eprintid: 59016
rev_number: 10
eprint_status: archive
userid: 12460
dir: disk0/00/05/90/16
datestamp: 2023-05-31 07:07:24
lastmod: 2023-05-31 07:07:24
status_changed: 2023-05-31 07:07:24
type: thesis
metadata_visibility: show
contact_email: muh.khabib@uin-suka.ac.id
creators_name: Muhammad Ulil Fahmi, NIM.: 19106010045
title: PERBANDINGAN ALGORITMA K-MEANS DENGAN K-MEDOIDS UNTUK PENGELOMPOKKAN TINGKAT KRIMINALITAS DI INDONESIA TAHUN 2020
ispublished: pub
subjects: Matematika
divisions: jur_mat
full_text_status: restricted
keywords: Analisis Cluster, K-Means, K-Medoids, Kriminalitas, Dan Davies Bouldin Index
note: Pembimbing: Epha Diana Supandi, S.Si., M.Sc.
abstract: Cluster analysis is a technique for summarizing data, namely by grouping objects according to the characteristics of each object. The K-Means is a distance-based clustering method which divides data into a number of clusters. K-Medoids method is a clustering method where this method overcomes the weaknesses of K-Means. The second method is used to classify crime data in Indonesia in 2020. In this study, the Davies Bouldin Index was used to determine the best method for data on crime in Indonesia in 2020. The Davies Bouldin Index (DBI) can be interpreted as the smaller the DBI value, the better the cluster obtained. The results of this study indicate that three clusters are formed where the K-Means no outlier method produces a DBI value of 0,9916 which is smaller than the DBI value for K-Medoids no outlier of 1,8733. So in this case, the K-Means no outlier method is a better method than the K-Medoids no outlier method.
date: 2023-03-28
date_type: published
pages: 134
institution: UIN SUNAN KALIJAGA YOGYAKARTA
department: FAKULTAS SAINS DAN TEKNOLOGI
thesis_type: skripsi
thesis_name: other
citation:   Muhammad Ulil Fahmi, NIM.: 19106010045  (2023) PERBANDINGAN ALGORITMA K-MEANS DENGAN K-MEDOIDS UNTUK PENGELOMPOKKAN TINGKAT KRIMINALITAS DI INDONESIA TAHUN 2020.  Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.   
document_url: https://digilib.uin-suka.ac.id/id/eprint/59016/1/19106010045_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf
document_url: https://digilib.uin-suka.ac.id/id/eprint/59016/2/19106010045_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf