EKSAKTA: Journal of Sciences and Data Analysis
VOLUME 3, ISSUE 2, August 2022

Pemodelan Proporsi Kasus Tuberkulosis di Sulawesi Selatan Menggunakan Sparse Least Trimmed Squares

Trigarcia Maleachi Randa (Department of Statistics, Faculty of Mathematics and Natural Science, Hasanuddin University, Makassar, Indonesia.)
Georgina Maria Tinungki (Department of Statistics, Faculty of Mathematics and Natural Science, Hasanuddin University, Makassar, Indonesia.)
Nurtiti Sunusi (Department of Statistics, Faculty of Mathematics and Natural Science, Hasanuddin University, Makassar, Indonesia.)

Article Info

Publish Date
07 Sep 2022

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.

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Journal Info
EKSAKTA: Journal of Sciences and Data Analysis
Website

Abbrev

eksakta

Publisher

Universitas Islam Indonesia

Subject

Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Materials Science & Nanotechnology

Description

Ekstakta is an interdisciplinary journal with the scope of mathematics and natural sciences that is published by Fakultas MIPA Universitas Islam Indonesia. All submitted papers should describe original, innovatory research, and modelling research indicating their basic idea for potential ...