Pemodelan Faktor-Faktor yang Berhubungan dengan Kasus Tuberkulosis Anak di Provinsi Jawa Timur, Indonesia Menggunakan Regresi Poisson Tergeneralisasi
DOI:
https://doi.org/10.55606/jrik.v6i2.6670Keywords:
Childhood Tuberculosis, Count Data, East Java, Generalized Poisson Regression, OverdispersionAbstract
Childhood tuberculosis (TB) remains a major public health problem in Indonesia, particularly in East Java Province. This study aimed to identify factors associated with childhood TB cases to support effective disease prevention and control. Since the number of TB cases represents count data that may exhibit overdispersion, Generalized Poisson Regression (GPR) was employed as an appropriate analytical approach. This ecological study used secondary data from 38 districts and municipalities in East Java Province, Indonesia, in 2024, obtained from the East Java Provincial Health Office. Multicollinearity was assessed using the Variance Inflation Factor (VIF). Because overdispersion was detected in the Poisson regression model, the analysis was subsequently performed using Generalized Poisson Regression. The final GPR model included the percentage of the population reporting health complaints, the average number of cigarettes smoked per week, the percentage of households with access to improved sanitation, the percentage of households with access to safe drinking water, the number of healthcare workers, and the number of healthcare facilities as explanatory variables. Model evaluation yielded an Akaike Information Criterion (AIC) value of 457.46 and an Adjusted R² value of 0.9813, indicating that the model explained 98.13% of the variation in childhood TB cases. These findings demonstrate that Generalized Poisson Regression is an appropriate method for modeling overdispersed childhood TB count data and provides useful evidence to strengthen tuberculosis surveillance and support targeted public health interventions for childhood TB control in East Java Province.
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Adiguno, F. (2022). Faktor-faktor yang berhubungan dengan capaian case detection rate (CDR) tuberkulosis di Puskesmas Wira Bangun Kecamatan Sampang Pematang Kabupaten Mesuji (Master's thesis). Politeknik Kesehatan Kementerian Kesehatan Tanjungkarang.
Al Haris, M., & Arum, P. R. (2022). Negative binomial regression and generalized Poisson regression models on the number of traffic accidents in Central Java. BAREKENG: Jurnal Ilmu Matematika dan Terapan, 16(2), 471–482.
Allo, C. B. G., Otok, B. W., & Purhadi. (2019). Estimation parameter of generalized Poisson regression model using generalized method of moments and its application. IOP Conference Series: Materials Science and Engineering, 546, Article 052050.
Alvionita, V. (2022). Faktor-faktor yang mempengaruhi jumlah kasus DBD di Provinsi Riau dengan menggunakan regresi Poisson inverse Gaussian (Master's thesis). Universitas Islam Negeri Sultan Syarif Kasim Riau.
Aminullah, A. A. H., & Purhadi. (2020). Pemodelan untuk jumlah kasus kematian bayi dan ibu di Jawa Timur menggunakan bivariate generalized Poisson regression. Jurnal Sains dan Seni ITS, 8(2), D72–D78.
An, Y., Teo, A. K. J., Huot, C. Y., Tieng, S., Khun, K. E., Pheng, S. H., Leng, C., Deng, S., Song, N., Nonaka, D., et al. (2023). Barriers to childhood tuberculosis case detection and management in Cambodia: The perspectives of healthcare providers and caregivers. BMC Infectious Diseases, 23(1), Article 80.
Consul, P. C., & Famoye, F. (1992). Generalized Poisson regression model. Communications in Statistics—Theory and Methods, 21(1), 89–109. https://doi.org/10.1080/03610929208830766
Da, K. A., Hargono, A., & Ratgono, A. (2023). Evaluasi pelaksanaan investigasi kontak kasus tuberkulosis di Kabupaten Tulungagung, Provinsi Jawa Timur. Jurnal Ners.
Desiana, C. M., & Melaniani, S. (2022). Pemodelan generalized Poisson regression pada jumlah kasus penyakit difteri di Kota Surabaya tahun 2017. Jurnal Ilmiah Permas: Jurnal Ilmiah STIKES Kendal, 12(3), 547–558.
Dinas Kesehatan Provinsi Jawa Timur. (2024). Profil kesehatan Provinsi Jawa Timur tahun 2024. Dinas Kesehatan Provinsi Jawa Timur.
Faisal, D. R., Noveyani, A. E., Purwatiningsih, Y., Lestyoningrum, S. D., Putro, W. G., Mikrajab, M. A., & Nugraheni, W. P. (2024). Prevalence and associated factors of childhood tuberculosis in Southeast Asian countries: A systematic review. Malaysian Journal of Medical Sciences, 31(6), Article 112.
Famoye, F. (1993). Restricted generalized Poisson regression model. Communications in Statistics—Theory and Methods, 22(5), 1335–1354. https://doi.org/10.1080/03610929308831089
Hilbe, J. M. (2014). Modeling count data. Cambridge University Press.
Ihsan, H., Sanusi, W., & Ulfadwiyanti, R. (2020). Model generalized Poisson regression (GPR) dan penerapannya pada angka pengangguran bagi penduduk usia kerja di Provinsi Sulawesi Selatan. Journal of Mathematics, Computations, and Statistics, 3(2), 109–117.
Irmawati, I., et al. (2025). Gambaran pertumbuhan dan perkembangan balita penderita tuberkulosis paru (TBC) di wilayah Puskesmas Kota Makassar.
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An introduction to statistical learning: With applications in R (2nd ed.). Springer.
Kementerian Kesehatan Republik Indonesia. (2024). Profil kesehatan Indonesia tahun 2024. Kementerian Kesehatan Republik Indonesia.
Kutner, M. H., Nachtsheim, C. J., Neter, J., & Li, W. (2005). Applied linear statistical models (5th ed.). McGraw-Hill Education.
Lembang, F. K., Nara, E. A., Rumlawang, F. Y., & Talakua, M. W. (2019). Pemodelan pengaruh iklim terhadap angka kejadian demam berdarah di Kota Ambon menggunakan metode regresi generalized Poisson. Indonesian Journal of Statistics and Its Applications, 3(3), 341–351.
Maharani, E. A. (2025). Persebaran kasus tuberkulosis berdasarkan kepadatan penduduk di Provinsi Jawa Timur tahun 2021–2023. Jurnal Kesehatan Tambusai.
Mohidem, N. A., Osman, M., Hashim, Z., Muharam, F. M., Mohd Elias, S., & Shaharudin, R. (2021). Association of sociodemographic and environmental factors with spatial distribution of tuberculosis cases in Gombak, Selangor, Malaysia. PLOS ONE, 16(6), e0252146. https://doi.org/10.1371/journal.pone.0252146
Montgomery, D. C., Peck, E. A., & Vining, G. G. (2021). Introduction to linear regression analysis (6th ed.). John Wiley & Sons.
Muhibah, I. (2020). Regresi binomial negatif pada kasus tuberkulosis Provinsi Jawa Timur menggunakan estimator spline truncated (Master's thesis). Universitas Islam Negeri Maulana Malik Ibrahim.
Oktavia, S., Hidayati, F., Lesmana, O., & Butar, M. B. (2026). Hubungan kondisi fisik lingkungan rumah dengan kejadian tuberkulosis paru di Indonesia (Analisis data Survei Kesehatan Indonesia tahun 2023). RIGGS: Journal of Artificial Intelligence and Digital Business, 4(4), 3581–3588.
Puspita, E., Perdana, A. A., & Aryawati, W. W. (2026). Analisis pelaksanaan penemuan kasus tuberkulosis (TB) di Puskesmas Roworejo Pesawaran tahun 2024. Jurnal Ilmiah Kesehatan Media Husada, 15(1), 37–51.
Putri, A. H. (2024). Pemetaan faktor risiko tuberkulosis paru BTA(+) secara spasial di wilayah kerja UPTD Puskesmas Pasir Sakti Kecamatan Pasir Sakti Kabupaten Lampung Timur tahun 2024 (Master's thesis). Politeknik Kesehatan Kementerian Kesehatan Tanjungkarang.
Setyoningrum, R. A., Maharani, R. A., Hapsari, R., & Chafid, A. P. P. (2024). Risk factors of tuberculosis in children with adult household tuberculosis contact. Paediatrica Indonesiana, 64(4), 287–292.
Supriyanti, S., Pohan, T. F., & Siregar, K. N. (2024). Sistem monitoring dan evaluasi serta perkembangan program pencegahan dan pengendalian penyakit tuberkulosis di Dinas Kesehatan Kota Depok. Jurnal Biostatistik, Kependudukan, dan Informatika Kesehatan, 4(2).
Triasih, R., Yani, F. F., Wulandari, D. A., Nababan, B. W. Y., Ardiyamustaqim, M. B., Meyanti, F., Indriyani, S. A. K., Pakasi, T. T., & Olivianto, E. (2025). Treatment-decision algorithm of child TB: Evaluation of WHO algorithm and development of Indonesia algorithm. Tropical Medicine and Infectious Disease, 10(4), Article 106. https://doi.org/10.3390/tropicalmed10040106
Trollfors, B., Sigurdsson, V., & Dahlgren-Aronsson, A. (2021). Prevalence of latent TB and effectiveness of BCG vaccination against latent tuberculosis: An observational study. International Journal of Infectious Diseases, 109, 279–282. https://doi.org/10.1016/j.ijid.2021.06.071
Wahyuningsih, A., Yolanda, O., & Sabatina, S. (2025). Implementasi kebijakan penanggulangan tuberkulosis: Literature review. Jurnal Administrasi Rumah Sakit Indonesia, 4(1), 56–63.
Wibawa, G. N. A., Abapihi, B., et al. (2023). Pemodelan regresi Poisson terhadap faktor-faktor yang mempengaruhi terjadinya hipertensi di Kota Kendari. Jurnal Matematika Komputasi dan Statistika, 3(1), 255–262.
Widyaningsih, Y., & Budiawan, Z. A. (2023). Poisson regression models to analyze factors that influence the number of tuberculosis cases in Java. BAREKENG: Jurnal Ilmu Matematika dan Terapan, 17(3), 1761–1772.
World Health Organization. (2022). WHO operational handbook on tuberculosis: Module 5: Management of tuberculosis in children and adolescents. World Health Organization.
World Health Organization. (2024). Global tuberculosis report 2024. World Health Organization.
Wulandari, D. N., & Salamah, M. (2022). Pemodelan jumlah penderita tuberkulosis di Provinsi Jawa Timur tahun 2018 menggunakan metode generalized Poisson regression. Jurnal Sains dan Seni ITS, 11(1), D36–D42.
Zulfa, H. A., Adhayati, B., Prameswari, Y. N., Amelia, R., Irawati, N. B. U., & Hermawati, L. (2025). ASI sebagai intervensi kesehatan ibu dan anak. Journal of Baja Health Science, 5(2), 235–248.
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