Jurnal Litbang Sukowati, Vol. 4, No. 2, Mei 2021, Hal 79-85 p-ISSN: 2580-541X, e-ISSN: 2614-3356 Tersedia online di http://journal.sragenkab.go.id, Permalink/DOI: 10.32630/sukowati.v4i2.204 79 MODELING OF THE NUMBER OF TUBERCULOSIS CASES IN INDONESIA Aida Meimela Statistics of North Sumatera Province aida.mey@bps.go.id Diterima: Juli 2020; Disetujui: Desember 2020 Abstract. One of the health issues listed in the Sustainable Development Goals (SDGs) is to end the tuberculosis epidemic in 2030. Indonesia is the country with the third-highest number of tuberculosis cases in the world after India and China in 2018. Aims of this study to model the number of tuberculosis cases in each province in Indonesia, depending on the characteristics of each region. Geographically Weighted Lasso (GWL) is a method used to overcome the local multicollinearity that appears in the Geographically Weighted Regression (GWR) model. By using this method, each region will have a different regression model according to its respective characteristics. There is local multicollinearity (VIF> 10) in each explanatory variable used. Banten, West Java, South Kalimantan, East Kalimantan, East Nusa Tenggara and Papua Province are provinces where all research variables affect the number of tuberculosis cases. The variable that has the most significant effect on the number of tuberculosis cases in each region in Indonesia is the number of health centers. Therefore, to end the number of tuberculosis cases, the government should increase the number of health centers and improve the health service. Keywords: dependency spatial, lasso, multicollinearity, spatial heterogeneity, tuberculosis. Abstraksi. Salah satu isu kesehatan yang tercantum dalam Sustainable Development Goals (SDG’s) adalah mengakhiri epidemi tuberkulosis (TBC) di tahun 2030. Indonesia merupakan negara dengan jumlah kasus TBC tertinggi ketiga di dunia setelah India dan China pada tahun 2018. Tujuan penelitian ini adalah melakukan pemodelan jumlah kasus tuberkulosis di Indonesia sesuai dengan karakteristik wilayah masing-masing. Geographically Weighted Lasso (GWL) merupakan metode yang digunakan untuk mengatasi multikonieritas lokal yang muncul pada model Geographically Weighted Regression (GWR). Adanya multikolineritas lokal (VIF >10) pada setiap variabel penjelas yang digunakan. Banten, Jawa Barat, Kalimantan Selatan, Kalimantan Timur, Nusa Tenggara Timur dan Papua adalah provinsi dimana seluruh variabel penelitian berpengaruh terhadap jumlah kasus tuberkulosis. Variabel yang paling banyak berpengaruh signifikan terhadap jumlah kasus tuberculosis di setiap wilayah di Indonesia adalah jumlah puskesmas. Oleh karena itu, untuk mengakhiri jumlah kasus tuberkulosis pemerintah sebaiknya menambah jumlah puskesmas dan meningkatkan pelayanan kesehatan. Kata Kunci: ketergantungan spasial, keragaman spasial, lasso, multikolinieritas, tuberkulosis. BACKGROUND One of the health issues listed in the Sustainable Development Goals (SDGs) is to end the tuberculosis epidemic in 2030 (Indonesia, 2018). This is because tuberculosis is one of the second-highest causes of death after HIV/ AIDS (Fogel, 2015). World Health Organization (WHO) publication in tuberculosis states that Indonesia is the country with the third- highest number of tuberculosis cases in the world after India and China in 2018 (WHO, 2019).