Implementasi Weighted Moving Average Berbasis Web Untuk Prediksi Ikan Gabus Dan Mujaer (Studi Kasus Pasar Kiringan)
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Abstract
Fish trading in traditional markets such as Pasar Kiringan faced challenges in managing stock due to fluctuating demand. Inaccurate demand forecasting could result in either overstock or stockouts, directly affecting traders' profitability. This study aimed to develop a web-based forecasting system using the Weighted Moving Average (WMA) method to improve accuracy in predicting the demand for snakehead fish (ikan gabus) and tilapia (ikan mujaer). WMA was chosen because it assigned greater weight to recent data, making it more responsive to market trends. The system development included collecting historical sales data, designing a database and user interface, implementing forecasting logic, and evaluating performance using the Mean Absolute Percentage Error (MAPE). The system was built with PHP and MySQL and included features such as weight management, demand input, automatic prediction, and reporting. Testing results showed average MAPE values of 8.17% for snakehead fish and 9.98% for tilapia, indicating very high accuracy. However, a few months recorded MAPE values above 10%, reflecting seasonal deviations in demand. The system was expected to be a practical tool for traders to plan inventory more efficiently and support data-driven decision-making.
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