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All Journal International Journal of Evaluation and Research in Education (IJERE) EKSAKTA: Journal of Sciences and Data Analysis TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Informatika Jurnal Karya Pendidikan Matematika International Journal of Advances in Intelligent Informatics AdMathEduSt: Jurnal Ilmiah Mahasiswa Pendidikan Matematika AKSIOMA Jurnal Penelitian Pendidikan IPA (JPPIPA) CARADDE: Jurnal Pengabdian Kepada Masyarakat JKPM (Jurnal Kajian Pendidikan Matematika) Indonesian Journal on Learning and Advanced Education (IJOLAE) JURNAL INOVASI PENDIDIKAN MATEMATIKA (JIPM) JEMSI (Jurnal Ekonomi, Manajemen, dan Akuntansi) Prosiding Seminar Nasional Program Pengabdian Masyarakat JNPM (Jurnal Nasional Pendidikan Matematika)
Suparman
Universitas Ahmad Dahlan
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Education Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Social Sciences

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Journal : EKSAKTA: Journal of Sciences and Data Analysis

 1 
Implementation of Minkowski-Chebyshev Distance in Fuzzy Subtractive Clustering Annisa Eka Haryati; Sugiyarto Surono; Suparman Suparman
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 2, ISSUE 2, August 2021
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol2.iss2.art1

Abstract

Clustering is a method of the grouping which is done by looking at the similarities between data in a data set. Fuzzy clustering is a clustering method that uses fuzzy set membership values as the basis for grouping data. Fuzzy Subtractive Clutering (FSC) is a fuzzy clustering method where the number of clusters to be formed is unknown. The concept of FSC is to determine the highest data density and the data with the most number of neighbors will be selected as the center of the cluster. Thus, the size of the proximity or distance between points is needed to determine the members of each cluster. The distance used in this study is a combination of the Minkowski and Chebyshev distances. The number of clusters formed will be evaluated using the Partition Coefficient (PC) value where the highest PC value indicates the best number of clusters. The results obtained indicate that the best clusters are three clusters with a PC value of 0.7422
Co-Authors Agus Purnama Ahmad Rizal Saqibul Fiqri Ami Ramadayanti Andri Pranolo Anggit Prabowo Annisa Eka Haryati Annisa Sulistyaningsih Apriliani Fitriya Damayanti Arif Darmawan Asroni Asroni Azzahrotul Jannah Bidayatun Nafi’ah Bunga Putri Syafina Cahya Damarjati Caraka Kresna Chairil Hikayat Chong Su Li Dahlia Janan Desi Kusuma Wardani Desi Rubiyanti Desty Emi Markahamah Devi Bima Arditama Diah Pramusinta Dinda Genius Anggun Maretha Diyah Istriani Dwi Lestari Eko Budi Isnanto Ellya Rakhmawati Endang Mulyani Epa Wira Darmawan Eti Rahayuningsih Eva Yuniarti Utami Fathurrahman, Muhammad Fernanda Amalia Putri Fifi Ninawati Habibi Habibi Hafidina Nur Fi Rahman Haristha Rachmawati Hujjatul Muslimah Ika Putri Astriyana Sari Imam Muhajir Setiawan Iryana Setyaningrum Isnaepi Isnaepi Kahar, Muhammad Syahrul Kirana Dwi Priharini Laila Rahmawati Lina Anggraeni Lusiana Pratiwi Marfilinda Atma Sari Subekti Michel Doisy Mohd Saifullah Rusiman Muhammad Ali Muhammad Muliya Al-amien Nita Novianti Nunung Azizah Nur Hasanah Nurlita Widoarti Okta Wibowo Pupus Winandari Putri Wulandari Queen Veronica Frieda Laurencia Rinda Hidayanti Riska Zunanto Rizky Fadillah Rofikoh Khasanah Sagita Dyah Putranti Salamatun Asakdiyah Salsabila, Unik Hanifah Sarwo Eddy Wibowo Seldy Derudinansyah Sindi Kurniawati Siregar, Ummu Habibah Siska Audhina Kusumaningtyas Slamet Riyadi Suci Annisa Sugiyarto Surono Surasmanto Surasmanto Suswandari Syaiful Rochmat Tri Dessy Damayanti Vica Windhi Seputri Wahyu Andriyani Yoga Dwi Kurniawan Yolan Nur Vitasari Yuliani Damayanti Zaini Fauzi Zunan Setiawan