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All Journal JITEEHA: Journal of Information Technology Applications in Education, Economy, Health and Agriculture
Trisna, Maria Rosalina
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Computer Science & IT Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering

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Utilizing Datamining to Predict Sales Trends Based on Historical Data Junda, Alby Afifuddin; Trisna, Maria Rosalina; Genohon, Yustino Prami; Akhdan, Farrel Muhammad Raihan; Salisu, Imam Auwal
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 3 (2024): October
Publisher : Lumina Infinity Academy Foundation

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Abstract

This study aims to compare the performance of the Naïve Bayes and Support Vector Machine (SVM) algorithms in predicting sales trends based on historical data. The results of the study show that SVM is more effective than Naïve Bayes with an accuracy of 34.74% compared to 15.49%. This study helps companies in making strategic decisions and improving operational efficiency. Data Mining is an important tool in predicting sales trends and improving prediction accuracy.
Co-Authors Akhdan, Farrel Muhammad Raihan Genohon, Yustino Prami Junda, Alby Afifuddin Salisu, Imam Auwal