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All Journal Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Ketahanan Nasional MUST: Journal of Mathematics Education, Science and Technology J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika G-Tech : Jurnal Teknologi Terapan Inferensi Sains dan Matematika
Suliyanto
Departemen Matematika, Fakultas Sains Dan Teknologi, Universitas Airlangga
Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Mathematics Physics Social Sciences

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Journal : Inferensi

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Modeling the Percentage of Tuberculosis Cure in Indonesia Using a Multivariate Adaptive Regression Spline Approach Dita Aris Novianti; Nadia Dwi Marwanda; Toha Saifudin; Suliyanto Suliyanto
Inferensi Vol 7, No 2 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i2.20344

Abstract

Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium Tuberculosis. After India, Indonesia is the country with the second highest number of TB sufferers in the world. TB prevention efforts in Indonesia have been carried out, even since 1995. However, in general, 2006-2022 the TB cure in Indonesia tends to experience a downward trend. Therefore, it is important to know what variables have a significant effect and how the pattern relates to the percentage of TB cures. We urgently need this information to optimize TB handling efforts and achieve Sustainable Development Goals (SDGs) point 3, which focuses on good health and well-being. For that purpose, this study used the Multivariate Adaptive Regression Spline (MARS) approach. MARS is considered more flexible in overcoming cases of predictor variables that do not form a certain pattern to their response variables and can accommodate possible interactions between predictor variables. The best model was obtained at BF=18,MI=2, and MO=0 with minimum GCV value is 37.053 and R^2 is 91.6%, with significant predictor variables are food management sites meet the requirements according to standards, complete treatment, smoking population over 15 years, families with healthy latrines, and districts/municipalities implement healthy living germas policy. The significance of the nine predictors should prioritize enhancing the quality of health services for example ensuring a fair distribution of complete treatment for TB patients.
Co-Authors Alfi Nur Nitasari Alfredi Yoani Ameliatul 'Iffah Ana, Elly Anisa Laila Azhar Christopher Andreas Dhyana Venosia Diah Puspita Ningrum Dita Amelia Dita Aris Novianti Eko Tjahjono Elly Ana Elly Ana Fina Insyiroh Leni Sartika Panjaitan M. Fariz Fadillah Mardianto M. Fariz Fadillah Mardianto Maelcardino Christopher Justin Mahfudhotin Mahfudhotin Mochamad Rasyid Aditya Putra Nadia Dwi Marwanda Netha Aliffia Nur Chamidah Salma Bethari Andjani Sumarto Sediono Sediono Sediono Sediono Sugha Faiz Al Maula Toha Saifudin Toha Saifudin Toha Saifudin Toha Saifudin