Predicting Agricultural Product E-Commerce Usage Behavior In Indonesia With Machine Learning Algorithms - Irwandi, Putra; Oktavianto, Rizki; Adetyaa, Aulia; Sopian, Sopan (Universitas Negeri Yogyakarta, 2025)
This study aims to identify factors that predict the usage behavior of agricultural product e-commerce platform in Indonesia with a comprehensive approach using machine learning algorithms. The research model uses the theory of technology acceptance and use (UTAUT), which consists of variables of social influence, supporting conditions, usage behavior, performance expectancy, effort expectancy, behavioral intention, and supporting conditions. The data in this study were collected throuh an online survey. Model analysis uses a partial least square-structural equation model (PLS-SEM) approach. Furthermore, machine learning algorithms were used to analyze the relationship between elements in the research model. The results showed that behavioral intentions were predicted by performance expectations, effort expectations, social influence, and supporting factors. Agricultural product e-commerce usage behavior is influenced by these behavioral intentions. This study also emphasizes the importance of further research on the application of machine learning algorithms in predicting agricultural e-commerce consumption behavior. Keywords: UTAUT; Machine Learning Algorithms; Agricultural Product e-commerce ABSTRAK Penelitian ini bertujuan untuk mengidentifikasi faktor-faktor yang memprediksi perilaku penggunaan platform e-commerce produk pertanian di Indonesia dengan pendekatan komprehensif menggunakan algoritma machine learning. Model penelitian menggunakan teori penerimaan dan penggunaan teknologi (UTAUT), yang terdiri dari variabel pengaruh sosial, kondisi pendukung, perilaku penggunaan, harapan kinerja, harapan usaha, niat perilaku, dan kondisi pendukung. Data dalam penelitian ini diperoleh melalui survei online. Analisis model menggunakan pendekatan partial partial least square-structural equation model (PLS-SEM). Lebih lanjut, algoritma machine learning digunakan untuk menganalisis hubungan antar elemen dalam model penelitian. Hasil penelitian menunjukkan bahwa niat perilaku diprediksi oleh ekspektasi kinerja, ekspektasi usaha, pengaruh sosial, dan faktor pendukung. Perilaku penggunaan platform e-commerce produk pertanian dipengaruhi oleh niat perilaku tersebut. Penelitian ini juga menekankan pentingnya penelitian lebih lanjut mengenai penerapan algoritma machine learning dalam memprediksi perilaku konsumsi e-commerce pertanian. Kata Kunci: UTAUT, Algoritma Machine Learning, E-commerce Produk Pertanian