Giese, M.; Theune, K. (2020). ‘Early prediction of university dropouts - A random forest approach. Jahrbücher Für Natl. Und Stat. 2020, 240, 743–789. [CrossRef]
6. Brendan Flanagan\* , Rwitajit Majumdar and Hiroaki Ogata (2022). Early‑warning prediction of student performance and engagement in open book assessment by reading behavior analysis. Int J Educ Technol High Educ.
7. Burgos, C.; Campanario, M.L.; de la Peña, D.; Lara, J.A.; Lizcano, D.; Martínez, M.A. (2018). ‘Data mining for modeling students’performance: A tutoring action plan to prevent academic dropout. Comput. Electr. Eng. 2018, 66, 541–556. [CrossRef]
8. Christenson S. L., Wylie C., & Reschly A. L. (2012). Handbook of research on student engagement. Springer Science and Business Media. https://doi.org/10.1007/978-1-4614-2018-7
9. Courtney Brallier (2020). The effects of student engagement on academic achievement among college students. Middle Tennessee State University.
10. Dessart L., Veloutsou C., & Morgan-Thomas A. (2015). Consumer engagement in online brand communities: A social media perspective. Journal of Product and Brand Management, 24(1), 28–42. https://doi.org/10.1108/JPBM-06-2014-0635/FULL/XML
11. Fredricks JA, Blumenfeld PC, Paris AH.(2004). ‘School engagement: Potential of the concept, state of the evidence. Review of Educational Research. 2004;74:59–109. [Google Scholar]
12. Guo, Y., Liu, Y., Oerlemans, A., Lao, S., Wu, S., & Lew, M. S. (2016). Deep learning for visual understanding: A review. Neurocomputing, 187, 27–48. http://dx.doi.org/ 10.1016/j.neucom.2015.09.116.
13. Henrie C. R., Halverson L. R., & Graham C. R. (2015). ‘Measuring student engagement in technology-mediated learning: A review. Computers & Education, 90, 36–https://doi.org/10.1016/J.COMPEDU.2015.09.005
14. Helal, S.; Li, J.; Liu, L.; Ebrahimie, E.; Dawson, S.; Murray, D.J. (2019). ‘Identifying key factors of student academic performance by subgroup discovery. Int. J. Data Sci. Anal. 2019, 7, 227–245. [CrossRef]
15. Iqbal, Z., Qadir, J., Mian, A.N. and Kamiran, F. (2017) ‘Machine Learning Based Student Grade Prediction: A Case Study’, pp. 1–22.
16. Jenz Abbing (2013), the effect of student’s engagement on academic achievement in different stages of their academic career from a drop out perspective. University of twente.
17. Kotsiantis, S. B. (2017). Supervised Machine Learning: A Review of Classification Techniques. Informatica 31 (2017). Pp. 249 – 268. Retrieved from IJSwebsite:2.4.3/index.php/informatica/article/download/148/140.
18. Lemay, D.J.; Doleck, T. (2020). ‘Predicting completion of massive open online course (MOOC) assignments from video viewing behavior. Interact. Learn. Environ. 2020, 1782–1793. [CrossRef]
19. Lemnaru C. (2012). Strategies for dealing with Real World Classification Problems, (Unpublished PhD thesis) Faculty of Computer Science and Automation, Universitatea Technica, Din Cluj-Napoca. Available at website: http://users.utcluj.ro/~cameliav/documents/TezaFinalLemna ru.pdf
20. Louridas, P., & Ebert, C. (2016). Machine Learning. IEEE Software, 33(5), 110-115. doi:10.1109/ms.2016.11.
21. Mangaroska, K.; Giannakos, M. (2018). ‘Learning analytics for learning design: A systematic literature review of analytics-driven design to enhance learning. IEEE Trans. Learn. Technol. 2018, 12, 516–534. [CrossRef]
22. Marbouti, F.; Diefes-Dux, H.A.; Strobel, J. (2015). ‘Building course-specific regression-based models to identify at-risk students. In Proceedings of the 2015 ASEE Annual Conference & Exposition, Seattle, WA, USA, 14–17 June 2015; pp. 26–304.
23. Martin, J., & Torres, A. (n.d.). (2016). ‘User's Guide and Toolkit for the Surveys of Student Engagement: The High School Survey of Student Engagement and the Middle Grade School Survey of Student Engagement. National Association of Independent Schools. Retrieved from https://www.nais.org/Articles/Documents/Member/2016 HSSSE-report-full-FINAL.pdf.
24. Neocleous C. & Schizas C. (2002). Artificial Neural Network Learning: A Comparative Review. In: Vlahavas I.P., Spyropoulos C.D. (eds)Methods and Applications ofArtificial Intelligence.
25. Nilsson, N.J. (2005). Learning machines. New York: McGraw-Hill.Published in: Journal of IEEE Transactions on Information Theory Volume 12 Issue 3, 1966. doi:
10.1109/TIT.1966.1053912 pp. 407 – 407. Available at ACM digital library website:
http://dl.acm.org/citation.cfm?id=2267404
26. Oliva-Cordova, L.M.; Garcia-Cabot, A.; Amado-Salvatierra, H.R. (2021). ‘Learning analytics to support teaching skills: A systematic literature review. IEEE Access 2021, 9, 58351–58363. [CrossRef]
27. Setiono R. and Loew, W. K. (2000), FERNN: An algorithm for fast extraction of rules from neural networks, Applied Intelligence.
28. Shai Shalev-Shwartz and Shai Ben-David (2014). Understanding Machine Learning From Theory to Algorithms.
29. Taiwo, O. A. (2010). Types of Machine Learning Algorithms, New Advances in Machine Learning, Yagang Zhang (Ed.), ISBN: 978-953-307-034-6, InTech, University of Portsmouth United Kingdom. Pp 3 – 31. Available at InTech open http://www.intechopen.com/books/new-advances-in- machine-learning/types-of-machine-learning-algorithms.
30. Timothy Jason Shepard, P. J. (2008). Decision Fusion Using a Multi-Linear Classifier. In Proceedings of the International Conference on Multisource-Multisensor Information Fusion.
31. Waheed, H.; Hassan, S.U.; Aljohani, N.R.; Hardman, J.; Alelyani, S.; Nawaz, (2020). ‘R. Predicting academic performance of students from VLE big data using deep learning models. Comput. Hum. Behav. 2020, 104, 106189. [CrossRef].
32. Yang, Y.; Hooshyar, D.; Pedaste, M.;Wang, M.; Huang, Y.M.; Lim, H. (2020). ‘Prediction of students’ procrastination behaviour through their submission behavioural pattern in online learning. J. Ambient. Intell. Humaniz. Comput. 2020, 1–18. [CrossRef]
33. Y. Xin, L. Kong, Z. Liu, Y. Chen, Y. Li, H. Zhu, et al., (2018). "Machine learning and deep learning methods for cybersecurity", IEEE Access, vol. 6, pp. 35365-35381.
34. Zhang, L., Li, K.F., (2018). Education analytics: Challenges and approaches, in: 2018 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA), p. 193–198. doi:10.1109/WAINA.2018.00086. www.kaggle.com/code/spscientist/student-performamce-in-exams/notebook**
Ubani Kingsley Chukwuemeka, Obayi Adaora Angela, Oloruntobe Samson Abiodun, Agbo Jonathan Chukwunike, Cassia Anwar C., "An Enhanced Student Engagement and Academic Performance Predictive System" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.12 issue 5, May 2023, pp.88-97 URL: https://doi.org/10.51583/IJLTEMAS.2023.12506
COVID-19 pandemic has changed the way of doing business and living. In particular, banking services were not spared leading to increase in the adoption of digital banking. The study investigated the determinants of customer satisfaction of digital banking services in Zimbabwe. Privacy, convenience, ease of use, site organization, reliability and personal need were identified as determinants that affect electronic customer satisfaction of banking services and were subjected to an examination. Mixed methodology was adopted with a view to capture both qualitative and quantitative aspects of the phenomenon. A sample of 20 electronic banking customers in Harare were randomly selected. In-depth interviews and questionnaires were used as methods for collecting data. It was found that electronic customer satisfaction, ease of use, zero-rated application, privacy and reliability were the main determinants in Zimbabwe. The study recommends that when developing digital banking applications, banks should consider giving maximum attention to these determinants noted in the empirical study.
**1. Ahager. (2011). Ahanger, 2011 LR.pdf. In Journal Applied Science (Vol. 11, Issue 3, pp. 426–437).
2. Altobishi, T., Erboz, G., & Podruzsik, S. (2018). E-Banking Effects on Customer Satisfaction: The Survey on Clients in Jordan Banking Sector. International Journal of Marketing Studies, 10(2), 151. https://doi.org/10.5539/ijms.v10n2p151
3. Chiu, C.-M., Chang, C., Cheng, H.-L., & Fang, Y.-H. (2009). Determinants of customer repurchase intention in online shopping. Online Information Review, 33, 761–784. https://doi.org/10.1108/14684520910985710
4. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008
5. Deyalage, P. A., & Kulathunga, D. (2019). Factors Affecting Online Customer Satisfaction: The Sri Lankan Perspective. International Journal of Business and Management, 14(2), 99. https://doi.org/10.5539/ijbm.v14n2p99
6. Dharmesti, M., & Nugroho, S. (2013). The Antecedents of online customer satisfaction and customer loyalty. Journal of Business and Retail Management Research, 7.
7. Ghali, Z. (2021). Motives of customers’ e-loyalty towards e-banking services: a study in Saudi Arabia. Journal of Decision Systems, 30(2–3), 172–193. https://doi.org/10.1080/12460125.2020.1870063
8. Ghane, S., Fathian, M., & Gholamian, M. (2011). Full relationship among e-satisfaction, e-trust, e-service quality, and e-loyalty: The case of Iran e-banking. Journal of Theoretical and Applied Information Technology, 33.
9. Kim, D. J. (2012). An investigation of the effect of online consumer trust on expectation, satisfaction, and post-expectation. Information Systems and E-Business Management, 10(2), 219–240. https://doi.org/10.1007/s10257-010-0136-2
10. Lakshmi, N. M., & Kavitha, M. (2020). A study on customer satisfaction on digital banking. Journal of Xi’an University of Architecture & Technology, XII(III), 727–734. www.ijrar.org
11. Lecturer, S., Development, E., & Development, E. (2014). Journal of Internet Banking and Commerce. Journal of Internet Banking and Commerce, 19(2). http://www.arraydev.com/commerce/jibc/
12. Ling, G. M., Fern, Y. S., Boon, L. K., & Huat, T. S. (2016). Understanding Customer Satisfaction of Internet Banking: A Case Study In Malacca. Procedia Economics and Finance, 37(16), 80–85. https://doi.org/10.1016/s2212-5671(16)30096-x
13. Liu, C., & Arnett, K. P. (2000). Exploring the factors associated with Web site success in the context of electronic commerce. Information and Management, 38(1), 23–33. https://doi.org/10.1016/S0378-7206(00)00049-5
14. Morabito, V. (2014). Trends and challenges in digital business innovation. Trends and Challenges in Digital Business Innovation, 9783319043074, 1–215. https://doi.org/10.1007/978-3-319-04307-4/COVER
15. Mukherjee, A., & Nath, P. (2007). Role of electronic trust in online retailing: A re-examination of the commitment-trust theory. In European Journal of Marketing (Vol. 41, Issues 9–10). https://doi.org/10.1108/03090560710773390
16. Munusamy, J., Chelliah, S., & Mun, H. (2010). Service quality delivery and its impact on customer satisfaction in the banking sector in Malaysia. International Journal of Innovation, …, 1(4), 398–404. http://www.ijimt.org/papers/71-M461.pdf
17. Nupur, J. M. (2010). E-Banking and Customers’ Satisfaction in Bangladesh: An Analysis. International Review of Business Research Papers, 6(4), 145–156.
18. Singh, I., Nayyar, A., Le, D. H., & Das, S. (2019). A conceptual analysis of internet banking users’ perceptions: An Indian perceptive. Espacios, 40(14).**
Makota Justin, "Determining The Determinants Customer Satisfaction of Digital Banking Services in Zimbabwe " International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.12 issue 5, May 2023, pp.98-104 URL: https://doi.org/10.51583/IJLTEMAS.2023.12507
Umar Abdulkadir, Sulaiman Salihu Suaibu, Ahmed Sayoji and Halima Musa Muhammad·May 2023·pp. 105-108
Together with the new developments in business, traditional business education is changing. Interactive games, creative class activities, mobile devices like iPads and tablets change the business education radically. In academic world and in business training there are very new and radical approaches. In this paper, new opportunities provided by new technologies will be analyzed and unusual teaching examples from Universiti Teknologi Malaysia (UTM) and other leading universities around the world will be presented.
Federal College of Education (Technical) Gombe, Gombe State, Nigeria
Sulaiman Salihu Suaibu
Federal College of Education (Technical) Gombe, Gombe State, Nigeria
Ahmed Sayoji
Federal College of Education (Technical) Gombe, Gombe State, Nigeria
Halima Musa Muhammad
Federal College of Education (Technical) Gombe, Gombe State, Nigeria
**1. Botsman, R. & Rogers R. (2010). What’s Mine is Yours: The Rise of Collaborative Consumption. Harper Business.
2. Broughton, P.D. (2009) Ahead of the Curve: Two Years at the Harvard Business School. Penguin Books.
3. Clayton, C. & Eyring, J.H. (2011). The Innovative University: Changing the DNA of Higher Education from the Inside Out. Jossey Bass.
4. Cook, C.K. & Grant-Davie, K. (2013). Evolving, Adapting, and Reinventing Online Technical Communication. Jossey Bass.
5. Hollender, J. & Green, B. (2013). The Responsibility Revolution: How the Next Generation of Businesses Will Win. Jossey Bass.
6. Howe, J. (2009). Crowdsourcing: Why the Power of the Crowd is Driving the Future of Business. Crown Business.
7. Resnick, D. & Scott, D. (2004). The Innovative University, Carnegie Mellon.
8. Sheahan P. (2005). Generation Y: Thriving and Surviving With Generation Y at Work. Hardie Grant Books.
9. Thorp, H. & Goldstein, B. (2
010) Engines of Innovation: The Entrepreneurial Universty in the Twenty-First Century. The University of North Carolina Press.**
Umar Abdulkadir, Sulaiman Salihu Suaibu, Ahmed Sayoji and Halima Musa Muhammad, "Innovative Approaches in Business Education" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.12 issue 5, May 2023, pp.105-108 URL: https://doi.org/10.51583/IJLTEMAS.2023.12508
Mr. Ravi I A, Dr. Sudharshan G M·May 2023·pp. 109-122
This study focuses on how consumers' use of social media affects the decision-making process throughout the entire buying cycle, not only at the beginning. In this context, "complicated purchasing behavior" describes consumers who make few purchases each year but are highly invested in each one. There's a new fad developing around social networking. Blogs, social networks, and other user-created forms of online social interaction have proliferated over the past decade. That's the whole point of social media, and these tools are what's behind the exponential growth of user-generated content and the emergence of a truly global online community. The proliferation of social media has resulted in several online communities where users can communicate and share information and ideas. The rise of social media has ushered in a plethora of new channels for researching and vetting potential purchases. It is possible for strangers on social media to dominate a single consumer's opinion and comments on products and services, with knock-on effects in the real world. But, there is no denying that the rise of social media has put the consumer in charge, as their chats online are the sole source of content for many platforms. The marketers' goal is to learn how consumers use social media and how the stuff they see there influences their purchasing decisions. Data from 180 participants was also collected and confirmed, and factor analysis was deemed a statistical technique. The research concluded that social media has a favorable effect on consumers' shopping decisions.
Research Scholar, Department of MBA, PES Institute of Technology and Management, Shivamogga, India
Dr. Sudharshan G M
Professor, Department of MBA, PES Institute of Technology and Management, Shivamogga, India
**1. Asad and Mohammed (2017). Factors Influencing Consumers' Attitudes toward Social Media Marketing
2. Ballantine and Stephenson (2011). Help me, I’m fat! Social Support in Online weight loss networks. Journal of Consumer Behaviour 10(6) DOI:10.1002/cb.374.
3. Blackwell,Miniard & Engel.(2001). Consumer Behaviour. Texas: Harcourt College Publishers.
4. Erkan Arkar&BirolTopcu (2011). An Examination of the Factors Influencing Consumers' Attitudes toward Social Media Marketing, Journal of Internet Commerce, doi.org/10.1080/15332861.2011.558456
5. Hussain, Irshad. (2012). A Study to Evaluate the Social Media Trends among University Students. Procedia - Social and Behavioral Sciences. 64. 639–645. 10.1016/j.sbspro.2012.11.075.
6. Kaplan & Haenlein (2010). Social Media, the Digital Revolution, and the Business of Media, The International Journal on Media Management 17(4):197-199 DOI:10.1080/14241277.2015.1120014
7. Keller (2009). Building strong brands in a modern marketing communications environment. Journal of marketing Communication 15(2), DOI:10.1080/13527260902757530.
8. Nga Ling Chan & Basak Denizci Guillet (2011) Investigation of Social Media Marketing: How Doesthe Hotel Industry in Hong Kong Perform in Marketing on Social Media Websites? Journal of Travel & Tourism Marketing, 28:4, 345-368, DOI: 10.1080/10548408.2011.571571
9. Patrick et al., (2013). Shopping and Word-of-Mouth Intentions on Social Media Journal of Theoretical and Applied Electronic Commerce Research 8(1) DOI: 10.4067/S0718- 18762013000100003
10. Reto Felix et al (2017) Elements of strategic social media marketing: A holistic framework Journal of Business Research, 2017, vol. 70, issue C, 118-126 DOI: 10.1016/j.jbusres.2016.05.001
11. Saadia.et.al (2013). An Emerging Method of Communication; Social Media Marketing and its Social and managerial Implications. World review of business research vol.3 No.1
12. Smith (2015). An Environmental social marketing intervention among employees: Assessing Attitude and Behaviour Change. The University of Sheffield, ISSN 1472- 1376.
13. Trusov et al., (2009). Effects of Word-of-Mouth versus Traditional Marketing: Findings from an Internet Social Networking Site. Journal of Marketing, DOI:10.2139/ssrn.1129352.
14. Zhao, Wenjin and Yun, Xu (2020). A Literature Review on Social Media Marketing: Social, Behavioral and Market-related Influences PACIS 2020 Proceedings. 92.**
Mr. Ravi I A, Dr. Sudharshan G M, "A Study on Impact of Social Media Marketing Influence Over Consumers Purchasing Decisions with Special Reference to Chikkamagaluru, Karnataka" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.12 issue 5, May 2023, pp.109-122 URL: https://doi.org/10.51583/IJLTEMAS.2023.12509
This research is a research of openness between children and stepparents. The purpose of this study is to describe in detail the openness of children with stepparents in building family harmony in Yogyakarta. The importance of this research is that if there is no openness in a stepfamily, it will lead to conflicts that lead to death. The theory used as material for data analysis is the theory of social penetration. This research method uses descriptive qualitative data collection techniques through in-depth interviews. Informant retrieval technique using purposive sampling technique, and triangulation of sources as a test of data validity. The data analysis technique went through several stages, namely data collection, data reduction, data display, and conclusion. This study found that the pair of informants I, DS & NR, and the pair of informants II, AP & SM had reached the stage of stable exchange. In the stable exchange stage, the couple's relationship is very intimate and there is no awkwardness at all between the two. The topic of conversation at this stage has led to personal things. As for the informant pair III, DA & VM only reached the stage of exploring affective exchange because DA felt that he was not open to VM and told VM about daily activities and when there was a need. Several factors that influence the stages of the relationship include cultural differences, gender, and personality neuroticism. Increasing conversations and increasing compatibility is the solution to the problem of children's openness with their stepparents.
**1. Ascharisa, A., & Anisa, A. (2020). Buku Ajar Komunikasi Interpersonal. Jawa Tengah: Pustaka Rumah Cinta.
2. Anshori Syaf, Lutfi dan Mulyadi. 2016. MOTIVASI MENIKAH LAGI: STUDI KASUS PASANGAN SUAMI ISTRI DARI SEORANG JANDA DAN DUDA YANG MENIKAH LAGI Dl USIA LANJUT. Jurnal Psikoislamika I Volume 13 Nomor 2 Tahun 2016
3. Agyta, V. (2018). KETERBUKAAN DIRI REMAJA DENGAN ORANG TUA TIRI (Studi Deskriptif Kualitatif Keterbukaan Diri Remaja Perempuan dengan Ibu Tiri Berkaitan Hubungan Asmara). Universitas Muhammadiyah Surakarta.
4. Angelia, Y. (2014). Self Disclosure Ibu Hamil di Luar Nikah Kepada Anaknya. E-Komunikasi, 2(2), 1–11.
5. Batoebara, M. U. (2018). Membangun trust (kepercayaan) pasangan dengan melalui komunikasi interpersonal. Jurnal Warta, 57(July 2018), 1–17. https://doi.org/10.46576/wdw.v0i57.144
6. Eliza, T. O. (2015). Hubungan Antara Keterbukaan Diri Dengan Keakraban Pada Mahasiswa Fakultas Pertanian dan Peternakan UIN SUSKA Riau.
7. Fensi, F. (2017). Mendengarkan Sebagai Model Komunikasi Untuk Memahami Remaja. Psibernetika, 9(2). https://doi.org/10.30813/psibernetika.v9i2.471
8. Gainau, M. (2009). Keterbukaan Diri Siswa Dalam Perspektif Budaya dan Implikasinya Bagi Konseling. Sekolah Tinggi Agama Kristen Protestan Negeri (STAKPN) Papua.
9. Herdiansyah, H. (2014). Metode Penelitian Kualitatif untuk Ilmu-Ilmu Sosial. Jakarta: Salemba Humanika.
10. Hayati, A., Yuswadi Program Studi Sosiologi, H., & Universitas Jember Jln Kalimantan, F. (2019). Pola Hubungan Ketetanggaan di Masyarakat Urban: Studi Kasus di Kampung Osing, Jember (The Pattern of Neighbourhood Relation in Urban Society: Case Study in Kampung Osing, Jember). Jember E-SOSPOL, 1, 14–20.
11. Huda, K. (2016). Peningkatan Keterampilan Sosial Melalui Bermain Benteng-Bentengan (Penelitian Tindakan Kelas pada Kelas B TK Nurul Arafah NW, Desa Sambelia, Kec. Sambelia Tahun 2016). Jurnal Realita, 1(2).
12. Khalika, N. N. (2018). Macam-Macam Sikap Anak Saat Orangtua Menikah Lagi. Diambil 16 Juli 2021, dari https://tirto.id/macam-macam-sikap-anak-saat-orangtua-menikah-lagi-c89L
13. Larasati, Tyas dan Sutarso, Joko. (2023) Pola Komunikasi Keluarga Antar Saudara Tiri Dalam Membangun Hubungan. Skripsi thesis, Universitas Muhammadiyah Surakarta. Liliweri, A. (2015). Komunikasi Antar Personal. Jakarta: Remaja Rosdakarya.
14. Maiaweng, P. C. D. (2017). Perceraian dan Pernikahan Kembali. Jurnal Jaffray, 15(1), 97. https://doi.org/10.25278/jj71.v15i1.237
15. Mawarni. (2017). Hubungan Antara Keharmonisan Keluarga dengan Rasa Percaya Diri pada Siswa SMP Negeri 3 Kota Jambi. STIE Perbanas Surabaya, 0–
16. 16. Mufidatu Z, F., & Sholichatun, Y. (2016). Penerimaan Diri Remaja yang Memiliki Keluarga Tiri. Psikoislamika : Jurnal Psikologi dan Psikologi Islam, 13(1), 29. https://doi.org/10.18860/psi.v13i1.6407
17. Muhtar, A. (2018). Relasi Ayah dengan Anak Tiri dan Implikasinya Terhadap Pembentukan Keluarga Sakinah. Universitas Islam Negeri Maulana Malik Ibrahim.
18. Mulyana, D. (2016). Pengantar Ilmu Komunikasi. Bandung: PT Remaja Rosdakarya.
19. Naibaho, F. (2020). Keterbukaan Remaja Kepada Orangtua Untuk Membahas Permasalahan Pacaran. Universitas Airlangga.
20. Novianti, R. D., Sondakh, M., & Rembang, M. (2017). Komunikasi Antarpribadi Dalam Menciptakan Harmonisasi (Suami Dan Istri) Keluarga Didesa Sagea Kabupaten Halmahera Tengah. Acta Diurna, 6(2), 1–15.
21. Novianti, E. (2019). Teori Komunikasi Umum dan Aplikasinya. Yogyakarta: Penerbit Andi.
22. Nurhayati, E. (2012). Psikologi Perempuan dalam Berbagai Perspektif. Yogyakarta: Pustaka Pelajar.
23. Nurulita, I., & Setyaraharjoe, R. (2014). Interpersonal Communication Pattern of Broken Home’s Teens with their Parents in Surabaya to Minimize Juvenile Delinquency. Academic Research International, 5(2).
24. Oktarina, Y., & Yudi, A. (2017). Komunikasi dalam Perspektif Teori dan Praktik. (Y. . Sanyoto, Ed.). Yogyakarta: Depublish.
25. Pratiwi, A. (2016). Hubungan Antara Interaksi Sosial Sesama Rekan Kerja dengan Kinerja Karyawan di Rumah Sakit Umum (RSUD) Kalisari Batang. Universitas Muhammadiyah Surakarta.
26. Prawitasllri, J. E. (2016). Mengenal Emosi Melalui Komunikasi Nonverbal. Buletin Psikologi, 3(1), 27–43. https://doi.org/10.22146/bpsi.13384
27. Purba, B. (2020). Ilmu Komunikasi: Sebuah Pengantar. Medan: Kita Menulis.
28. Ratnasari, A. (2007). Komunikasi Harmonis Orang Tua dengan Anak. Mediator: Jurnal Komunikasi, 8(2), 345–352. https://doi.org/10.29313/mediator.v8i2.1247
29. Rhosyidah, K. (2015). Pengaruh Keterbukaan Diri Terhadap Ketrampilan Komunikasi Interpersonal Menantu Perempuan Pada Ibu Mertua di Daerah Karanganyar Probolinggo. Universitas Islam Negeri Maulana Malik Ibrahim.
30. Rossnanda, Titis (2011) KOMUNIKASI ADAPTASI KELUARGA DALAM REMARRIAGE. Undergraduate thesis, Faculty of Social and Political Sciences Universitas Diponegoro Semarang
31. Sagala, Desy Mariana, (2017). Pola Komunikasi Keluarga Tiri Batak dalam Resolusi Konflik Keluarga (Studi Kasus Dua Keluarga Tiri Batak di Kota Bandung). Skripsi Departement Ilmu Komunikasi FPIPS UPI, Bandung
32. Sangadah, U. (2014). Analisis Interpretasi Ekspresi Wajah Ditinjau Dari Latar Belakang Pendidikan dan Jenis Kelamin. Universitas Islam Negeri Maulana Malik Ibrahim Malang.
33. Sari, A., & Mulyana, O. (2015). Hubungan Antara Komunikasi Interpersonal Dengan Penyesuaian Diri Pada Guru di Sekolah Dasar Negeri Yang Meger. Jurnal Character, 03(2).
34. Sari, R., Andayani, T., & Masykur, A. (2006). Pengungkapan Diri Mahasiswa Tahun Pertama Universitas Diponegoro Ditinjau Dari Jenis Kelamin Dan Harga Diri. Jurnal Psikologi, 3(2), 11–25. https://doi.org/10.14710/jpu.3.2.11-25
35. Suciati. (2019). Komunikasi Interpesonal. Yogyakarta: Buku Litera.
36. Suherman, A. (2020). Buku Ajar Teori-Teori Komunikasi. Yogyakarta: Deepublish.
37. Suparman. (2017). Konsep Pernikahan Kembali Ditinjau dari Sudut Pandang Kekristenan.
38. Torana, Y. I. (2016). Komunikasi Interpersonal Antara Sebagai Atlet Bela Diri Muay Thay Profesionalisme. Jurnal E-Komunikasi Program Studi Ilmu Komunikasi Universitas Kristen Petra, Surabaya, 4.
39. UMA. (2013). Jurnal Universitas Medan Area. Jurnal Universitas Medan Area, 53(1), 3–4. http://dx.doi.org/10.1016/j.encep.2012.03.001
40. West, R., & Lynn, T. (2008). Pengantar Teori Komunikasi. Jakarta: Salemba Humanika.
41. Wiryanto. (2004). Pengantar Ilmu Komunikasi. Jakarta: Grasindo
42. Yudha, I. (2019). Hambatan Komunikasi Pada Mahasiswa Perantauan Asal Bali di Yogyakarta. Universitas Sebelas Maret Surakarta.
43. Yusuf, I., & Agus, A. (2019). Komunikasi Interpersonal Orang Tua Interpersonal Communication Between Stepparent and. Komunikasi interpersonal orang tua dan anak tiri dalam membangun kepercayaan, 6(2), 4848–4860.
44. Zuhria, N. A. (2013). Proximity dalam Komunikasi antara Dosen dan Mahasiswa Fakultas Dakwah IAIN Sunan Ampel Surabaya, 4(2), 2088. Diambil dari http://digilib.uinsby.ac.id/id/eprint/11159
45. Zulfiana, U. (2003). Menjanda Pasca Kematian Pasangan Hidup, 1(1), 1–10. Website: 1. Mau Keluarga Harmonis? Ini 12 Tips untuk Dicoba. (2020). Take 7 Maret 2021, from https://www.cermati.com/artikel/mau-keluarga-harmonis-ini-12-tips-untuk-dicoba**
Suciati, Alin Rizki Amita, "Children's Openness with Stepparents in Building Family Harmony: Case Study in Yogyakarta" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.12 issue 5, May 2023, pp.123-133 URL: https://doi.org/10.51583/IJLTEMAS.2023.12510
