Penentuan Lokasi Baru Kantor Otoritas Jasa Keuangan (OJK) di Provinsi Sumatera Utara Menggunakan Analisis Faktor dan Analisis Klaster Fuzzy C-Means

Lasahido, Mutiara Avista Candra Dewi (2018) Penentuan Lokasi Baru Kantor Otoritas Jasa Keuangan (OJK) di Provinsi Sumatera Utara Menggunakan Analisis Faktor dan Analisis Klaster Fuzzy C-Means. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

[thumbnail of 1315105050-Undergraduate_Thesis.pdf]
Preview
Text
1315105050-Undergraduate_Thesis.pdf - Accepted Version

Download (6MB) | Preview

Abstract

Analisis Klaster Fuzzy C-Means (FCM) merupakan suatu teknik pengelompokan yang mempertimbangkan sifat keanggotaan fuzzy sebagai dasar pembobotan. Pada penelitian ini, Analisis Klaster digunakan untuk menentukan lokasi baru kantor Otoritas Jasa Keuangan (OJK) di Provinsi Sumatera Utara. Lokasi baru kantor OJK direkomendasikan melalui Analisis Klaster K-Means dan FCM yang mengelompokkan seluruh Kabupaten/Kota di Sumatera Utara berdasarkan seluruh variabel yaitu Produk Domestik Regional Bruto (PDRB), Pengeluaran Pemerintah, Jumlah Penduduk, Indeks Pembangunan Manusia (IPM), dan Piutang Perusahaan Pembiayaan serta berdasarkan variabel terpilih hasil Analisis Faktor. Analisis faktor membentuk dua faktor dimana faktor pertama diwakili oleh PDRB, dan faktor kedua adalah IPM. Analisis Klaster K-Means dan FCM membentuk empat klaster optimum menggunakan dua variabel terpilih hasil Analisis Faktor. Kabupaten/Kota yang disarankan menjadi lokasi kantor baru adalah Kabupaten Deli Serdang, Kabupaten Simalungun, dan Kota Pematang Siantar.
============================================================================================================
Fuzzy C-Means Cluster Analysis (FCM) is a grouping tech-nique that considers the nature of fuzzy membership in a group as a weighted basis. The new location of Financial Services Authority (OJK) in North Sumatra Province is rec-ommended through K-Means and Fuzzy C-Means Cluster Analysis which classifies all districts / cities in North Sumatra based on all variables, namely Gross Regional Domestic Product (GRDP), Government Expenditure, Population, Hu-man Development Index (HDI), and Receivable Financing Company as well as grouping based on selected variables of Factor Analysis results. Factor analysis forms two factors where the first factor is represented by GRDP, and the second factor is HDI. K-Means and FCM Cluster Analysis forms four optimum clusters using two variables chosen based on the result of Factor Analysis. The recommended district / city to be the location of the new office is Deli Serdang Regency, then Simalungun Regency and Pematang Siantar City as al-ternatives.

Item Type: Thesis (Undergraduate)
Additional Information: RSSt 519.535 Las p-1 3100018074474
Uncontrolled Keywords: Analisis Faktor; Analisis Klaster K-Means dan Fuzzy C-Means; IPM; Penduduk; PDRB; Pengeluaran Pemerintah; Piutang Perusahaan Pembiayaan; Factor Analysis; GDRP; Government Expenditure; HDI; K-Means and Fuzzy C-Means Cluster Analysis; Population; Receivable Financing Company
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HD Industries. Land use. Labor > HD30.23 Decision making. Business requirements analysis.
Q Science > QA Mathematics > QA278.55 Cluster analysis
Q Science > QA Mathematics > QA248_Fuzzy Sets
Divisions: Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User: Mutiara Avista Candra Dewi Lasahido
Date Deposited: 26 Mar 2018 04:26
Last Modified: 24 Sep 2020 08:55
URI: http://repository.its.ac.id/id/eprint/50707

Actions (login required)

View Item View Item