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All Journal International Journal of Public Health Science (IJPHS) PROSIDING SEMINAR NASIONAL Jurnal Keperawatan Indonesia Media Kesehatan Masyarakat Indonesia ASPIRATOR Jurnal Kesehatan Masyarakat Jurnal Penelitian Kesehatan Suara Forikes JURNAL DIVERSITA Jurnal Penelitian dan Pengembangan Pelayanan Kesehatan Al-sihah: The Public Health Science Journal Jurnal Kreativitas PKM Manuju : Malahayati Nursing Journal Jurnal Manajemen Informasi Kesehatan Indonesia (JMIKI) Surya Medika: Jurnal Ilmiah Ilmu Keperawatan dan Ilmu Kesehatan Masyarakat Jurnal Ilmiah Kesehatan Masyarakat : Media Komunikasi Komunitas Kesehatan Masyarakat Jurnal Kesmas Untika Luwuk: Public Health Journal Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Cahaya Mandalika Charity : Jurnal Pengabdian Masyarakat Jurnal Indonesia : Manajemen Informatika dan Komunikasi Indonesian Journal of International Law Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Indonesian Journal of Multidisciplinary Science Makara Journal of Health Research Berita Kedokteran Masyarakat Medika Respati : Jurnal Ilmiah Kesehatan Jurnal Keperawatan Merdeka Jurnal manajemen informasi kesehatan Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal Biostatistik, Kependudukan, dan Informatika Kesehatan Proceeding Mulawarman International Conference on Tropical Public Health Kesmas: Jurnal Kesehatan Masyarakat Nasional (National Public Health Journal)
Tris Eryando
Departemen Biostatistik Dan Ilmu Kependudukan Fakultas Kesehatan Masyarakat Universitas Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Neuroscience Nursing Public Health Social Sciences

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Faktor Dominan yang Mempengaruhi Kejadian Malaria di Perdesaan Susanna, Dewi; Eryando, Tris
Kesmas Vol. 4, No. 4
Publisher : UI Scholars Hub

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Abstract

KLB malaria selama periode 1998-2003 telah menyerang 15 propinsi yang meliputi 84 desa endemis dengan jumlah penderita 27.000 dengan kematian 368. Hewan besar seperti sapi, kerbau dan kuda adalah merupakan cattle barrier malaria. Hewan tersebut perlu diteliti agar dapat diketahui jenis hewan dan tempat hidup hewan (kandang) terhadap kejadian malaria. Tujuan umum penelitian ini adalah untuk mengetahui faktor dominan yang mempengaruhi kejadian malaria di pedesaan. Jenis penelitian adalah non-intervensi, merupakan analisis lanjut data sekunder yaitu “Riset Kesehatan Dasar 2007”. Subyek yang dianalisis sebanyak 618.593 yang bertempat tinggal di perdesaan. Analisis dilakukan dengan metoda multivariat menggunakan regresi logistik. Ternak dibagi menjadi empat kategori, yaitu unggas (ayam, burung, dan bebek/itik), ternak besar (sapi, kuda, dan kerbau), ternak sedang (babi, domba,dan kambing), dan ternak kecil (kucing, anjing, dan kelinci). Faktor yang paling dominan mempengaruhi kejadian malaria adalah kepemilikan ‘ternak sedang’ (kambing, babi, dan domba), dengan OR = 0,52 (0,50-0,54). Faktor yang paling dominan mempengaruhi kejadian malaria adalah tidak adanya ‘ternak sedang, yaitu kambing, babi, dan domba. Malaria outbreak in the period of 1998-2003 was occurred in 15 province including 84 endemic villages with number of cases of 27 000 and deaths of 368. Big cattles such as cow, horse and buffalo have been known as cattle barrier for malaria, while others have not been investigated yet. The objective of this research was to know the dominant factor related to cattle which influenced malaria in village area. The secondary data from ‘Riset Kesehatan Dasar 2007” had been used in this research with total population of 618593 who lived in village area and was analyzed using logistic regression test. Cattle as independent variable was divided into four categories, they were poultry (chicken, bird, and duck), big cattle (cow, horse and buffalo), medium cattle (pig, sheep, and goat), and small cattle (cat, dog, and rabbit). The most dominant factor for protection of malaria was medium cattle (pig, sheep, and, goat) as protective with Odds Ratio of 0.52 (0.50-0.54). The other cattle had Odds Ratios less than 2, although they had p value < 0.05. The medium cattle was the dominant factor influenced malaria in village area, while others did not have effect.
Bayi Berat Lahir Rendah di Rumah Sakit Umum Daerah Pasar Rebo dan Faktor-faktor yang Berhubungan Djaali, Nur Asniati; Eryando, Tris
Kesmas Vol. 5, No. 2
Publisher : UI Scholars Hub

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Abstract

Salah satu penyebab utama angka kematian bayi yang tinggi adalah masalah berat badan lahir di bawah 2500 gram (berat badan lahir rendah). Berdasarkan data dari Statistik Rumah Sakit Indonesia tahun 2005, sekitar 40,7% kematian bayi disebabkan oleh berat lahir rendah, pertumbuhan janin yang lambat, malnutrisi janin, dan gangguan yang berhubungan dengan kecukupan masa kehamilan. Angka BBLR di RSUD Pasar Rebo pada tahun 2007 mencapai 8,7%. Tujuan penelitian ini adalah mengetahui berbagai faktor yang mempengaruhi berat lahir menggunakan data rekam medis RSUD Pasar Rebo. Studi ini menggunakan desain crosseksional dan data retrospektif rekam medis rumah sakit. Populasi penelitian adalah seluruh ibu yang melahirkan di RSUD Pasar Rebo, Sampel diperoleh dengan teknik simple random sampling, dan jumlah sampel dihitung menggunakan rumus sample size uji hipotesis koefisien korelasi dengan variabel kontinyu/ numerik. Hasil analisis dan pengolahan data menunjukkan berat lahir berdistribusi normal dengan rata-rata sebesar 3126,6 gram dan standar deviasi sebesar 453,65 gram. Tingkat pendidikan, usia kehamilan, dan kenaikan berat badan ibu selama hamil berhubungan signifikan dengan berat badan bayi lahir. Berdasarkan hasil analisis regresi linier ganda, didapatkan bahwa ketiga variabel tersebut berkontribusi pada berat lahir dan tingkat pendidikan berkontribusi paling besar. Of the main causes of high infant mortality rate is birth weight under 2500 gram (low birth weight/LBW). Base on data from Indonesian Hospital Statistic in 2005 =, as much as 40,7% baby’s death was caused by low birth weight, intrauterine growth restriction, fetal malnutrition, and problem related with term of pregnancy. Base on data from sample, LBW in RSUD Pasar Rebo in 2007 reached 8,7%.This study is aimed to know the factors that influence infant birth weight as observed from medical record in Pasar Rebo Public General Hospital, Jakarta, and to identify what factor influence most in predicting infant birth weight. A cross-sectional study was designed using retrospective data of hospital medical record. The population of this study was all mothers who gave birth in this hospital, had complete registration and data containing variables observed, such as infant birth weight, and at least performed antenatal care visit in the first trimester. Simple random sampling was administered. The amount of samples were obtained using correlation coefficient hypothesis testing sample size formula with continuous variable. Data processing and analysis showed that infant birth weight are distributed normally with mean 3126.6 grams and 453.655 grams standard deviation. Further analysis showed that educational level, term of pregnancy, and weight-gained during pregnancy were significantly related with infant birth weight. Using double linear regression analysis, those three variables contributed in predicting infant birth weight, where the educational level contributed most.
Spatial Analysis for Enhancing the Use of Health Data Availability from Different Sources to Help the Decision-Making Process Eryando, Tris
Kesmas Vol. 17, No. 3
Publisher : UI Scholars Hub

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Abstract

Spatial analysis in public health has become a common method used by researchers to understand the distribution of public health aspects related to the surrounding environment. It can also be used to analyze individual information in the form of a dot and the location or line of aggregated information in a specific area of study. Another benefit is the possibility of using different data sources to be analyzed in one statistical model analysis, as long as the identification area is sufficiently clear as a key variable. Spatial analysis can show an object's distribution on a locational map and explain the distribution type, whether random, cluster, or uniform. The statistical analysis model can also develop different risk factors for each region of the research area. A specific model sometimes explains how to treat health issues differently in a specific location and can be used as an alternative approach to dealing with an intervention plan for public health issues based on specific local phenomena.
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

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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.
Users’ Perception of the Hospital Information System in a Maternity Hospital in Lampung, Indonesia Asyary, Al; Prasetyo, Arief Kurniawan Nur; Eryando, Tris; Gerke, Solvay
Kesmas Vol. 14, No. 2
Publisher : UI Scholars Hub

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Hospital information systems (HIS) have been applied on a massive scale; however, user evaluation of their effectiveness, efficiency, and service quality improvements remain rare. This study aimed to describe the utility of information systems from the users’ point of view by using the Technology Acceptance Model (TAM) in a maternity hospital in Lampung, Indonesia. The study provided an overview of the features of the information system and the workflow of the user through this information system. Screenshots were taken by using Camtasia Studio 2.0 Trial Version application software for one day (two shifts) in the outpatient service. The HIS generally supported the workflow, but not all application modules were fully applied. The obstacles appear to be at the registration unit/outpatient registration and queue dashboard, cashier unit, pharmacy unit, medicine storage/room, and poly unit/checking room. A TAM framework, which included perceived ease of use and perceived usefulness of the information system, revealed that the currently implemented HIS was not perceived as optimal. However, users are still optimistic and aware of the usefulness of the information system in supporting their jobs. Thus, leaders have committed to initiate the potential development of this information system in the inpatient polyclinic.
Level of Exposure of Childhood Tuberculosis with Adult Pulmonary Tuberculosis Household Contacts Asyary, Al; Eryando, Tris; Purwantyastuti, Purwantyastuti; Junadi, Purnawan; Clark, Carol; Teijlingen, Edwin van
Kesmas Vol. 12, No. 1
Publisher : UI Scholars Hub

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Abstract

Tuberkulosis paru (TB) pada anak kian menjadi masalah kesehatan global yang masih terlupakan seiring dengan peningkatan proporsi TB di Indonesia. Penularan penyakit ini di populasi umum seringkali berdampak pada anak, terlebih ketika kontak TB terjadi di rumah tangga. Penelitian ini bertujuan untuk memperoleh faktor protektif sehingga anak tetap sehat meskipun memiliki kontak dengan penderita TB dewasa serumah. Penelitian ini dilakukan dengan pendekatan kasus kontrol pada 132 responden anak yang berasal dari delapan rumah sakit rujukan dan beberapa puskesmas di Provinsi Daerah Istimewa Yogyakarta. Penelitian dilakukan dalam periode Januari hingga Desember 2014 yang hasilnya dianalisis dengan uji bivariat (kai kuadrat) dan multivariat (regresi logistik ganda). Hasil penelitian menunjukkan bahwa rumah yang memenuhi syarat kesehatan, yakni ruang tidur yang sehat, serta paparan yang jarang diterima dari penderita TB dewasa mampu memproteksi anak agar tetap sehat meskipun tinggal serumah dengan penderita dewasa penyakit ini. Penelitian ini menyimpulkan bahwa lama tinggal bersama bukanlah faktor risiko penyakit TB pada anak.Hal ini karena meskipun lama tinggal bersama antara penderita TB dewasa dengan anak, namun apabila memiliki paparan yang jarang, hal ini pun tidak signifikan menjadikan anak untuk terkena TB. Pulmonary tuberculosis (TB) in children is a neglected global health problem, with an increasing proportion of TB cases in Indonesia. Children with TB are most often impacted by TB transmission in the population at large, especially adult TB that exists in the child’s household. This study aimed to find protective factors that can keep children healthy despite household adult TB contacts. This study reports on 132 respondents with a case-control study conducted at nine referred hospitals and several health centers based on medical records at Special Region of Yogyakarta Province. The study lasted from January to December 2014, while the data analysis was used by both of bivariate (chi-square) and multivariate (multiple logistic regression) analysis. The study found that healthy houses, especially those with healthy bedrooms and fewer exposures to adult TB sufferer, influenced by confounder variables, protected children from TB even though they were exposed to adult TB in their environment. Longer periods of living together is not a risk factor for children to contract TB when living with adult TB patients at home. However, this risk increases with frequent exposure among children to adult TB patients at home.
COVID-19 Case Fatality Rate and Detection Ability in Indonesia Sipahutar, Tiopan; Eryando, Tris
Kesmas Vol. 15, No. 5
Publisher : UI Scholars Hub

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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 Durbin Model on the Utilization of Delivery at Health Facilities: A 2017 Indonesian Demographic and Health Survey Analysis Wahyuni, Indah Sri; Gustina, Ira; Makful, Martya Rahmaniati; Eryando, Tris
Kesmas Vol. 19, No. 2
Publisher : UI Scholars Hub

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Abstract

The utilization of delivery at health facilities is a major intervention in reducing 16 to 33% of deaths. This study aimed to determine the model of utilization of delivery at health facilities in Indonesia in 2017 and its influential factors. This study used secondary data from the 2017 Indonesian Demographic and Health Survey using a Spatial Durbin Model (SDM) approach. The population was mothers aged 15 – 49 years, spread across 34 provinces of Indonesia, and had 15,321 samples. The results showed that the Moran’s I value was positive (0.146) and significant at p-value = 0.007, indicating clustered regions with similar characteristics. The SDM modeling estimation results (R2 = 91.61%) presented those dependent and independent variables that influenced the utilization of delivery at health facilities and its influential factors. The significant and most dominant direct factor that influenced the utilization of delivery at health facilities was pregnancy visits, while the most dominant indirect factor was socioeconomic status. Therefore, further policy planning is expected to be based on regional specificities, and effective intervention programs should be designed based on these factors.
Applied Machine Learning for Early Diabetes Detection Based on Symptoms Intansari; Tris Eryando; Miftakul Fira Maulidia; Edi Utomo Putro
BKM Public Health and Community Medicine The 12th UGM Public Health Symposium
Publisher : Universitas Gadjah Mada

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Abstract

Purpose: Diabetes is a chronic disease that occurs either when the pancreas does not produce enough insulin or when the body cannot effectively use the insulin it produce. Diabetes is often referred to as a silent killer because this disease can affect all organs of the body and cause various symptoms. About 422 million people worldwide have diabetes, the majority living in low-and middle-income countries, and 1.5 million deaths are directly attributed to diabetes each year. Early diabetes detection is essential to prevent serious complications in patients based on symptoms. Method: This study present a prediction using various Machine Learning (ML) algorithm based on age, gender and symptoms as predictor such as polyuria, feeling thirsty, easy itching, losing weight unintentionally, blurred vision, irritability and feeling tired. We have used such a dataset of 520 patients, which has been collected using direct questionnaires from the patients of Sylhet Diabetes Hospital, Bangladesh. Results: This study compared several machine learning algorithms such as Logistic Regression, Naive Bayes, Classification and Regression Trees (CART), K-Nearest Neighbour, and Random Forest to develop diabetes prediction model. Several parameter, including classification accuracy (CA), F1 score, precision, and recall were used to evaluate the models. CART algorithm showed better parameter values, with CA 97,1%, recall 0.953, precision 0.932, and F1 score 0.901. Conclusion: The use of machine learning models for early detection of diabetes with an accuracy rate of 97,1%. ML offers the ability to develop a quick prediction model for diabetes screening based on symptoms. We hope that with this study can contribute to the wider community by decrease the incidence of diabetes through recognizing suspicious symptoms. To prevent diabetes the future this machine learning model can be developed into a mobile application that the public can widely access.
Analisis Spasial Pemetaan Prioritas Penanganan Pneumonia pada Balita di Provinsi Jawa Timur Tahun 2022: Spatial Analysis of Mapping Priorities for Handling Pneumonia in Toddlers in East Java Province 2022 Delfiyanti, Rani; Eryando, Tris
Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Vol. 7 No. 5: MAY 2024 - Media Publikasi Promosi Kesehatan Indonesia (MPPKI)
Publisher : Fakultas Kesehatan Masyarakat, Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/mppki.v7i5.5026

Abstract

Latar belakang: Pneumonia masih menjadi penyebab utama mortalitas dan morbiditas pada anak. Adapun Provinsi Jawa Timur di tahun 2021 merupakan provinsi dengan penyakit pneumonia balita paling banyak di Indonesia yakni sebanyak 74.071 kasus. Tujuan: Penelitian ini dilakukan untuk memperoleh pengetahuan mengenai penyebaran pneumonia balita di provinsi Jawa Timur tahun 2022 serta menentukan wilayah prioritas penanganan penyakit pneumonia pada balita di provinsi Jawa Timur. Metode: Penelitian ini merupakan penelitian observasional analitik dengan pendekatan desain ekologi menggunakan aplikasi Quantum GIS (QGIS) versi 3.22. Hasil: Hasil pemetaan kasus pneumonia balita di Jawa Timur tahun 2022, terdapat dua wilayah dengan kategori jumlah kasus pneumonia balita kategori tinggi yakni Kota Surabaya dan Kabupaten Sidoarjo. Dengan case fatality rate (CFR) tertinggi pada wilayah Kabupaten Pacitan sebesar 0,9%. Kesimpulan: Berdasarkan pengolahan data melalui klasifikasi dan skoring menunjukkan bahwa wilayah prioritas 1 terdiri dari Kabupaten Bangkalan, Kabupaten Sampang, Kabupaten Probolinggo, Kota Surabaya, dan Kabupaten Malang.
Co-Authors Aenaya Delavera Aenaya Delavera Afriansyah, Eddy Agung Waluyo Al Asyary Al Asyary Aldila Riznawati Aldila Riznawati Allagan, Tiurma Mangihut Pitta Allenidekania Allenidekania Anggela Pradiva Putri Apriningrum, Nelly Aria Kusuma Aria Kusuma Arief Kurniawan Nur Prasetyo Arman Harahap Artha Prabawa Astuti Yuni Nursasi Bagus, Nurzahara Bahar, Ryza Jazid Budi Anna Keliat Budiharsana, Meiwita Carol Clark Clark, Carol Daniah Daniah Delavera, Aenaya Delfiyanti, Rani Deny Yudhistira Deny Yudhistira Dera Alfiyanti Dewi Susanna Dia Wulandari Dian Kistiani Irawaty Dian Pratiwi Dian Pratiwi Dian Pratiwi Dian Pratiwi Doni Lasut Doria, Magda Dwi Prihatin Era Edi Utomo Putro Edwin van Teijlingen Efi Trimuryani Elly Nurachmah Elysabeth Sinulingga Fajar Nugraha Falupi, Lilik Aryani Gerke, Solvay Gustina, Ira Hanny Handiyani Helmi Safitri Hermansyah, Hendra Indah Sri Wahyuni Intansari Irawaty, Dian Kristiani Jesa Nuhgroho Juariah Juariah Jusuf, Ester Indahyani Kemal N. Siregar Makful, Martya Rahmaniati Martya Rahmaniati Martya Rahmaniati Martya Rahmaniati Martya Rahmaniati Martya Rahmaniati Meiwita Budiharsana Miftakul Fira Maulidia Milla Herdayati, Milla Nani Nurhaeni Negari, Nurfatia Nessi Meilan Nuhgroho, Jesa Nur Asniati Djaali Nurfatia Negari Nurhidayah, Nurhidayah Nuridzin, Dion Zein Prasetyo, Arief Kurniawan Nur Purnawan Junadi Purnawan Junadi Purnawan Junadi Purwantyastuti Purwantyastuti Purwantyastuti Purwantyastuti Purwantyastuti Purwantyastuti Rahmadewi Rahmadewi Ratna Sitorus Resti Sintya Ervina Restu Apriena Putri Restu Apriena Putri Retnowati Retnowati Riris Dian Hardiani Ristina Rosauli Harianja Riznawati, Aldila Roma Tao Toba MR Ryza Jazid Safanta, Nurzalia Safitri, Helmi Saini, Izzatul Mardiah Sipahutar, Tiopan Solly Aryza Solvay Gerke Sri Yona Sulastri Sulastri Supriyadi Supriyadi Talib, Suprohaita Rusdi Teijlingen, Edwin van Tiopan Sipahutar Tiopan Sipahutar Tri Agustini Trivalni, Ratih Violila, Vallery Warendi Warendi Winarni Naweng Triwulandari Winnie Tunggal Mutika Yati Afiyanti Yudhistira, Deny Yulia Herawati Yvonne M. Indrawani