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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika
Akkad, Muhammad Iqbal
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Computer Science & IT

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Journal : Sinkron : Jurnal dan Penelitian Teknik Informatika

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Implementation and Evaluation of Artificial Neural Networks for Product Sales Prediction at Basmalah Stores Akkad, Muhammad Iqbal; Hariyadi, Mokhamad Amin; Almais, Agung Teguh Wibowo
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 4 (2025): Articles Research October 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i4.15341

Abstract

This study aims to develop a product sales prediction system for Toko Basmalah located in the Malang Regency area by utilizing the Artificial Neural Network (ANN) algorithm. A quantitative approach was employed, using time series sales data obtained from the Marketing Division of PT. Sidogiri Pandu Utama for the period of January 1, 2023, to December 31, 2024. The research stages included data collection and preprocessing, normalization using the min-max scaling technique, data splitting into training and testing sets, ANN model experimentation with various data compositions, and performance evaluation based on the Mean Squared Error (MSE) metric. The experiments were conducted five times using the Kaggle Editor platform. The results showed that the ANN-E model with a specific architecture achieved the lowest MSE value of 34.38%, making it the most optimal model for sales prediction. These findings are expected to assist in making better decisions regarding stock management, sales planning, and business strategies in the retail environment.
Co-Authors Agung Teguh Wibowo Almais Mokhamad Amin Hariyadi