Developing a Predictive Model to Evaluate Factors Influencing the Success of a Livestock Business in Indonesia
DOI:
https://doi.org/10.33379/gtech.v8i3.4770Keywords:
AHP, livestock business, MLR, predictive modelAbstract
The increasing population in several countries, including Indonesia, leads to a heightened demand for food, a significant portion of which comes from animal sources. Various efforts have been made by different parties to meet the soaring demand for animal meat. Although there is a growing trend of individually managed livestock enterprises, failure risks are frequent, often resulting in suboptimal economic outcomes. Accordingly, this study aims to evaluate the factors influencing the success of livestock businesses. Furthermore, this research also intends to develop a mathematical model to predict potential profits, taking these factors into account. The framework is developed based on the analytic hierarchy process (AHP) and multiple linear regression (MLR). This proposed framework is demonstrated in a pig farming business located in Wamena, Papua, Indonesia. The results indicate that out of six identified criteria, four are most significant in affecting livestock success: culture (C5), pig breed (C2), gender (C1), and physical condition (C4). Additionally, to build a mathematical model for predicting profits, a dataset comprising 44 combinations of sub-criteria has been constructed. The mathematical model shows a prediction capability of 84.3%, indicating very strong correlation. Although the livestock success evaluation model developed in this study is tested only on one type of livestock, the framework, in general, can be adopted for other types of business ventures.
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Copyright (c) 2024 V. Reza Bayu Kurniawan, Retno Widiastuti, Syamsul Ma'arif, Dina Yulina Heriyani, Endil Linggi, Yudhistira Wahyu Septianto
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