Pemodelan Komponen Yang Mempengaruhi Indeks Pembangunan Manusia Di Provinsi Kalimantan Barat Menggunakan Principal Component Regression

Yaumy, Ilayna (2021) Pemodelan Komponen Yang Mempengaruhi Indeks Pembangunan Manusia Di Provinsi Kalimantan Barat Menggunakan Principal Component Regression. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

IPM Indonesia telah berada pada kategori tinggi, namun terdapat perbedaan rata-rata angka IPM antara wilayah barat Indonesia dengan wilayah tengah dan timur Indonesia. Provinsi Kalimantan Barat yang berlokasi di Indonesia bagian barat, berada pada posisi ke-5 terendah pada peringkat IPM provinsi di Indonesia. Pada data IPM di Kalimantan Barat beserta indikator-indikator yang diduga mempengaruhinya terdapat asumsi yang tidak terpenuhi, yaitu adanya multikolinearitas, sehingga digunakan metode Principal Component Regression untuk memodelkan komponen-komponen yang mempengaruhi IPM di Kalimantan Barat. Hasil analisis menggunakan Principal Component Analysis menunjukkan bahwa terdapat 3 komponen yang memiliki proporsi varians lebih dari 80%. Tiga komponen utama terpilih dijadikan variabel prediktor pada Principal Component Regression. Hasil analisis menggunakan metode Principal Component Regression menunjukkan bahwa komponen yang mempengaruhi indeks pembangunan manusia di Kalimantan Barat pada tahun 2019 adalah komponen utama pertama atau komponen ekonomi dan sanitasi, yaitu komponen yang di dalamnya terdapat kontribusi kuat oleh indikator-indikator yang berkaitan dengan dimensi ekonomi (kepadatan penduduk, tingkat pengangguran terbuka, rata-rata upah pekerja, PDRB perkapita) dan akses terhadap sanitasi layak. Nilai kebaikan model yang dihasilkan adalah sebesar 84%.
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Indonesian Human Development Index has been in the high category. However, there is difference of Human Development Index’s average between western region of Indonesia with the central region of Indonesia and the eastern region of Indonesia. West Kalimantan province which is located in western region of Indonesia is in fifth lowest Human Development Index in Indonesian’s province ranking of HDI. On West Kalimantan’s HDI data and the expected indicators of it, there is an assumption which is not eligible. The assumption is multicollinearity. Aims to solve this case, Principal Component Regression method used for modelling components affecting Human Development Index in West Kalimantan province. The analysis result using Principal Component Analysis show that there are three components which have variance proportion more than 80 percent. Then, the three principal component was used to be independent variabel on principal component regression. The analysis results of principal component regression show that components which affecting West Kalimantan’s Human Development Index in 2019 are the first principal component or economic and sanitation component, specifically component which has a strong contribution by standard of living dimension (population density, unemployment rate, the average of net wage employee per month, gross domestic regional bruto) and the percentage of household population to proper sanitation. The R-Square of the model is 84%.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Indeks Pembangunan Manusia, Kalimantan Barat, Multikolinearitas, Principal Component, Human Development Index, West Kalimantan, Multicollinearity
Subjects: Q Science > QA Mathematics > QA278.5 Principal components analysis. Factor analysis. Correspondence analysis (Statistics)
Divisions: Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis
Depositing User: Ilayna Yaumy
Date Deposited: 02 Sep 2021 02:44
Last Modified: 02 Sep 2021 02:44
URI: http://repository.its.ac.id/id/eprint/91288

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