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All Journal EKSAKTA: Journal of Sciences and Data Analysis
Trigarcia Maleachi Randa
Department of Statistics, Faculty of Mathematics and Natural Science, Hasanuddin University, Makassar, Indonesia.
Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Materials Science & Nanotechnology

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Pemodelan Proporsi Kasus Tuberkulosis di Sulawesi Selatan Menggunakan Sparse Least Trimmed Squares Trigarcia Maleachi Randa; Georgina Maria Tinungki; Nurtiti Sunusi
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 3, ISSUE 2, August 2022
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol3.iss2.art6

Abstract

The deadliest infectious disease in Indonesia is tuberculosis (TB), and South Sulawesi is one of the provinces that contributed the most tuberculosis cases in Indonesia in 2018 with 84 cases per 100,000 population. This study aims to identify variables that could explain the proportion of TB cases in South Sulawesi. The data used has many explanatory variables, and there are outliers. Sparse Least Trimmed Squares (LTS) analysis can be used to handle data that has many explanatory variables and outliers. The resulting sparse LTS model successfully selects and shrinks the variables to 14 variables only. In addition, based on the value of R2 and RMSE for the model evaluation, the sparse LTS shows satisfying results rather than classical LASSO. The government can focus on these factors if they want to reduce the proportion of TB cases in South Sulawesi.
Co-Authors Georgina Maria Tinungki NURTITI SUNUSI