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All Journal Jurnal Pilar Nusa Mandiri Economic: Journal Economic and Business
Dewi, Amelia Citra
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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CLASSIFICATION OF CUSTOMERS’ REPEAT ORDER PROBABILITY USING DECISION TREE, NAÏVE BAYES AND RANDOM FOREST Dewi, Amelia Citra; Hermawan, Arief; Avianto, Donny
Jurnal Pilar Nusa Mandiri Vol. 20 No. 1 (2024): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v20i1.5243

Abstract

Limited customer information in sales data on e-commerce in Indonesia hinders companies in determining targeted marketing strategies, especially in targeting groups of potential customers to make repeat purchases. Sales data in the form of customers' names and cellphone numbers has been hidden by e-commerce, and only data is available in the form of products purchased, number of purchases, and customer addresses. So far, the methods used to determine potential customers mostly use more complete data features. Research that uses limited e-commerce data to determine potential customers is scarce. Several algorithms for predicting repeat purchases in e-commerce also have been widely used. However, the comparison of the performance of these methods in the context of e-commerce in Indonesia with limited data has yet to be discovered. In this research, the Decision Tree, Naive Bayes, and Random Forest methods were compared to classify potential customers using Maschere brand sales data from two e-commerce sites, namely Tokopedia and Shopee. The research results show that the Decision Tree algorithm achieved an accuracy of 90.91%, Naive Bayes achieved an accuracy of 37.50%, and Random Forest achieved the best level of accuracy, namely 93.94%. These results show that the Random Forest method is the best method for classifying customers' probability of repeat purchases. In the future, the results of this research can be developed again as a decision-making system to determine potential customers.
The role of human resource management on employee performance in the management of Pekalen rafting tourism in Probolinggo Maimunah, Khotijah; Dewi, Amelia Citra; Ikhsan, M Ariel; Hardiyanto, M Feri; Solihin, Ahmad Riadus; Kartikawati, Yeni
Economic: Journal Economic and Business Vol. 5 No. 1 (2026): ECONOMIC: Journal Economic and Business
Publisher : Lembaga Riset Mutiara Akbar (LARISMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/ejeb.v5i1.1419

Abstract

This study aims to analyze the role of human resources on employee performance in managing rafting tourism in Probolinggo. The adventure tourism industry, especially rafting tourism, requires optimal human resource management to ensure tourist satisfaction, safety, and business sustainability. This study uses a descriptive qualitative approach with a case study method on Pekalen Rafting tourism in Probolinggo. Data collection techniques were carried out through in-depth interviews, direct observation, and documentation studies with informants consisting of managers, rafting guides, operational staff, and support employees. The results of the study indicate that the role of human resources, including the recruitment process, training and development, and a fair compensation system, has a positive effect on employee performance in managing Pekalen Rafting tourism in Probolinggo. Good employee performance is reflected in the level of operational safety, customer satisfaction, and service efficiency. The conclusion of this study confirms that the role of human resources on employee performance is a key factor in increasing the competitiveness and sustainability of rafting tourism businesses.
Co-Authors Donny Avianto Hardiyanto, M Feri Ikhsan, M Ariel Kartikawati, Yeni Maimunah, Khotijah Solihin, Ahmad Riadus