MODEL GEOGRAPHICALLY WEIGHTED POISSON REGRESSION MENGGUNAKAN PEMBOBOT ADAPTIVE GAUSSIAN KERNEL PADA KASUS TUBERKULOSIS DI INDONESIA

AKTI, ASTRID MUTIARA, B2A220027 (2022) MODEL GEOGRAPHICALLY WEIGHTED POISSON REGRESSION MENGGUNAKAN PEMBOBOT ADAPTIVE GAUSSIAN KERNEL PADA KASUS TUBERKULOSIS DI INDONESIA. Sarjana / Sarjana Terapan (S1/D4) thesis, Universitas Muhammadiyah Semarang.

[img]
Preview
Text
Cover.pdf

Download (504kB) | Preview
[img]
Preview
Text
ABSTRAK.pdf

Download (454kB) | Preview
[img]
Preview
Text
BAB I.pdf

Download (528kB) | Preview
[img]
Preview
Text
BAB II.pdf

Download (796kB) | Preview
[img] Text
BAB III.pdf
Restricted to Repository staff only

Download (558kB) | Request a copy
[img] Text
BAB IV.pdf
Restricted to Repository staff only

Download (813kB) | Request a copy
[img]
Preview
Text
BAB V.pdf

Download (487kB) | Preview
[img]
Preview
Text
DAFTAR PUSTAKA.pdf

Download (507kB) | Preview
[img] Text
Lampiran.pdf
Restricted to Repository staff only

Download (1MB) | Request a copy
Official URL: http://repository.unimus.ac.id

Abstract

ABSTRAK Akti, Astrid Mutiara, 2021, Model Geographically Weighted Poisson Regression Menggunakan Pembobot Adaptive Gaussian Kernel Pada Kasus Tuberkulosis di Indonesia, Skripsi, Program Studi Statistika, Universitas Muhammadiyah Semarang, Pembimbing I: Bapak Dr. Rochdi Wasono, M.Si. Pembimbing II: Ibu Prizka Rismawati Arum, S.Si, M.Stat. Indonesia merupakan negara dengan beban tuberkulosis (TB) tertinggi ketiga di dunia setelah India dan China. Kasus TB yang jarang terjadi sering di asumsikan berdistribusi poisson dan sering ditemukan berupa data spasial, karena itu metode yang sesuai digunakan adalah Geographically Weighted Poisson Regression. Tujuan penelitian ini memperoleh gambaran umum data penyakit tuberkulosis di Indonesia, kemudian diperoleh model dan faktor-faktor yang mempengaruhinya. Data penelitian ini data sekunder, dimana peubah respon yaitu jumlah kasus tuberkulosis, sedangkan peubah prediktor adalah kepadatan penduduk, persentase rumah layak huni, persentase tempat pengelolaan pangan, persentase gerakan hidup sehat, dan penduduk miskin. Hasil penelitian didapat gambaran bahwa penyebaran kasus tuberkulosis di Indonesia tahun 2020 masih ada dan yang tertinggi berada di provinsi Jawa Barat. Berdasarkan tabel diskriptifnya, nilai varians tertinggi untuk faktor yang mempengaruhi kasus TB adalah variabel kepadatan penduduk sebesar 364,578% dapat dikatakan bahwa data kepadatan penduduk sangat fluktuatif. Sedangkan yang terendahnya ada pada variabel persentase rumah layak huni sebesar 21,7675%. Kemudian didapat faktor-faktor yang mempengaruhi secara signifikan terhadap penyakit tuberkulosis di Indonesia yaitu kepadapatan penduduk dan penduduk miskin, dimana jumlah kasus TB akan bertambah sebesar 1,81362 jika jumlah kepadatan penduduk bertambah 1%. Pengujian untuk masing-masing provinsi di Indonesia, di dapatkan variabel signifikan yang sama. Kata Kunci: Geographically Weighted Poisson Regression (GWPR), Tuberkulosis ABSTRACT Akti, Astrid Mutiara, 2021, Geographically Weighted Poisson Regression Model Using Adaptive Gaussian Kernel Weighting in Tuberculosis Cases in Indonesia, Thesis, Statistics Study Program, University of Muhammadiyah Semarang, Supervisor I: Dr. Rochdi Wasono, M.Sc. Advisor II: Mrs. Prizka Rismawati Arum, S.Si, M.Stat. Indonesia is a country with the third-highest burden of tuberculosis (TB) in the world after India and China. TB cases that rarely occur are often assumed to have a Poisson distribution and are often found in the form of spatial data, therefore the appropriate method used is Geographically Weighted Poisson Regression. The purpose of this study is to obtain an overview of the data on tuberculosis in Indonesia, then obtain the model and the factors that influence it. The data of this research is secondary data, where the response variable is the number of tuberculosis cases, while the predictor variables are population density, percentage of livable houses, percentage of food management places, percentage of healthy living movements, and poor people. The results showed that the spread of tuberculosis cases in Indonesia in 2020 still existed and the highest was in the province of West Java. Based on the descriptive table, the highest variance value for the factors that influence TB cases is the population density variable of 364.578%. It can be said that the population density data is very volatile. While the lowest is in the variable percentage of livable houses of 21.7675%. Then the factors that significantly affect tuberculosis in Indonesia are population density and the poor, where the number of TB cases will increase by 1.81362 if the total population density increases by 1%. Tests for each province in Indonesia obtained the same significant variables. Keywords: Geographically Weighted Poisson Regression (GWPR), Tuberculosis

Item Type: Thesis (Sarjana / Sarjana Terapan (S1/D4) )
Contributors:
ContributionCobtributorsNIDN/NIDKEmail
UNSPECIFIEDIndah, Manfaati NurUNSPECIFIEDperpustakaan@unimus.ac.id
UNSPECIFIEDRochdi, WasonoUNSPECIFIEDperpustakaan@unimus.ac.id
Call Number: 002/Statistika/VII/2022
Subjects: L Education > Statistics
Divisions: Faculty of Science and Mathematics > S1 Statistics
Depositing User: perpus unimus
URI: http://repository.unimus.ac.id/id/eprint/5744

Actions (login required)

View Item View Item