ANALISIS FAKTOR SOSIAL DAN EKONOMI YANG MEMENGARUHI KASUS POSITIF MALARIA PADA 33 PROVINSI DI INDONESIA DENGAN METODE PARTIAL LEAST SQUARES REGRESSION

Natalie, Hanson (2023) ANALISIS FAKTOR SOSIAL DAN EKONOMI YANG MEMENGARUHI KASUS POSITIF MALARIA PADA 33 PROVINSI DI INDONESIA DENGAN METODE PARTIAL LEAST SQUARES REGRESSION. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Malaria adalah penyakit yang disebabkan oleh parasit Plasmodium sp. pada tahun 2017 World Health Organization (WHO) mencatat 219 juta kasus seluruh dunia, dan 435.000 kematian seluruh dunia. Penelitian ini bertujuan untuk mengetahui faktor sosial dan ekonomi apa saja yang mempengaruhi kasus positif Malaria pada 33 Provinsi di Indonesia, dimana variabel independen pada penelitian ini berjumlah total 11 variabel. Data yang diambil peneliti adalah data Kemenkes RI tahun 2004-2020 dan data pendukung dari BPS (Badan Pusat Statistik). Partial Least Squares Regression adalah metode yang digunakan, metode ini meliputi pembuatan komponen pada tiap data berdasarkan variabel yang berpengaruh signifikan, dan Uji Asumsi Klasik. Penelitian dengan teknik ini bertujuan untuk meniadakan multikolinearitas yang terjadi pada data 33 provinsi Indonesia yang digunakan dengan melihat nilai VIF. / Malaria is a disease that is caused by the parasite Plasmodium sp.on 2017 World Health Organization (WHO) recorded 219 million cases worldwide, and 435,000 deaths worldwide. This study aims to determine what social and economic factors affect positive cases of malaria in 33 provinces in Indonesia, where the independent variables in this study amounted to 11 variables. The data taken by the researcher is the Indonesian Ministry of Health data for 2004-2020 and supporting data from the BPS (Badan Pusat Statistik). This study uses the Partial Least Squares Regression data processing method. This method includes making components in each data based on variables that have a significant effect, and Classical Assumption Test. Research with this technique aims to eliminate the multicollinearity that occurs in the data of 33 provinces of Indonesia used by looking at the VIF value.

Item Type: Thesis (Bachelor)
Creators:
CreatorsNIMEmail
Natalie, HansonNIM01112170029hannatalie19@gmail.com
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorFerdinand, Ferry VincenttiusNIDN0323059001ferry.vincenttius@uph.edu
Thesis advisorJosephine, JosephineUNSPECIFIEDyosie.linoto@gmail.com
Uncontrolled Keywords: Malaria; Partial Least Squares Regression; Provinsi; Malaria; Partial Least Squares Regression; Province
Subjects: Q Science > QA Mathematics
Divisions: University Subject > Current > Faculty/School - UPH Karawaci > Faculty of Science and Technology > Mathematics
Current > Faculty/School - UPH Karawaci > Faculty of Science and Technology > Mathematics
Depositing User: Hanson Natalie
Date Deposited: 02 Feb 2023 03:33
Last Modified: 02 Feb 2023 03:33
URI: http://repository.uph.edu/id/eprint/53310

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