Comparison of Single Linkage, Complete Linkage, and Average Linkage Methods on Community Welfare Analysis in Cities and Regencies in East Java
DOI:
https://doi.org/10.20956/j.v18i1.14228Keywords:
Single linkage, Complete Linkage, Average LinkageAbstract
Community welfare is one of the important points for a region and is also the essence of national development. The welfare of the people in Indonesia is fairly unequal, especially in East Java. To be able to map an area to the welfare of its people in East Java, one way that can be used is to use clustering. The hierarchical clustering method is one of the clustering methods for grouping data. In hierarchical clustering, single linkage, complete linkage, and average linkage methods are suitable methods for grouping data, which will compare the best method to use. The results of the calculation show that the average linkage method with three clusters is the best calculation with a silhouette index value of 0.6054, with the 1st cluster there are 23 regions, namely the city/district with the highest community welfare, the 2nd cluster there are 11 regions, namely cities/districts with moderate social welfare, and in the third cluster there are 4 regions, namely cities/districts with the lowest community welfare.Downloads
References
. Abidin, Zainal., 2017. Pengelompokan Kabupaten/Kota di Jawa Timur Berdasarkan Indikator Kemiskinan dengan Menggunakan Analisis Cluster Hierarki. Skripsi, Fakultas Vokasi, Departemen Statistika Bisnis, Institut Teknologi Sepuluh November, Surabaya.
. Alwi, Wahidah, & Muh. Hasrul., 2018. Analisis Klaster untuk Pengelompokan Kabupaten/Kota di Propinsi Sulawesi Selatan Berdasarkan Indikator Kesejahteraan Masyarakat. Jurnal MSA, Vol. 6, No. 1, pp. 35-42.
. Anggara, Mario., Herry Sujiani, & Helfi Nasution., 2016. Pemilihan Distance Measure Pada K-Means Clustering Untuk Pengelompokan Member di Alvaro Fitness. Jurnal Sistem dan Teknologi Informasi, Vol. 1, No. 1, pp. 1-6.
. Asmiatun, Siti., Nur Wakhidah, & Astrid Novita Putri., 2020. Penerapan Metode K-Medoids Untuk Pengelompokan Kondisi Jalan di Kota Semarang. Jurnal Teknik Informatika dan Sistem Informasi, Vol. 6, No. 2, pp. 171-180.
. Badan Pusat Statistik Jawa Timur., 2019. Indikator Kesejahteraan Rakyat Provinsi Jawa Timur. Badan Pusat Statistik Jawa Timur., Surabaya.
. Dani, Andrea Tri Rian., Sri Wahyuningsih, & Nanda Arista Rizki., 2019. Penerapan Hierarchical Clustering Metode Agglomerative Pada Data Runtun Waktu. Jambura Journal of Mathematics, Vol. 1, No. 2, pp. 64-78.
. Elvina & Musdhalifah., 2019. Peningkatan Kesejahteraan Masyarakat melalui Partisipasi dan Implementasi Kebijakan dengan Efektivitas Pembangunan Program Dana Desa sebagai Variabel Intervening. Jurnal Sosial Humaniora dan Pendidikan, Vol. 3, No. 1, pp. 1-9.
. Goreti, Maria., Yuki Novia N, & Sri Wahyuningsih. 2016. Perbandingan Hasil Analisis Cluster dengan Menggunakan Metode Single Linkage dan Metode C-Means. Jurnal EKSPONENSIAL, Vol. 7, No. 1, pp. 9-16.
. Gustientiedinda, M. Hasmil Adiya, & Yenny Desnelita., 2019. Penerapan Algoritma K-Means untuk Clustering Data Obat-Obatan pada RSUD Pekanbaru. Jurnal Nasional Teknologi dan Sistem Informasi, Vol. 05, No. 1, pp. 17-24.
. Lintong, Rocky., Yohanes A. R. Langi, & Charles E. Mongi. 2019. Penerapan Analisis Faktor Terhadap Kualitas dan Kepuasan Pelayanan Pasien Rumah Sakit TK-II R.W Mongisidi. Jurnal Matematika dan Aplikasi, Vol. 9, No. 1, pp. 24-30.
. Mu’afa, Sulthan Fikri, & Nurissaidah Ulinnuha., 2019. Perbandingan Metode Single Linkage, Complete Linkage, dan Average Linkage dalam Pengelompokan Kecamatan Berdasarkan Variabel Jenis Ternak Kabupaten Sidoarjo. Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi, Vol.4, No. 2.
. Nasifah, Qonitatin, & Novita Eka Chandra., 2017. Analisis Cluster Average Linkage Berdasarkan Faktor-Faktor Kemiskinan di Provinsi Jawa Timur. Math Journal, Vol. 3, No. 2, pp. 31-36.
. Ningsih, Silvia., Sri Wahyuningsih, & Yuki Novia Nasution., 2016. Perbandingan Kinerja Metode Complete Linkage dan Average Linkage dalam Menentukan Analisis Cluster (Studi Kasus : Produksi Palawiya Provinsi Kalimantan Timur 2014/2015). Prosiding Seminar Sains dan Teknologi UNMUL, Vol. 1 thn 2016, 46-50: Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Mulawarman, Samarinda.
. Ramadhani, Lisa., Ika Purnamasari, & Fidia Deny Tisna Amijaya., 2018. Penerapan Metode Complete Linkage dan Metode Hierarchical Clustering Multiscale Bootstrap (Studi Kasus: Kemiskinan di Kalimanta Timur Tahun 2016). Jurnal EKSPONENSIAL, Vol. 9, No. 1, pp. 1-10.
. Rosni., 2017. Analisis Tingkat Kesejahteraan Masyarakat Nelayan di Desa Dahari Selebar Kecamatan Talawi Kabupate Batubara. Jurnal Geografi, Vol. 9, No. 1, pp. 53-66.
. Sapriyanti, & Yan Rianto., 2020. Komparasi Metode Clustering K-Means dan Single Linkage untuk Penetuan Kelompok Agent pada Call Center. Journal of Information System, Applied, Management, Accounting, and Research, Vol. 4, No. 3, pp.1-7.
. Sjafrizal., 2008. Ekonomi Regional Teori dan Aplikasi. Baduose Media., Padang.
. Sukmasari, Dahliana., 2020. Konsep Kesejahteraan Masyarakat dalam Perspektif Al-Qur’an. Journal of Qur’an and Hadis Studies, Vo. 3, No. 1, pp. 1-16.
. Verdian, Edo., 2019. Analisis Faktor yang Merupakan Intensi Perpindahan Merek Transportasi Online di Surabaya. Jurnal AGORA, Vol. 7, No. 1, pp. 1-8
. Widyawati., Wawan Laksito Yuly Saptomo, & Yustina Retno Wahyu Utami., 2020. Penerapan Agglomerative Hierarchical Clustering untuk Segmentasi Pelanggan. Jurnal Ilmiah Sinus, Vol. 18, No. 1, pp. 75-87.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2021 Author and publisher
This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Jurnal Matematika, Statistika dan Komputasi is an Open Access journal, all articles are distributed under the terms of the Creative Commons Attribution License, allowing third parties to copy and redistribute the material in any medium or format, transform, and build upon the material, provided the original work is properly cited and states its license. This license allows authors and readers to use all articles, data sets, graphics and appendices in data mining applications, search engines, web sites, blogs and other platforms by providing appropriate reference.