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Journal : JURNAL EKSBIS

TOURIST CLUSTER ANALYSIS FOR THE DEVELOPMENT OF KE'TE' KESU' TOURISM OBJECT Putri Dalipang, Mutiara; Kurniasari Wibisono , Lisa; Marchelin, Marchelin
JURNAL EKBIS Vol 26 No 1 (2025): Jurnal Ekbis : Jurnal Analisis,Prediksi dan Informasi
Publisher : Universitas Islam Lamongan

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Abstract

This study aims to analyze the clustering of tourists visiting the Ke'te' Kesu' tourist attraction to support the development of more effective marketing strategies and tourism services. The research employs a K-Means clustering algorithm, which groups tourists based on their socio-economic characteristics and visit preferences. Data were collected through questionnaires distributed to tourists during a specific period. The analysis results indicate that tourists are divided into two main clusters. Cluster one (C1) consists of high-income to very high-income tourists who tend to seek exclusive and premium travel experiences. Cluster two (C2) includes the majority of tourists who are students with low to very low incomes, preferring educational tourism and affordable access. The implications of this study suggest that tourism managers should offer customized travel packages tailored to each cluster, such as premium services for high-end tourists and educational programs for students. Additionally, infrastructure improvements, sanitation facilities, and digital marketing optimization are key recommendations to enhance Ke'te' Kesu's appeal as a cultural tourism destination.
ANALYSIS OF CREDIT FEASIBILITY USING THE DECISION TREE METHOD (Case Study at CP Rantepao Pawnshop) Tando, Sisilia; Marchelin, Marchelin; Devi Y. Pompeng, Olivia
JURNAL EKBIS Vol 26 No 1 (2025): Jurnal Ekbis : Jurnal Analisis,Prediksi dan Informasi
Publisher : Universitas Islam Lamongan

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Abstract

This study aims to analyze the feasibility of providing credit at Pegadaian CP Rantepao using the decision tree method. Quantitative research is the method used. The population in this study was 413 customer data, 100 of which were used as samples provided by Pegadaian CP Rantepao. The type of data used is secondary data, in the form of customer data registered at Pegadaian CP Rantepao. The data analysis used in this research is using Data Mining Clarification with the C4.5 Algorithm Method. The results showed that by using the Decision Tree method to determine customer status on CP Rantepao Pawnshop Customer data, it was able to classify or predict customer data into categories, namely current and bad using 5 attributes, namely gender, loan time, collateral, product type and installations. Based on tests that have been carried out using Confusion Matrix, the accuracy value is 75.71%.
SEGMENTATION OF MSMEs BASED ON FINANCIAL MANAGEMENT PATTERNS (Case Study of MSMEs in the Industrial Sector in Rantepao District) Kondo, Marlina; Marchelin, Marchelin; Kurniasari Wibisono, Lisa
JURNAL EKBIS Vol 26 No 1 (2025): Jurnal Ekbis : Jurnal Analisis,Prediksi dan Informasi
Publisher : Universitas Islam Lamongan

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Abstract

This study uses a quantitative research approach with the aim of analyzing the segmentation of MSMEs based on financial management patterns in the Rantepao District. Using a clustering method with the K-Means algorithm, this study groups MSMEs based on the characteristics of financial recording, planning, reporting, and control that are implemented. The results show that there are two main clusters: the first cluster (68%) consists of MSMEs that still use manual financial recording, have unclear financial planning, and lack structured financial control. Meanwhile, the second cluster (32%) consists of MSMEs that have adopted more systematic financial recording with tools such as Microsoft Excel or accounting applications, and have regular financial reports and better cash reserves. Based on these results, interventions are needed in the form of financial literacy training, access to digital recording technology, and mentoring for MSMEs to improve financial stability and long-term sustainability.