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

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Analysys of Consumer Buying Behavior of Goods and Services Using The Naïve Bayes Method and Clustering Study in The Computer Service Shop Fahmi, Muchammad Alvi Nur; Marisa, Fitri; Conteh, Alusine
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 1 (2024): February
Publisher : Lumina Infinity Academy Foundation

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Based on the observation results at Anik Komputer as a company providing computer, printer, and other device services, online sales results have a significant influence on revenue generation. Therefore, it is necessary to know the most significant factors that influence consumers to buy goods and services online. This study aims to identify factors that influence purchasing decisions, evaluate consumer behavior patterns, and propose strategic steps based on web intelligent. The analysis method uses Data Mining with the Naïve Bayes and Clustering algorithms. The results of this study indicate that the factors that influence purchasing decisions at Anik Komputer are price, customer reviews, and stock availability. Customer segmentation based on purchasing patterns through Clustering analysis produces three main segments, namely loyal customers (30% of total customers) who contribute the most to total sales of 40%, price sensitive customers (50% of total customers) who contribute 45% to sales, and new customers (20% of total customers) who contribute 15% to sales. This analysis provides deeper insight into consumer behavior that can be applied in intelligent web-based marketing strategies to increase the effectiveness and efficiency of online sales.
Application of the Naive Bayes Algorithm to Predict The Purchase Decisions Puspitarini, Erri Wahyu; Masdiyanto, Andreas; Kiyosaki, Robert Baz; Hakiki, Sudrajad; Conteh, Alusine; Wafa, Fachrian Muhammad Ahzami
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 1 No. 2 (2024): June
Publisher : Lumina Infinity Academy Foundation

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This study applies the Naive Bayes algorithm to predict the decision to purchase used motorcycles based on attributes such as model, year of manufacture, price, engine capacity, and transaction results. Utilizing the Gaussian Naive Bayes approach for continuous data, this research aims to develop a reliable predictive model and understand the most significant attributes influencing purchasing decisions. The test results show that the predictive model achieves an accuracy rate of 75%, indicating the effectiveness of the Naive Bayes algorithm in handling data classification. This study provides insights that can help industry players enhance their sales strategies based on accurate data analysis.
Co-Authors Fahmi, Muchammad Alvi Nur Hakiki, Sudrajad Kiyosaki, Robert Baz MARIFANI FITRI ARISA Masdiyanto, Andreas Puspitarini, Erri Wahyu Wafa, Fachrian Muhammad Ahzami