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All Journal International Journal of Research in Vocational Studies (IJRVOCAS) Frontier Management Science (FMS)
Loreño, Dustin
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Determinants of Repayment Performance of Agricultural Loans Clients of RBDI, Abuyog Branch Loreño, Dustin; Teves, Joviel
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 3 No. 3 (2023): IJRVOCAS - December
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v3i3.213

Abstract

The study aimed to present the profile of the agricultural loan clients of RBDI, describe the loan assessment process, describe the loan monitoring process in RBDI, identify the determinants of loan repayment performance of RBDI agricultural loan clients and to recommend courses of action to improve loan application assessment, loan monitoring, and loan collection activities of RBDI. The study used the Logit Regression Analysis and the model Y = β0 + β1X1 + β2X2 + β3X3 + β4X4 + . . . . . . . βnXn + e was developed. The binary response is non-payment (default) and payment (non-default). The determinants were the socio-demographic and socio-economic characteristics of the agricultural loan clients, as well as the loan application and monitoring activities of the bank. The profile of the agricultural loan clients of RBDI showed commonalities of the clients in terms of age (63% are above 45 years old), most of them were not able to finish college (53% secondary level) and most are married (77%) with more than 3 dependents (73%).  Age was determined as a statistically significant factor affecting the non-payment or loan default. The increase in family size and schooling dependents also raises the probability of default. The result that higher educational level and increase in dependents reduces the probability of default has to be further verified. As the size of land increases and the farming experience increases, the probability of loan default decreases.
Linear Programming Approach for Optimal Profit Mix of Cassava Grates and Flour Loreño, Dustin; Cirenuela, Junmarie; Cagabhion, Harold; Jurial, Mitchelyn; Apas, Genalyn; Remoto, Elma; Fuentes, Carla Jean; Casas, Marie Cris; Falcone, Quenne; Gonzaga, Luzviminda; Dawal, Annabeth; Cuesta, Mary Joy; Flores, Paulo; Ortiz, Jessica
Frontier Management Science Vol. 1 No. 1 (2024): FMS - January
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/fms.v1i1.257

Abstract

The research aimed to identify the optimal combination of cassava grates and flour to maximize the profit of a project initiated by the Philippine Root Crops Research and Training Center at Visayas State University. The findings revealed that the most profitable combination consisted of 125 kg of cassava grates and 25 kg of flour, resulting in an optimum profit of Php 4,250.00 for the entire production. The study highlighted that the project was constrained by limited inputs, preventing it from exceeding the optimal quantities of the two products. To enhance the profitability of both products, adjustments in the resources utilized during production were necessary. While the current production of cassava grates falls below the optimum quantity, indicating room for increased production with the existing inputs, the production of cassava flour had already reached its optimal level. To achieve optimal quantity and profit, the project must implement strategies to prevent resource wastage.
Verbal and Non-Verbal Marketing Strategies of Vegetable Vendors During Market Day in Aborlan, Public Market Tulukan, Joshua Jay; Saldevia, Gladys Joy; Palermo, Dexter; Tilos, Daisy; Villaran, Jeffrey; Reyes, Princess Delos; Sebido, Maria Asela; Loreño, Dustin
Frontier Management Science Vol. 1 No. 1 (2024): FMS - January
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/fms.v1i1.260

Abstract

The study was conducted to evaluate both the verbal and non-verbal marketing strategies employed by vegetable vendors during Market Day at Aborlan Public Market. The study also aimed to assess the advantages and effects of these strategies on the business, as well as to identify the challenges encountered in vegetable marketing. Employing a descriptive method, the respondents consisted of vegetable vendors present at Aborlan Public Market during Market Day, selected based on their availability for interviews. The study revealed that vegetable vendors derived benefits from the implementation of their chosen verbal and non-verbal marketing strategies. These strategies proved effective in attracting buyers, promoting products, building relationships with customers, and fostering customer retention. Furthermore, the utilization of these strategies enabled vegetable vendors to enhance their sales performance.
Comparative Analysis of Forecasting Techniques for Enhancing Coconut Oil Export Predictions in the Philippines Loreño, Dustin; Olpenda, Aimee
Frontier Management Science Vol. 1 No. 2 (2024): FMS - April
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/fms.v1i2.267

Abstract

In the agricultural domain, the accurate forecasting of crop yields is crucial for economic stability and planning. The Philippines, being one of the world’s largest producers of coconut oil, has a significant portion of its agricultural sector influenced by the predictability of this commodity’s yield. While traditional forecasting methods have been employed, their accuracy fluctuates, necessitating the exploration of more reliable techniques. This study evaluates Grey Forecasting, Moving Average, Forecast by Forecasting Sheet, and Regression Analysis methods for predicting coconut oil production, comparing them over two decades. Through rigorous statistical analysis using measures like MAD, MSE, and MAPE. Grey Forecasting emerges as more consistent and accurate. In 2023, there was an increase of approximately 13.86% compared to 2022. In 2024, this figure rose to about 25.08% compared to 2023. Similarly, in 2025, there was an increase of roughly 18.17% compared to 2024. The study's contribution lies in its comprehensive long-term data analysis, offering new insights into Grey Forecasting's application. These findings could significantly impact Philippine agricultural planning and policies, prompting further research to refine forecasting methods. Emphasizing the value of advanced predictive models in agriculture, the study advocates for informed decision-making and resource allocation. Future research should focus on refining these models by incorporating broader datasets and advanced algorithms to improve accuracy and reliability.
Co-Authors Apas, Genalyn Cagabhion, Harold Casas, Marie Cris Cirenuela, Junmarie Cuesta, Mary Joy Dawal, Annabeth Falcone, Quenne Flores, Paulo Fuentes, Carla Jean Gonzaga, Luzviminda Jurial, Mitchelyn Olpenda, Aimee Ortiz, Jessica Palermo, Dexter Remoto, Elma Reyes, Princess Delos Saldevia, Gladys Joy Sebido, Maria Asela Teves, Joviel Tilos, Daisy Tulukan, Joshua Jay Villaran, Jeffrey