Article Per Year (5 Year)
p-Index From 2020 - 2025
1.203
P-Index
This Author published in this journals
All Journal Berita Kedokteran Masyarakat Jurnal Biostatistik, Kependudukan, dan Informatika Kesehatan Kesmas: Jurnal Kesehatan Masyarakat Nasional (National Public Health Journal)
Sipahutar, Tiopan
Unknown Affiliation
Health Professions Nursing Public Health

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search

 1 
Autokorelasi Spasial Prevalensi Stunting di Jawa Barat Tahun 2021 Riznawati, Aldila; Yudhistira, Deny; Rahmaniati, Martya; Sipahutar, Tiopan; Eryando, Tris
Jurnal Biostatistik, Kependudukan, dan Informatika Kesehatan Vol. 3, No. 1
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Angka prevalensi stunting Provinsi Jawa Barat tahun 2021 sebesar 24,5% dan menjadi salah satu provinsi dengan kategori stunting kronis-akut di Indonesia. Analisis spasial digunakan untuk mengetahui apakah terdapat korelasi secara spasial antar wilayah kabupaten/kota di Jawa Barat berdasarkan prevalensi stunting. Hasil penelitian menunjukkan adanya autokorelasi spasial positif dan terdapat korelasi secara spasial yang artinya prevalensi stunting di satu wilayah kabupaten/kota berkaitan dengan wilayah disekitarnya. Wilayah yang menjadi hotspot stunting di Jawa Barat tahun 2021 berdasarkan pola kluster yang terbentuk adalah Kabupaten Bandung, Kabupaten Bandung Barat, dan Kota Bandung. Ketiga wilayah ini menjadi prioritas utama dalam melakukan intervensi penurunan prevalensi stunting di Jawa Barat.
Determinan Kematian Balita di Provinsi Bangka Belitung, Gorontalo, dan Papua Barat: Analisis Data SDKI 2017 Mutaqin, Jilan Salshabilla; Rahmaniati, Martya; Hastono, Sutanto Priyo; Sipahutar, Tiopan
Jurnal Biostatistik, Kependudukan, dan Informatika Kesehatan Vol. 3, No. 3
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Bangka Belitung, Gorontalo, dan Papua Barat memiliki angka kematian balita tertinggi berdasarkan wilayah Indonesia bagian Barat, Tengah, dan Timur. Tingginya kematian balita terkait langsung dengan keberlanjutan hidup anak dan merefleksikan kondisi sosio-ekonomi, lingkungan tempat tinggal, serta pemeliharaan kesehatan anak. Penelitian ini dilakukan untuk menyelidiki determinan kematian balita menggunakan data Survei Demografi dan Kesehatan Indonesia (SDKI) 2017. Analisis dilakukan pada 1056 sampel dengan uji potong lintang dan regresi logistik untuk melihat faktor kematian balita yang signifikan serta besar risiko masing-masing faktor pada determinan sosio-ekonomi dan proksi. Jumlah kelahirkan, jenis kelamin anak, ibu yang tidak memberikan ASI, pendidikan ibu, dan umur ibu saat melahirkan menjadi faktor risiko kematian balita. Faktor-faktor pada kedua determinan sosio-ekonomi maupun proksi merupakan faktor penting terhadap kematian balita di Provinsi Bangka Belitung, Gorontalo, dan Papua Barat sehingga interversi yang mengarah pada program perencanaan keluarga, khususnya terkait jumlah kelahiran perlu dilakukan untuk menurunkan angka kematian balita.
Spatial Analysis of Seven Islands in Indonesia to Determine Stunting Hotspots Sipahutar, Tiopan; Eryando, Tris; Budiharsana, Meiwita
Kesmas Vol. 17, No. 3
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Indonesia is a vast country struggling to reduce its stunting prevalence. Hence, identifying priority areas is urgent. In determining areas to prioritize, one needs to consider geographical issues, particularly correlations among areas. This study aimed to discover whether stunting prevalence in Indonesia occurs randomly or in clusters; and, if it occurs in clusters, which areas are the hotspots. This ecological study used aggregate data from the 2018 National Basic Health Research and Poverty Data and Information Report from the Statistics Indonesia. This study analyzed 514 districts/cities across 34 provinces on seven main islands in Indonesia. The method used was the Euclidean distance to define the spatial weight. Moran's index test was used to identify autocorrelation, while a Moran scatter plot was applied to identify stunting hotspots. Autocorrelation was found among districts/cities in Sumatra, Java, Sulawesi, and Bali East Nusa Tenggara West Nusa Tenggara Islands, resulting in 133 districts/cities identified as stunting hotspots on four major islands. Autocorrelation proves that stunting in Indonesia does not occur randomly.
COVID-19 Case Fatality Rate and Detection Ability in Indonesia Sipahutar, Tiopan; Eryando, Tris
Kesmas Vol. 15, No. 5
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The world is currently experiencing a COVID-19 pandemic. More than 5 million people have been infected with COVID-19 and more than 300 thousand have died from this virus worldwide. In Indonesia, the number of infected people has reached more than twenty thousand people and more than one thousand people have died from this virus. During the COVID-19 pandemic, Case Fatality Rate (CFR) was a very important measure for many people because death is very important to each person, including questions of when and how death will occur and whether there is any way to delay it. However, caution is needed in calculating and displaying CFR. This paper will present the uses and the weaknesses of CFR in the context of the COVID-19 pandemic in Indonesia.
Spatial analysis of rabies-transmitting animal bite cases in North Tapanuli Regency, North Sumatera Province in 2016-2020 Simanjuntak, Saidah Fatimah Sari; Sipahutar, Tiopan; Mafkul, Martya Rahmaniati
BKM Public Health and Community Medicine Vol 40 No 02 (2024)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/bkm.v40i02.11278

Abstract

Purpose: Rabies is a priority strategic disease because it has an impact on socio-economic and public health. This study aims to describe the incidence of rabies-transmitting animal bite cases in North Tapanuli Regency in 2016-2020, contribute to understanding the dynamics of cases, and provide effective information in controlling cases of animal bites that transmit rabies. Methods: Ecological study using aggregated data. The data was collected from monthly reports of rabies cases at the North Tapanuli Regency Health Service in 2016-2020. As a unit analysis, all districts are used. QGIS and GeoDA software are used for data analysis. Through GeOda software, spatial autocorrelation analysis was carried out globally using Moran's I test and locally using the LISA test. Results: Rabies-transmitting animal bite cases had a dispersed pattern in 2016 (I<E[I]) and a clustered pattern (I>E[I]). Globally, there is positive spatial autocorrelation in rabies-transmitting animal bite cases between districts in North Tapanuli Regency in 2017 and 2020 (p-value < 0.05). Moran's cluster map shows that locally in 2016-2020, the districts in the quadrant I (High-High) are Siborongborong and Sipoholon. Quadrant II (Low-High) is Adiankoting and Pagaran. Quadrant III (Low-Low) is Pangaribuan, and quadrant IV (High-Low) is Pahae Jae and Pangaribuan. Conclusion: Globally, cases of animal bites that transmit rabies in North Tapanuli Regency occur in clusters. It means that the number of bite cases in one area is related to the number of cases in other nearby areas. Therefore, rabies control program interventions in areas with high observation values must be prioritized so they do not spread to areas with low observation values.
Spatial autocorrelation of stunting prevalence among children under five years in West Bandung Regency in 2022 Minawati; Trihandini, Indang; Sipahutar, Tiopan; Salsabila, Syefira
BKM Public Health and Community Medicine Vol 40 No 01 (2024)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/bkm.v40i01.11645

Abstract

Purpose: This study aims to determine whether there is spatial autocorrelation based on the prevalence of stunting and their spatial diffusion pattern. It also aims to find areas that will become stunting hotspots and cold spots area in West Bandung Regency in 2022. Method: This research employed an ecological study design using spatial analysis to estimate and analyze the distribution pattern of stunting prevalence in the West Bandung Regency in 2022. The data used results from a child monitoring record in Posyandu (Integrated Service Post) carried out by the West Bandung Regency Health Office regarding the prevalence of stunting among children under five years. This study used Moran Index and Local Indicators Autocorrelation (LISA) for spatial pattern analysis. Results: This study shows that there is negative spatial autocorrelation, or the distribution of stunting prevalence forms a random pattern (I<E). This study also indicates that there is statistically no spatial correlation between sub-district areas based on stunting prevalence in West Bandung Regency in 2022 (p-value > 0,05). There is no hotspot and cold spot area of stunting in West Bandung Regency in 2022. Conclusion: The prevalence of stunting in West Bandung Regency in 2022 is not spatially related between sub-district areas, with a random or scattered pattern. The area that is the main priority for intervention is Saguling Subdistrict, the subdistrict with the highest prevalence of stunting. The intervention program implemented in Cililin Subdistrict can be implemented in Saguling Subdistrict to reduce stunting prevalence.
Co-Authors Budiharsana, Meiwita Fachry Abda El Rahman Indang Trihandini Mafkul, Martya Rahmaniati Martya Rahmaniati Minawati Mutaqin, Jilan Salshabilla Riznawati, Aldila Simanjuntak, Saidah Fatimah Sari Sutanto Priyo Hastono Tris Eryando Yudhistira, Deny