Melola Discovery

← Melola Discovery

Jurnal SINTA 1

Unveiling Tuberculosis Dynamics in Indonesia for Effective Control and Prevention: A Panel Regression and Clustering Approach

Journal of Public Health and Pharmacy · Vol. 6 No. 2 (2026) · hlm. 296–309

DOI
10.56338/jphp.v6i2.7265
ISSN
2775-4952
Terbit
2026-07-01
Penerbit
Pusat Pengembangan Teknologi Informasi dan Jurnal Universitas Muhammadiyah Palu
Bahasa
eng

Abstrak

Introduction: Tuberculosis (TB) remains a critical global health challenge, with Indonesia ranking second in global TB burden. This study examines factors influencing TB incidence across Indonesian provinces and applies clustering to guide targeted interventions aligned with TB eradication goals by 2030. Specifically, these findings inform Indonesia’s End TB 2030 roadmap by identifying provincial heterogeneity that necessitates differentiated resource allocation and strengthened health governance frameworks. Methods: This ecological time-series study design analyzed data from 34 Indonesian provinces (2020–2022), including TB cases, healthcare services, HIV cases, smoking prevalence, food management places, and public facilities. Descriptive statistics summarized variable distribution, while panel data regression identified key factors using multicollinearity checks, model selection, and assumption testing. Fuzzy Possibilistic C-Means (FPCM) clustering grouped provinces based on similarity characteristics. Results: TB cases rose from 10,351 in 2020 to 21,303 in 2022. This study underscores the multifaceted factors influencing TB incidence in Indonesia. Significant factors included healthcare services (?1 = -8.37), HIV cases (?2 = 13.76), smoking prevalence (?3 = 905.32), food management places (?4 = 1.62), and public facilities (?5 = 1.11). This study proves that TB is not only influenced by health factors but also by non-health factors. Fuzzy clustering using the FPCM identified three clusters based on their possibilistic membership degrees: Cluster 3, with high HIV prevalence and public facilities, requiring urgent action; Cluster 2, needing improved healthcare and smoking reduction; and Cluster 1, with moderate challenges. Conclusions: Health and environmental factors significantly influence TB incidence. Addressing cluster-specific needs, such as enhancing healthcare, reducing HIV and smoking prevalence, and improving public health standards, is essential for TB control. Future studies should expand variables and periods to deepen insights.

Kata kunci

Jaringan kolaborasi para penulis

12 penulis · 45 tautan kepenulisan bersama · 13 lintas organisasi

Arahkan kursor atau ketuk sebuah nama untuk menyorot rekan penulisnya. Klik dua kali untuk membuka halaman penulis.

  • Universitas Syiah Kuala
  • Prince of Songkla University
  • University of Hong Kong
  • Afiliasi tidak diketahui
  • Organisasi berbeda
  • Organisasi sama
  • Afiliasi tidak diketahui
  • Garis lebih tebal = lebih banyak artikel bersama · lingkaran lebih besar = lebih banyak artikel
Tampilkan sebagai tabel
Rekan penulisOrganisasiArtikel bersama
Rahmatil Adha PhonnaUniversitas Syiah Kuala2
Saiful KamalAfiliasi tidak diketahui2
Nudzran YusyaUniversitas Syiah Kuala2

Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.

Sumber metadata: OAI-PMH (metadata jurnal) https://jurnal.unismuhpalu.ac.id/index.php/jphp/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en-US">Unveiling Tuberculosis Dynamics in Indonesia for Effective Control and Prevention: A Panel Regression and Clustering Approach</dc:title>
	<dc:creator>Sasmita, Novi Reandy</dc:creator>
	<dc:creator>Syifa, Mutiara</dc:creator>
	<dc:creator>Khairul, Mhd </dc:creator>
	<dc:creator>Rahayu, Latifa </dc:creator>
	<dc:creator>Kesuma, Zurnila Marli </dc:creator>
	<dc:creator>Mardalena, Selvi </dc:creator>
	<dc:creator>Kruba, Rumaisa</dc:creator>
	<dc:creator>Chongsuvivatwong, Virasakdi</dc:creator>
	<dc:creator>Asshiddiqi, M. Ischaq Nabil </dc:creator>
	<dc:subject xml:lang="en-US">Tuberculosis</dc:subject>
	<dc:subject xml:lang="en-US">Panel Data Regression</dc:subject>
	<dc:subject xml:lang="en-US">Fuzzy Possibilistic C-Means (FPCM)</dc:subject>
	<dc:subject xml:lang="en-US">Health and Environmental Factors</dc:subject>
	<dc:subject xml:lang="en-US">Indonesia</dc:subject>
	<dc:description xml:lang="en-US">Introduction: Tuberculosis (TB) remains a critical global health challenge, with Indonesia ranking second in global TB burden. This study examines factors influencing TB incidence across Indonesian provinces and applies clustering to guide targeted interventions aligned with TB eradication goals by 2030. Specifically, these findings inform Indonesia’s End TB 2030 roadmap by identifying provincial heterogeneity that necessitates differentiated resource allocation and strengthened health governance frameworks.
Methods: This ecological time-series study design analyzed data from 34 Indonesian provinces (2020–2022), including TB cases, healthcare services, HIV cases, smoking prevalence, food management places, and public facilities. Descriptive statistics summarized variable distribution, while panel data regression identified key factors using multicollinearity checks, model selection, and assumption testing. Fuzzy Possibilistic C-Means (FPCM) clustering grouped provinces based on similarity characteristics.
Results: TB cases rose from 10,351 in 2020 to 21,303 in 2022. This study underscores the multifaceted factors influencing TB incidence in Indonesia. Significant factors included healthcare services (?1 = -8.37), HIV cases (?2 = 13.76), smoking prevalence (?3 = 905.32), food management places (?4 = 1.62), and public facilities (?5 = 1.11). This study proves that TB is not only influenced by health factors but also by non-health factors. Fuzzy clustering using the FPCM identified three clusters based on their possibilistic membership degrees: Cluster 3, with high HIV prevalence and public facilities, requiring urgent action; Cluster 2, needing improved healthcare and smoking reduction; and Cluster 1, with moderate challenges.
Conclusions: Health and environmental factors significantly influence TB incidence. Addressing cluster-specific needs, such as enhancing healthcare, reducing HIV and smoking prevalence, and improving public health standards, is essential for TB control. Future studies should expand variables and periods to deepen insights.</dc:description>
	<dc:publisher xml:lang="en-US">Pusat Pengembangan Teknologi Informasi dan Jurnal Universitas Muhammadiyah Palu</dc:publisher>
	<dc:date>2026-07-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jurnal.unismuhpalu.ac.id/index.php/jphp/article/view/7265</dc:identifier>
	<dc:identifier>10.56338/jphp.v6i2.7265</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Public Health and Pharmacy; Vol. 6 No. 2 (2026); 296-309</dc:source>
	<dc:source>2775-4952</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jurnal.unismuhpalu.ac.id/index.php/jphp/article/view/7265/7613</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2026 Journal of Public Health and Pharmacy</dc:rights>
</oai_dc:dc>