Decision Model of Interest in Buying East Asian Food Products based on Halal Awareness and Religiosity Values using the Classification Machine Learning Algorithm Method
Abstract
Indonesia has not yet developed a strong halal food industry despite its potential and remains more of a target market. With rapid digital transformation, cultural influences, and social media trends, halal awareness among Indonesians needs to be strengthened. This study aims to explore the most influential factors on buying interest in East Asian food products based on halal awareness and religiosity values, to model purchase decisions, and stimulate the model. A descriptive quantitative method was used with 302 Muslim respondents aged 15-60+ in Jabodetabek who are active social media users. Data were analyzed using five machine learning classification algorithms: Naïve Bayes, Decision Tree, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Logistic Regression. Validity and reliability test were conducted to ensure the quality of the instruments. Results show that the key factors influencing buying interest are halal certification, certification institutions, and brand image. Among the models tested, the K-Nearest Neighbors algorithm delivered the performance with 97% accuracy and an AUC of 0,91. This model effectively classifies consumer interest in East Asian food products. The findings highlight the importance of halal assurance and brand trust in shaping consumen behavior in Indonesia’s growing halal market.
Keywords– East Asian food products, Halal awareness, Machine learning classification, Purchase intention, Religious values
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DOI: http://dx.doi.org/10.36722/exc.v2i1.2341
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