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All Journal Proceedings of KNASTIK INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) VOX EDUKASI: Jurnal Ilmiah Ilmu Pendidikan Fullerene Journal of Chemistry Abdimas Toddopuli: Jurnal Pengabdian Pada Masyarakat Journal Dynamic SainT Jurnal Pengabdian kepada Masyarakat Teaching English as a Foreign Language Overseas Journal (TEFLO) Jurnal Mosfet INFINITY : UKI TORAJA JOURNAL OF INFORMATION TECHNOLOGY Jurnal Pengabdian Masyarakat Bangsa TONGKONAN: Jurnal Pengabdian Masyarakat Agroland: Jurnal Ilmu-ilmu Pertanian Jurnal Sistem Informasi dan Teknologi Informasi
Eko Suripto Pasinggi
Program Studi Teknik Informatika, Universitas Kristen Indonesia Toraja
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Enhancing Tourist Experiences in North Toraja through K-Means Clustering-Based Recommendation System Palelleng, Srivan; Pasinggi, Eko Suripto; Rusman, Juprianus
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 10 No 1 (2026)
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v10i1.25597

Abstract

Background: North Toraja in South Sulawesi, Indonesia, is a culturally rich region with high tourism potential due to its unique traditions. The government has invested in infrastructure to boost tourism and regional income (PAD), but has insufficiently used information systems for promotion. An innovative system that can assist tourists in navigating the diverse attractions in North Toraja based on their interests needs to be developed. Objective: This research aims to develop a recommendation system for tourist attractions in North Toraja using K-means Clustering and the Similar Characteristics Method. Methods: We used Orange Data Mining to perform K-means clustering, and then used similarity-based methods to determine the closeness of characteristics among attractions. The system analyzes based on the fields of cultural, geographical, facility, and landscape features, resulting in four distinct clusters. The clusters were defined as three tourist attractions in cluster C1, eleven in C2, four in C3, and fourteen in C4. We also developed a system interface that allows travelers to input preferences, view personalized recommendations, and access detailed information. The system's novelty lies in its specific application of K-Means Clustering to leverage these local attributes for granular categorization for effective promotion of North Toraja's diversity. Conclusion: Our approach effectively groups attractions with similar characteristics, enhancing exploration based on user interests. The high altitude and similar geographical features of North Toraja result in attractions that share natural characteristics, making this system an advancement in technology-driven tourism solutions. 
Co-Authors Adewidar Marano Pata'dungan Adha, Muhammad Sofwan Alexander Te’dangan Bimo Sunarfri Hantono Conny Conny Damayanti, Irene Devi Dian Yulianti Paulang Dwi Prasetyawati Thana Febriyani Nur Riyanti Ferayanti Boas Gallaran Garonga, Melki Gidion Aryo Nugraha Pongdatu Ishak Pawarangan Judith Ratu Tandi Arrang Juprianus Rusman Linerda Tulaktondok Marchelin, Marchelin Martina Pineng Muhammad, Merson Padang, Semuel Yacobus Pamaru’, Zamanna parea russan rangan Patandean, Lindsay Sapan Patandung, Suryaningsih Pongdatu, Gideon A.N. Pongdatu, Gideon Aryo Nugraha Rali Sarira Bone Rumpa, Lantana Dioren Sari, Irma Permata Selo Sulistyo, Selo Sepsriyanti Kannapadang Siappa, Marchelino Dwi Putra Silambi, Oktovianus Srivan Palelleng Suharpania, Exzelen Tri Upa, Samrius Wanti Willy Yavet Tandirerung Wilson Jefriyanto Yosep Mari' Yudiantika, Aditya Rizki Yusuf L. Limbongan