Comparison of Euclidean with Manhattan in K-Means Clustering for Grouping Palm Oil Production in the Province North Sumatra

S Solikhun(1*), Lise Pujiastuti(2),

(1) AMIK Tunas Bangsa
(2) STMIK Antar Bangsa
(*) Corresponding Author

Abstract


North Sumatra is the largest palm oil-producing province in Indonesia. The region of North Sumatra has an extensive area of oil palm plantations compared to other provinces in Indonesia. To produce a good clustering of oil palm production using the K-Means Clustering method, it is necessary to compare several calculation methods to find the shortest distance in K-Means Clustering. This study focuses on comparing Euclidean Distance with Manhattan Distance on K-Means Clustering. To determine the best method of calculating the shortest distance, the researchers looked for the smallest Davies Bouldin Index (DBI). The smallest DBI value is at k=2 0.145. The result of grouping oil palm production in Sumatra province with k=2 is the high group being Asahan, Langkat and North Labuhanbatu regencies, while 30 other regencies/cities are in the low group

Full Text:

Pdf

References


H. Sulastri and A. I. Gufroni, “Penerapan Data Mining Dalam Pengelompokan Penderita Thalassaemia,” J. Nas. Teknol. dan Sist. Inf., vol. 3, no. 2, pp. 299–305, 2017.

D. Marlina, N. Lina, A. Fernando, and A. Ramadhan, “Implementasi Algoritma K-Medoids dan K-Means untuk Pengelompokkan Wilayah Sebaran Cacat pada Anak,” J. CoreIT J. Has. Penelit. Ilmu Komput. dan Teknol. Inf., vol. 4, no. 2, p. 64, 2018.

F. Ramdhani and A. Hoyyi, “Pengelompokan Provinsi Di Indonesia Berdasarkan Karakteristik Kesejahteraan Rakyat Menggunakan Metode K-Means Cluster,” J. Gaussian, vol. 4, no. 4, pp. 875–884, 2015.

W. Gie and D. Jollyta, “Perbandingan Euclidean dan Manhattan Untuk Optimasi Cluster Menggunakan Davies Bouldin Index : Status Covid-19 Wilayah Riau,” Pros. Semin. Nas. Ris. Dan Inf. Sci. 2020, vol. 2, no. April, pp. 187–191, 2020.

C. A. Pamungkas, “Aplikasi Penghitung Jarak Koordinat Berdasarkan

Latitude Dan Longitude Dengan Metode Euclidean Distance Dan Metode Haversine,” J. Inf. Politek. Indonusa Surakarta, vol. 5, no. 2, pp. 8–13, 2019.

M. Nishom, “Perbandingan Akurasi Euclidean Distance, Minkowski Distance, dan Manhattan Distance pada Algoritma K-Means Clustering berbasis Chi-Square,” J. Inform. J. Pengemb. IT, vol. 4, no. 1, pp. 20–24, 2019.

I. F. Ashari, R. Banjarnahor, and D. R. Farida, “Application of Data Mining with the K-Means Clustering Method and Davies Bouldin Index for Grouping IMDB Movies,” vol. 6, no. 1, pp. 7–15, 2022.

Yuliyanti, S. Al-Zulfa Nas, I. Jauhari Muhas, and E. Firmansyah, “Perbandingan metode pendekatan manhattan distance dengan euclidian distance pada implementasi pengenalan aksara jawa dengan menggunakan algoritma k-nearest neighbor.”




DOI: https://doi.org/10.30645/ijistech.v5i6.197

Refbacks

  • There are currently no refbacks.







Jumlah Kunjungan:

View My Stats

Published Papers Indexed/Abstracted By: