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Novia Nur
Lugi Prayoto
Bagas Tanjung Mardiyanto
Heliyanti Susana


The most popular tourist attractions in Cirebon Regency are the graves of the ancestors, which are included in the type of religious tourism. Basically, there are quite a lot of tourist attractions in Cirebon Regency, but there are still tourist attractions that have not been organized and have not been developed optimally. Even though there are many places in Cirebon Regency that have the potential to be developed into a tourist attraction. One of the tourist attractions that has been developed and has an official manager is the Banyu Panas Gempol-Cirebon Tourism Object. The research objective is to implement machine learning using the K-Means algorithm to classify and map villages and sub-districts in Cirebon Regency which have tourism potential to be developed. The stages of implementing mechine learning using the K-means clustering algorithm for mapping village potential and keluranah in Cirebon Regency are carried out in five stages. The first process is data collection. both data processing. The third group of data uses the K-means algorithm by determining the center of the initial cluster. The fourth process is an implementation of the application of mechine learning using rapidminer with the K-means algorithm. The fifth analyzes the cluster results generated by the system. From the results of the research based on the Davies Bouldin test on the K-Means algorithm, the closest value is Davies Bouldin: 0.061, so the smallest value is the 3rd cluster containing members of the cluster of 70 villages that have tourism potential.


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How to Cite
Nur, N., Lugi Prayoto, Bagas Tanjung Mardiyanto, & Heliyanti Susana. (2021). ANALISIS PEMETAAN WILAYAH MENGGUNAKAN METODE ALGORITMA K-MEANS. JURNAL ILMIAH BETRIK : Besemah Teknologi Informasi Dan Komputer, 12(3), 237-241. Retrieved from


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