Implementasi Metode Fuzzy Tsukamoto Berbasis Web untuk Prediksi Produk Penjualan pada Toko Farid Mart

Abstract

Sales prediction constitutes a critical component in retail inventory management as it directly affects stock availability and operational efficiency. Farid Mart Store encounters challenges in determining optimal Stock levels due to fluctuating demand and reliance on manual calculation methods. This study aims to design and implement a web-based system for predicting product sales using the Fuzzy Tsukamoto method. The method is applied through fuzzification, rule-based inference, and defuzzification to generate precise prediction values. The variables employed include demand and inventory as input variables, and sales as the output variable. The system is developed using PHP programming language and MySQL database and modeled using Unified Modeling Language (UML). System evaluation is conducted using Black Box Testing to ensure functional conformity. The results indicate that the developed system improves the accuracy of sales predictions and supports more effective and efficient decision-making in inventory management.