IMPLEMENTATION OF THE NAIVE BAYES METHOD FOR CATERING SALES PREDICTION AT PT NEGARA RASA INDONESIA

Benifati Gulo; Syaeful Machfud

doi:10.62567/micjo.v3i2.2374

Authors

Benifati Gulo Pamulang University
Syaeful Machfud Pamulang University

DOI:

https://doi.org/10.62567/micjo.v3i2.2374

Keywords:

Naïve Bayes, Sales Prediction, Historical Data, Rapidminer, Classification

Abstract

This study discusses the implementation of the Naïve Bayes method to predict catering sales at PT.Negara Rasa Indonesia. The background of this study is based on the problem of suboptimal sales due to the absence of a structured sales prediction system. The Naïve Bayes method was chosen because of its simplicity, speed, and ability to classify data with a high degree of accuracy. The data used in this study is historical sales data from the last two years, which has undergone cleaning, labeling, and transformation into four sales categories, namely very popular, popular, fairly popular, and less popular. The testing process was carried out using RapidMiner software by dividing the dataset into training data and test data at various ratios of 80:20. The test results showed a very high level of accuracy, with the highest value reaching 91.41%. These findings prove that the Naïve Bayes method is reliable for predicting catering sales, thereby assisting decision-making in more efficient sales management and planning at PT. Negara Rasa Indonesia.

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