Application of the C4.5 Algorithm for Predicting Banana Chips Production Demand (Case Study at UD. Sinar Sejahtera Medan)

M. Teguh wijaya; Rakhmat Kurniawan R

doi:10.36378/jtos.v7i2.3975

M. Teguh wijaya Universitas islam negeri sumatera utara
Rakhmat Kurniawan R State Islamic University of North Sumatra

DOI: https://doi.org/10.36378/jtos.v7i2.3975

Keywords: Prediction, Banana, C.45 Algorithm, Production Demand

Abstract

The rapid advancement of science and technology significantly impacts various aspects of life, including business operations. Technology plays a vital role in providing information and simplifying human tasks, addressing challenges faced by growing companies, particularly in managing sales fluctuations. Factors such as market competition, product quality, and consumer interest are critical for evaluating and improving sales strategies. UD. Sinar Sejahtera Medan, a food processing industry specializing in banana chips, faces challenges such as fluctuating raw material supply, impacting production and sales. To address this, a prediction system for raw material demand was developed, leveraging the C4.5 algorithm. The C4.5 algorithm was selected for its ability to generate decision trees from historical data, providing interpretable results and high accuracy in forecasting categorical outcomes. By analyzing past trends in raw material availability and usage, the algorithm predicts future supply needs, optimizing production planning and supporting sustainable business operations. This study's findings are expected to align with previous research, offering insights for better production and sales management.

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