INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,  
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)  
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
Farmer Crop Insurance Scheme Adoption process with application  
Theory of Planned Behavior (TPB)  
1 Mrs. R. Radhika, 2 Dr. P. Rengarajan  
1 Part-time Research Scholar, PG and Research Department of Commerce, Poompuhar College  
(Autonomous), Melaiyur, Tamilnadu India (Affiliated to Bharathidasan University). Thiruchirappali –  
620024. Assistant Professor, Department of Commerce, Idhaya College for Women, Kumbakonam.  
2 Assistant Professor & Research Advisor, PG and Research Department of Commerce, Poompuhar  
College (Autonomous), Melaiyur, Tamilnadu India (Affiliated to Bharathidasan University).  
Thiruchirappali – 620024.  
DOI : https://doi.org/10.51583/IJLTEMAS.2025.1411000072  
Received: 28 November 2025; Accepted: 04 December 2025; Published: 11 December 2025  
ABSTRACT  
The study found that farmers' awareness of crop insurance schemes has a positive and insignificant influence on  
their attitude toward the scheme. However, a lack of awareness hurts farmers' attitudes. Social norms  
considerably impact behavioural intention, with a C.R. of 1.868. Perceived behaviour control (PBC) has an  
insignificant influence on behavioural intention, while risk awareness has less impact. Awareness about crop  
insurance schemes significantly affects farmer behavioural intentions, with a positive attitude (3.45/5.0) and a  
significant impact on crop insurance behaviour. Perceived behaviour control has less impact on farmer crop  
insurance behaviour. The analysis considers income, attitude towards crop insurance, behavioural intention, and  
insurance behaviour as dependent variables. Results show no significant difference in education, attitudes, or  
insurance behaviour among different groups. Low-income farmers showed significant differences from middle-  
and high-income farmers, as per Scheffe's post-hoc tests. crop insurance and risk awareness explained a 34% (R  
squared) variance in farmers' attitude toward crop insurance towards the scheme. Attitude, Perceived behaviour  
control, social norms, Awareness about crop insurance schemes, and Knowledge about crop insurance, variables  
explain 43% variance in the behavioural intention of the farmers.  
Keyword: Perceived behaviour control, behavioural intention, crop insurance schemes  
INTRODUCTION  
Crop insurance protects farmers and cultivators, safeguarding them against financial losses resulting from  
anticipated crop failure caused by a range of uncontrollable natural factors. These factors include weather  
conditions, floods, pests, and diseases, among others. The actuarial aspect of crop insurance involves intricate  
calculations conducted by actuaries. This field is essentially a branch of statistics that deals with determining the  
probabilities of certain events occurring. A "catastrophe" refers to a sudden and severe disaster that strikes  
unexpectedly, leading to substantial losses. When a farmer faces a loss covered by the insurance policy, they can  
file a "claim" for indemnity, which is the payment made to them by the insurer. The "Sum Insured" is the  
specified amount mentioned in the policy, representing the maximum limit up to which the insurer will provide  
indemnity in the event of a covered peril resulting in a loss to the insured property. "Indemnity" is the  
compensation paid to insured farmers for their crop loss caused by insured perils. The amount is determined  
based on the extent to which the actual yield falls short of the coverage specified in the policy. The insurance  
policy includes a "Guaranteed Yield," which is the expected physical yield of the crop as stated in the policy.  
This guaranteed yield serves as a benchmark against which actual yields are compared when adjusting any losses.  
Crop insurance has been essential in managing agricultural risk globally, with various systems developed to  
protect farmers from losses due to weather anomalies. In India, crop insurance has a long history and has evolved  
over time, particularly with the implementation of the Pradhan Mantri Fasal Bima Yojana (PMFBY) in 2016.  
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This scheme primarily uses area-yield insurance mechanisms, which are designed to address crop yield losses  
across insured regions. Wang, Tack, and Coble(2019) To spur investments and innovations in agriculture, a  
robust crop risk transfer system is necessary. Because weather anomalies occur frequently and agricultural losses  
arise globally, agriculture insurance is a must to protect farmers. India has a long history of defending the farming  
community from a range of cultivation risks by putting in place several crop insurance systems that have  
undergone periodic modifications. India has a long history of defending the farming community from a range of  
cultivation risks by putting in place several crop insurance systems that have undergone periodic modifications.  
These insurance policies, which often cover plantation and horticultural crops, have grown in popularity.  
Singh and Singh (2018) study focusses on improving crop loss assessment in area-yield crop insurance products,  
which cover horticulture and plantation crops by the way data-driven approaches in field. These insurance  
mechanisms address climate change effects, and studies require a stronger market presence. The basis risk in  
area-weather insurance has increased due to concerns about low-quality weather records and the disparate  
relationship between weather parameters and agricultural productivity. The basis risk in area-weather insurance  
has increased due to concerns about low-quality weather records and the disparate relationship between weather  
parameters and agricultural productivity. India's PMFBY, launched in 2016, is an area-yield crop insurance  
scheme, focusing on determining crop yields through manual measurements, making it difficult to obtain  
unbiased estimates (Ray, Hasan, and Goswami., 2018).  
Active Corp Insurance Scheme in Tamilnadu:  
a) Modified National Agricultural Insurance Scheme (MNAIS) - The Department of Agriculture & Cooperation  
has selected several Agriculture Insurance Company of India Ltd., which have potentially provide insurance  
to agricultural sectors.  
b) The Weather Based Crop Insurance Scheme (WBCIS) provide safe cuard to farmers especially from  
unfavorable weather events like excess rainfall, frost, heat, and humidity, affecting the crop's growth season.  
c) The government-sponsored Pradhan Mantri Fasal Bima Yojana (PMFBY) is a crop insurance program that  
combined several stakeholders on a single platform..  
d) The Coconut Palm Insurance Scheme provides risk management assistance to farmer and marketer of  
susceptible to natural disasters, pests, and illnesses, covering damage or losses to coconut palm and nut  
output during the 2011-12 fiscal year.  
The four schemes are mostly used in insurance schemes in Tamilnadu (and the present research intent is to  
measure the acceptance and crop insurance behaviour of the farmers  
Objective of the study  
To study the farmer's attitudes of towards various crop insurance schemes  
To study farmer awareness about crop insurance scheme  
To explain the farmer crop insurance behaviour with application of The Theory of Planned Behaviour (TPB)  
THEORETICAL BACKGROUND  
The Theory of Planned Behaviour (TPB) is used to predict a person's intention to participate in a behaviour at a  
certain time and location. TPB is derived from the Theory of Reasoned Action (TRA). TRA originated in 1980;  
it was to provide an explanation for every behaviour that a person has control over. The TRB model's central  
idea is behavioural intent, which is influenced by attitudes towards the certain things that a behaviour will  
produce the desired result as well as subjective supports of the advantages and disadvantages of that result  
(Ajzen, 1991). The TPB is has five constructs that collectively explains a person's behavior. Rabiu et al., (2018)  
usethe TPB to explain the farmer adoption process of tactfulness in agricultural processes. Attitude is a major  
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determinant of behaviour intention as TPB. Farmers' attitude toward crop insurance scheme is studies by various  
authors; Jamanal Natikar and Halakatti (2019) study was carried out in Karnataka state (India) former have  
positive attitude to crop insurance in general but they were unhappy delay settlement of claims. Dhande (2017)  
Samota, Dangi, Yadav and Yadav (2024) former have positive attitude towards crop insurance scheme and he  
suggest benefits derived the positive attitude. He also suggests attitude play  
schemes.  
major role in crop insurance  
Adah, Chia, and Shaibu (2016) study on 240 rural Nigerian farmers reveals a negative perception of agricultural  
insurance schemes due to unclear communication about implementation procedures. Their reserach suggests  
enhancing communication and education could improve farmers' attitudes and participation in such programs.  
Johari, Saili, Ahmad and Azam (2024) study suggests that enhancing farmers' awareness of crop insurance can  
improve their perception of its reliability, leading to more positive attitudes towards insurance schemes,  
ultimately improving financial security and resilience. Mohamad Basir, Roslan, Zakaria, Nasron Ooi, and  
Anggraini (2024) reveals that smallholder farmers' awareness of crop insurance, risk attitudes, and farm size  
significantly influence their adoption of insurance schemes. further their work suggest that awareness programs  
and individual farmer characteristics.  
H1) Awareness about crop insurance schemes significantly affects attitude towards a crop insurance scheme  
H2) Risk awareness significantly affects attitude towards crop insurance schemes.  
RESEARCH METHODOLOGY  
The present research uses comes under category of behaviour studies and a questionnaire was adopted in various  
earlier studies in the field. Attitude and Social norms were adopted from Rabiu et al., (2018). Perceived  
behavioural control and behavioural intention adopted (Ajzen, 1991)and used with a slightly modified manner.  
Awareness about crop insurance and risk awareness were five and four items which were adopted Rabiu et al.,  
(2018).  
Sample determination: the present research collects schedules from 129 farmers on a simple random sampling  
method in the Thanjavur and Thiruvarur districts of Tamilnadu. The present study also uses MSEM to execute  
the research design framed on the basis theory of planned behavior. Mean is the arithmetical average of a group  
of scores, and standard deviation measures the variability of data about the mean score.  
One-way ANOVA is used to test the difference between the mean scores of more than two groups. In the study,  
ANOVA is used to test the hypotheses of difference in the level of impact by various socio-demographic  
variables age and income level on attitude towards crop insurance, behavioral intention, and insurance behaviour  
as dependent variables. ANOVA analysis was used to find a significant difference among the groups and Post  
Hoc (Scheffe) Tests were conducted to find which group differs from others.  
The study used a Multi-Structural Equation Modeling (MSEM) approach to test hypotheses. Validity tests  
included Exploratory Factor Analysis (EFA), Discriminate Validity (DV), Convergent Validity, Average  
Variance Extracted (AVE), Cronbach's Alpha (R), and Confirmatory Factor Analysis (CFA). These tests ensure  
accurate and reliable measurement of constructs, providing a solid foundation for testing hypotheses using  
MSEM.  
The data was analyzed using SPSS version 21, with most items loading onto their variables. Confirmatory Factor  
Analysis (CFA) was performed to assess convergent and discriminant validity. The Average Variance Extracted  
(AVE) value was above 0.7, indicating excellent variance capture. Cronbach's alpha was calculated, with all  
values exceeding the acceptable threshold of 0.70, confirming data reliability and internal consistency.  
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Table 1 Master Validity Table  
CR  
AVE  
MS  
V
MaxR(H  
)
OD  
PRO  
CI  
CU  
RT  
VC  
MMP  
PP  
0.95  
2
0.77  
0
0.05  
7
0.958  
0.993  
1.002  
0.973  
0.855  
0.853  
1
2
3
4
5
6
0.877  
0.94  
3
0.78  
0
0.05  
7
0.238**  
*
0.883  
0.018  
-0.089  
0.065  
0.93  
0
0.73  
0
0.04  
1
0.169**  
-0.023  
0.052  
0.855  
-0.036  
0.004  
-0.007  
0.92  
3
0.75  
2
0.00  
8
0.86  
7
0.85  
0
0.58  
6
0.07  
0
0.04  
8
0.765  
0.81  
0
0.52  
3
0.02  
2
0.148*  
0.106  
-
0.02  
3
-0.001  
0.72  
3
†
0.91  
1
0.78  
1
0.04  
1
1.054  
0.847  
0.107†  
0.114  
*
0.203**  
*
0.06  
1
0.096  
0.01  
5
7
8
0.884  
0.79  
3
0.50  
0
0.07  
0
0.065  
0.063  
-0.005  
0.08  
4
0.264**  
*
-
0.03  
4
0.107  
0.70  
7
†
Source: primary data  
Subjective Norms (SN) are beliefs about how others in a social circle approve or disapprove of a behavior,  
influencing an individual's decisions and actions. Rahman and Husin (2022) these norms are influenced by  
social context and expectations, shaping an individual's approach to specific behaviors; this norms affects farmer  
adoption of insurance schemes.  
Furthermore, the subjective norm describes how social pressure affects a  
person's perspective on how to behave an action, and relates on an individual's behaviour (Husin & Rahman,  
2016).Suriansyah, Nurliza, Dolorosa, Rosyadi, Suswati (2024) suggest that subjective norms have significant  
influence of on the farmers’ intention to considered insurance scheme as well s risk management systems.  
H3) Social norms significantly affect the farmer's crop insurance intention.  
Perceived behavioral control (PCB) is an individual's perception of how easy or difficult it is to perform a exact  
behavior, influenced by factors like resources, skills, and external obstacles. Behavioural intention: This refers  
to the influencing desire factors that influence a given behaviour, where the stronger the intention to perform the  
behaviour, the more likely the behaviour will be performed. Hossain (2024)  
Farmers’ insurance purchase  
decisions were correlated with their experimental measures of risk aversion and perception behavioural control  
affects the crop insurance behaviour. Farmers who are risk-averse and have control over risk-taking have a  
significant impact on their behavioural intention.  
H4) PCB of farmer shasa significant impact on farmer crop insurance intention  
Johari, Saili, Ahmad, and Azam (2024)Crop insurance is crucial for rural farmers in developing countries,  
mitigating risks and providing shield against climate change and weather hazards. It enhances resilience,  
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stabilizes income, and supports agricultural sustainability and food security in vulnerable regions. examines the  
factors that influence paddy farmers' intention to purchase agriculture crop insurance being affect awareness and  
risk management behavior. Karthik and Ramalingam (2014); and Nirmal and Babu (2021) stated that scheme  
availability and knowledge about policy affect the insurance intention of farmers.  
H5) Risk awareness has a significant impact on farmer crop insurance intention  
H6) Awareness about crop insurance schemes significantly affects farmer crop insurance intentions  
H7) Attitude has a significant impact on farmer crop insurance intension  
This study provides empirical insights into the various factors influencing farmers' intentions to purchase crop  
insurance, including knowledge, risk attitude, and social factors. These insights can help identify areas for  
improvement and strategic interventions. By shedding light on farmers' intentions to purchase crop insurance,  
this study can contribute to the enhancement of risk mitigation strategies in agriculture. Farmers will be better  
equipped to safeguard their investments and ensure their economic stability. Furthermore, policymakers will  
benefit from this study's findings, which can guide the development and implementation of crop insurance  
policies that are more attuned to the needs and preferences of farmers.  
H8) The behavioural intention has a significant impact on farmer crop insurance behaviour  
H9) Perceived behaviour control of farmers has a significant impact on farmer crop insurance behaviour  
Table 2 Variable mean score and Slandered deviation  
S.no  
Mean score  
3.51  
Slandered deviation  
1
2
3
4
5
6
Awareness about crop insurance,  
Risk awareness  
0.78  
0.56  
0.39  
0.56  
0.34  
0.53  
2.76  
Social norms,  
3.10  
Attitude  
3.45  
Perceived behaviour control  
2.35  
Awareness about crop insurance  
schemes,  
3.22  
7
8
9
Risk awareness  
3.09  
3.55  
2.35  
0.71  
0.31  
0.45  
behavioural intention  
Perceived behavior control  
Measured Structural Equation Model - The hypotheses tested in MSEM based on three exogenous (attitude,  
buying intent, and buyer behaviour variables) and five endogenous (awareness, Knowledge, PBC, and perceived  
behavioural control)  
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The model summary was prepared with the "Model Fit Measures", AMOS Plugin developed by Gaskin and  
Lim (2016) and the model has been an excellent fit for the analysis. Hu and Bentler (1999) suggested five  
important measures and threshold for this model (in table).The table shows that the model is an excellent fit for  
the analysis except one measurement such as RSMR which is inacceptable level.  
Table 3Results of the Model Fitness  
Measure  
CMIN  
DF  
Estimate Threshold  
Interpretation  
--  
844.132  
458  
--  
--  
--  
CMIN/DF  
CFI  
1.843  
0.969  
0.050  
0.044  
0.984  
Between 1 and 3  
>0.95  
Excellent  
Excellent  
Acceptable  
Excellent  
Excellent  
SRMR  
RMSEA  
P Close  
<0.08  
<0.06  
>0.05  
(Output generated by AMOS graphic 21version)  
Table 4Variance Explained  
S.No  
Dependent variable  
Independent Variable  
Variance  
Explained  
1
2
Attitude  
Awareness about crop insurance, Risk awareness  
34%  
43%  
Buying intent  
Attitude, Perceived behaviour control, social norms,  
Awareness about crop insurance schemes, Knowledge  
about crop insurance  
3
Buyer behaviour  
behavioural intention, Perceived behaviour control  
37%  
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Source: primary data  
The dependent variables awareness about crop insurance and risk awareness explained 34% (R squared) variance  
in farmers attitude crop insurance towards scheme. Attitude, Perceived behaviour control, social norms,  
Awareness about crop insurance schemes, Knowledge about crop insurance, these variables explain 43%  
variance in the behavioural intention of the farmers. behavioural intention, Perceived behaviour control explains  
37.5%variances in buyer behaviour  
Table -5: Hypotheses Results (unstandardized Regression weights)  
Independent  
Dependent  
Estimate  
S.E.  
C.R.  
P
Variables  
Variable  
H1  
Awareness towards crop  
insurance,  
Attitude  
<---  
0.031  
.011  
-.999  
.318  
H2  
H3  
H7  
H4  
H6  
Attitude  
<---  
<---  
<---  
<---  
Risk awareness  
Social norms,  
.020  
.389  
.144  
.000  
.011  
.208  
.058  
.023  
1.970  
1.868  
2.494  
.019  
.047  
.062  
.011  
.985  
Buying intent  
Buying intent  
Buying intent  
Attitude  
Perceived behaviour control  
Awareness about crop  
insurance schemes,  
Buying intent  
.089  
.039  
2.257  
.022  
H5  
H8  
H9  
Buying intent  
Buyer behavior  
Buyer behavior  
Risk awareness  
.017  
.089  
.058  
.037  
.039  
.050  
.440  
2.257  
1.149  
.660  
.022  
.251  
<---  
<---  
behavioural intention  
Perceived behavior control  
Source: primary data Output generated by AMOS graphic 23 version  
Results and Interpretation:  
H1 is rejected and it suggests that awareness about crop insurance schemes have a positive and insignificant  
influence on attitude towards a crop insurance scheme. H2) Attitude towards crop insurance schemes is  
significantly affected by the risk awareness of farmers in the study area. Farmers' awareness of the insurance  
scheme has an average score of 3.10 and a high deviation of 0.78. It suggests a lack of awareness about schemes  
has adverse effect on attitude of farmers.  
H3 is approaching a significant level and it suggests that social norms have a considerable impact on the  
behavioral intention with C.R of 1.868.H4 is rejected and it suggest that Perceived behaviour control(PBC) has  
an insignificant influence on behavioural intention. This result is against Johari et al (2024) and we can suggest  
that the PBC average score is also 2.35 maximum of 5, farmers study PBC role in the study area has less impact  
on farmer behaviour.  
H5 is rejected and it suggests that risk awareness has less impact on farmer crop insurance intention. it suggests  
that farmer risk does not pay considerable importance to risk awareness.  
H6 is accepted and it suggest that  
awareness about crop insurance schemes significantly affects farmer behavioural intensions.H7 is accepted with  
p value less than 0.05 and as per our bases theory of study attitude played major role in behavioural intention  
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this finding is in line with earlier studies of Jamanal et al., (2019); Nirmal and Babu (2021). H7 the result also  
suggests that farmer in the study area have positive attitude (3.45/5.0) towards the crop insurance schemes.  
H8 is accepted, and present research uses TPB, as per bases theory to study the farmer behaviour, and behavioural  
intentions significantly affects the crop insurance behaviour. The result supports earlier studies such as that  
behavioural intention has a significant impact on farmer crop insurance behaviour Hossain (2024); Rabiu et al.,  
(2018). H9 is rejected and it suggests that perceived behaviour control has less impact on farmer crop insurance  
behaviour in the study area.  
Age of the sample Respondents  
Table -6: Respondent Age  
Frequency  
Percent  
Valid  
Percent  
Cumulative  
Percent  
Age level  
18-25  
17  
53  
13.1  
41.1  
24.0  
14.2  
7.6  
13.1  
41.1  
24.0  
14.2  
7.6  
13.1  
54.2  
78.2  
92.4  
100.0  
25-35  
35-45  
31  
45-55  
18  
55-above  
10  
Total  
129  
100.0  
100.0  
Source: Primary Data  
The above table indicates that most of the respondents are middle-aged group people. The study avoids the  
minor respondents in their analysis. The age group above 55 is the minimum participant group 53% of the  
respondents come within the age of 35.  
The gender of the sample Respondents  
Table -7: Respondent Gender Details  
Gender  
Frequency  
Percent  
Valid  
Percent  
Cumulative  
Percent  
Female  
Male  
54  
75  
42.8  
57.2  
42.8  
57.2  
42.8  
100.0  
Total  
100.0  
100.0  
Source: Primary Data  
H10) There is no significant difference among different age groups and attitudes towards crop insurance  
H11) There is no significant difference among different age groups and buying intention towards crop  
insurance  
H12) There is no significant difference among different age groups and crop insurance buying behavior.  
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Demographic variable role on farmer crop insurance behaviour  
Kumari,Singh,Mishra,Sinha, and Ahmad (2017) study socio-economic variables' role in the adoption of crop  
insurance schemes and suggest that income and education play a major role in the crop insurance adoption  
process. The descriptive statistics show that Attitude towards crop insurance schemes is positive with a second  
high mean score (3.51) for this study. In this study, consumer age effects on attitude towards crop insurance,  
behavioural intention, and insurance behavior were tested. The result is illustrated in below table (ANOVA  
with Post Hoc test). Statistical analysis and results (Age and study variables) One-way ANOVA tells us whether  
there is any significant difference in the mean scores of the dependent variable across the groups. Post-  
hoc tests were done to find out where these differences lie‖ (Pallant, 2007). The present study consists of an  
unequal group in size, so the researcher goes with Scheffe's Post – hoc tests which are most suitable for  
unequal groups.  
Table 8Independent Variable: Age  
Type III  
Sum of  
Squares  
Mean  
Square  
Observed  
Powerb  
dependent  
Df  
F
Sig.  
H10  
Attitude towards crop insurance  
schemes  
1.267  
4
.322  
.480  
.651  
.165  
H11  
H12  
buying intention  
12.65  
3.45  
3
4
4.152  
.836  
6.52  
1.25  
.000  
.277  
.971  
.394  
crop insurance behavior  
Source: Primary Data  
First the researcher takes age as an independent variable and attitude towards crop insurance, behavioral  
intention, and insurance behaviour as dependent variables. The table illustratesthat H10 and H12 were accepted  
at @5% significance in different age group respondents and attitudes towards crop insurance schemes mean and  
crop insurance behaviour do not differ significantly. The study found that attitudes towards crop insurance and  
behaviour were not statistically significant, but buying intention was significantly influenced. Schaffer’s post-  
hoc tests suggest that farmers aged 45-55 had higher buying intentions, highlighting the importance of age in  
evaluating factors influencing crop insurance adoption among farmers.  
H13) There is no significant differences among different income groups and attitudes towards crop insurance.  
H14) There is no significant difference among different income groups and buying intention towards crop  
insurance.  
H15) There is no significant difference among different income groups and crop insurance buying behaviour.  
Table - 9Independent Variable: Income  
Sum of  
Squares  
Mean  
square  
Observed  
Powerb  
Source  
Df  
4
F
Sig.  
.416  
.074  
.033  
H13 Attitude  
H14 buying intention  
5.471  
8.357  
1.368  
2.786  
2.837  
1.186  
2.429  
2.480  
.374  
.606  
.708  
3
H15crop insurance  
behavior  
11.349  
4
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In this analysis, (Table-9) the researcher takes First the researcher takes income as an independent variable and  
attitude towards crop insurance, behavioural intention, and insurance behavior as dependent variables and results  
are illustrated in the above table. H13 and H14 were accepted @5% significant which means that their no  
significant difference among various education and attitudes towards crop insurance schemes mean and crop  
insurance behaviour. The results reveals that education does not significantly impact crop insurance behaviour,  
while crop insurance behaviour has a significant impact. Low-income farmers showed significant differences in  
crop insurance behaviour compared to middle- and high-income farmers, emphasizing the need for tailored  
approaches to support low-income groups in accessing financial tools.  
CONCLUSION  
The intention to purchase crop insurance is a crucial aspect of the agricultural landscape. This study is motivated  
by the pressing need to better understand the factors influencing this intention, with the ultimate goal of  
enhancing risk management, economic resilience, and policy effectiveness in agriculture. The contributions of  
this study will be invaluable to farmers, policymakers, and the entire agricultural sector in achieving a more  
sustainable and secure future.  
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue XI, November 2025  
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