PEMODELAN KRIMINALITAS DI SUMATERA BARAT DENGAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) PEMBOBOT ADAPTIVE GAUSSIAN KERNEL DAN ADAPTIVE BISQUARE KERNEL

DITYA, AFRIYENIDA (2023) PEMODELAN KRIMINALITAS DI SUMATERA BARAT DENGAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) PEMBOBOT ADAPTIVE GAUSSIAN KERNEL DAN ADAPTIVE BISQUARE KERNEL. Sarjana / Sarjana Terapan (S1/D4) thesis, Universitas Muhammadiyah Semarang.

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Abstract

ABSTRAK Afriyenida, Ditya (2022). Pemodelan Geographically Weighted Regression dengan Pembobot Adaptive Gaussian Kernel dan Adaptive Bisquare Kernel pada kasus Kriminalitas di Provinsi Sumatera Barat tahun 2021. Skripsi, Program Studi Statistika, Universitas Muhammadiyah Semarang. Pembimbing: I. Prizka Rismawati Arum, M.Stat., II. Indah Manfaati Nur, M.Si. Kriminalitas di Provinsi Sumatera Barat menempati posisi keempat tertinggi di Pulau Sumatera. Kota Padang adalah salah satu kota dengan tingkat kriminalitas tertinggi di Indonesia, disusul oleh Kota Bekasi, Kota Tanggerang, dan Kota Pekanbaru. Upaya yang dapat dilakukan untuk mengatasi masalah tersebut adalah mengidentifikasi karakteristik kriminalitas dari masing-masing kabupaten/kota di Provinsi Sumatera Barat. Metode analisis yang digunakan yaitu Geographically Weighted Regression (GWR) pembobot Adaptive Gaussian Kernel dan Adaptive Bisquare Kernel. Data yang digunakan adalah data sekunder tentang angka kriminalitas, kepadatan penduduk, tingkat pengangguran terbuka, angka partisipasi sekolah usia 16-18 tahun, dan pengeluaran per kapita di 19 kabupaten/kota di Provinsi Sumatera Barat tahun 2021 yang diambil dari Provinsi Sumatera Barat Dalam Angka 2022 dan Badan Pusat Statistik Provinsi Sumatera Barat. Hasil penelitian menunjukan bahwa model GWR dengan fungsi pembobot adaptive bisquare kernel lebih baik dalam memodelkan kriminalitas di Provinsi Sumatera Barat tahun 2021 karena memiliki nilai AIC yang terkecil yakni 225,648 dan nilai R2 yang terbesar yakni 0,9395. Kata Kunci : Adaptive Bisquare Kernel, Adaptive Gaussian Kernel, GWR, Kriminalitas, Spasial ABSTRACT Afriyenida, Ditya (2022). Geographically Weighted Regression Modeling with Adaptive Gaussian Kernel and Adaptive Bisquare Kernel Weighting in Crime Cases in West Sumatra Province in 2021. Thesis of Statistics Study Program, University of Muhammadiyah Semarang. Supervisor: I. Prizka Rismawati Arum, M.Stat., II. Indah Manfaati Nur, M.Si. Crime in West Sumatra Province occupies the fourth highest position on the island of Sumatra. Padang City is one of the cities with the highest crime rate in Indonesia, followed by Bekasi City, Tangerang City, and Pekanbaru City. Efforts that can be made to overcome this problem are to identify the criminality characteristics of each regency/city in West Sumatra Province. The analytical method used is Geographically Weighted Regression (GWR) with Adaptive Gaussian Kernel and Adaptive Bisquare Kernel weights. The data used is secondary data on crime rate, population density, open unemployment rate, school enrollment rate of 16-18 years, and per capita spending in 19 districts/cities in West Sumatra Province in 2021 taken from West Sumatra Province in Figures 2022 and the Central Bureau of Statistics for West Sumatra Province. The results show that the GWR model with the adaptive bisquare kernel weighting function is better at modeling crime in West Sumatra Province in 2021 because it has the smallest AIC value of 225.648 and the largest R2 value of 0.9395 Keywords : Adaptive Bisquare Kernel, Adaptive Gaussian Kernel, Criminality, GWR, Spatial

Item Type: Thesis (Sarjana / Sarjana Terapan (S1/D4) )
Call Number: 003/Statistika/VII/2023
Subjects: L Education > Statistics
Divisions: Faculty of Agricultural Science and Technology > S1 Statistics
Depositing User: perpus unimus
Date Deposited: 14 Jul 2023 08:28
Last Modified: 14 Jul 2023 08:28
URI: http://repository.unimus.ac.id/id/eprint/7119

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