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

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Classification of Used Car Prices Using the Naive Bayes Method Abillah, Bintang; Pratama, Djourdi Amrida; Baskara, Rizandi Agung; Praseptiawan, Mugi; Hanfiro, Pauline
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 2 No. 1 (2025): February
Publisher : Lumina Infinity Academy Foundation

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This research uses the Naive Bayes algorithm to predict used car purchasing decisions based on attributes such as brand, year of production, mileage, engine condition, completeness of features, and maintenance history. By applying the Gaussian Naive Bayes approach to handling continuous data, this research aims to develop a reliable prediction model while identifying the attributes that most influence purchasing decisions. The test results show that the prediction model achieved a correct accuracy level of 80%, and an incorrect accuracy of 20%, which indicates the ability of the Naive Bayes algorithm to handle data classification. This research provides insights that can support industry players in designing more effective sales strategies based on accurate data analysis.
Clustering Of Informatics Students Based On Understanding The Material Using The K-Means Method Irmayanti, Meiselina; Prasetyo, Naufal Ibra; Bria, Dionisia Kasilda; Paratu, Jeki Bani; Hanfiro, Pauline
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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The level of student understanding in coursework is a crucial determinant of academic success, reflecting both teaching quality and the effectiveness of applied learning methods. In the context of Informatics, challenges often stem from the complexity of subjects such as algorithms, programming, and data analysis, which require analytical and in-depth comprehension. However, differences in learning abilities, backgrounds, and styles often result in varying levels of understanding among students. This study investigates the application of k-means clustering as an innovative method to analyze academic data and classify students based on their understanding of course materials. By utilizing data such as exam scores, quiz results, and classroom engagement, k-means clustering identifies patterns in students’ comprehension levels, offering educators insights to tailor teaching strategies effectively. The findings of this study are expected to aid educators in designing targeted interventions, enhance learning processes, and support an inclusive and effective academic environment.
Hybrid Clustering with Deep Learning in E-commerce for Customer Segmentation: A Data-Driven Approach for Business Strategy Optimization Sidharta, Robertus; Riyadi, Agung; Hanfiro, Pauline; Handini, Mia
Journal of Information Technology application in Education, Economy, Health and Agriculture Vol. 3 No. 1 (2026): Vol. 3 No. 1 (2026): February
Publisher : Lumina Infinity Academy Foundation

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Customer segmentation is a strategic approach to understanding customer needs and preferences, especially in the dynamic e-commerce industry. Traditional clustering methods, such as k-means, are often used for this task, but have limitations in handling complex and high-dimensional data. In this research, we use a hybrid clustering approach that integrates deep learning for feature extraction with traditional clustering algorithms for customer segmentation. Uses Mall Customers Dataset from Kaggle, which includes customer demographic and shopping behavior data. Experimental results show that this approach is able to produce more accurate and meaningful segmentation. The visualization of the results shows significant patterns that can be used to develop more personalized and effective marketing strategies.
Co-Authors Abillah, Bintang Agung Riyadi Baskara, Rizandi Agung Bria, Dionisia Kasilda Handini, Mia Irmayanti, Meiselina Paratu, Jeki Bani Praseptiawan, Mugi Prasetyo, Naufal Ibra Pratama, Djourdi Amrida Sidharta, Robertus