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Data and information have an important role in the decision-making process. In the health sector, data utilization is used to estimate the burden of a disease including its determinants. Tuberculosis (TB) remains a global health problem that infects 10.6 million people worldwide in 2021, where Indonesia is the second highest contributor to caseload after India. The province with the highest number of TB case findings in Indonesia in the last 5 years is West Java Province. To find out the spatial model of risk factors that have an effect on each district/city, an analysis was carried out using a spatial approach using secondary data. The results of this study indicate that there is a positive spatial autocorrelation that has a significant effect on the number of TB cases in West Java Province, which means that the distribution of cases forms a clustered pattern and adjacent areas tend to affect the surrounding area. The districts/cities that have become hotspot areas and are priority areas for intervention in handling TB cases in West Java Province are Bekasi Regency, Bogor Regency, Karawang Regency, Purwakarta Regency, Sukabumi Regency, Bekasi City, Bogor City and Depok City. Spatial analysis found risk factors that had different effects in each district/city area, namely the poor population, temperature and altitude, so that the forms of health interventions carried out were also different. Utilization of data with this spatial approach is expected to be able to support decision-making support related to health intervention programs and policies that are specific to the area so that they are right on target and able to reduce the number of TB cases in West Java Province.
Kematian ibu merupakan salah satu permasalahan kesehatan yang masih terjadi. AKI Indonesia pada tahun 2020 mencapai 189 per 100.000 kelahiran hidup yang masih di atas target SDGs 2030. Dan Jawa Timur merupakan provinsi yang memiliki kasus kematian ibu cukup tinggi di Indonesia. Berbagai faktor dapat berpengaruh terhadap kejadian kematian ibu, baik dari faktor kesehatan maupun non kesehatan. Pendekatan spasial pada penelitian ini bertujuan untuk melihat pengaruh faktor secara lokal di antarwilayah dan antarwaktu. Dalam penelitian ini, digunakan data sekunder berupa agregat dari publikasi profil kesehatan Jawa Timur dan BPS Jawa Timur, dengan variabel dependen kematian ibu, serta independen Rata-Rata Lama Sekolah (RLS), usia kawin, penduduk miskin, rasio tenaga kesehatan, rasio puskesmas, persalinan di fasyankes, dan ANC dari tahun 2021 – 2023. Juga terdapat atribut spasial berupa ketinggian wilayah dan kerapatan jalan serta peta digital. Metode yang digunakan adalah pemetaan faktor risiko dengan overlay serta statistik spasial dengan Geographically Weighted Regression. Didapatkan faktor risiko determinan kematian ibu cenderung sedang dan tinggi di tahun 2021, 2022, dan 2023. Juga didapatkan kejadian kematian ibu terjadi autokorelasi global dengan pola berkelompok. Dan secara autokorelasi lokal, terdapat beberapa wilayah signifikan di setiap tahun. Sedangkan untuk hasil GWR, didapatkan variabel signifikan lokal di tahun 2021 adalah ANC di seluruh wilayah, dan 2022 tidak ada variabel signifikan, sedangkan 2023 beberapa wilayah signifikan dengan rasio tenaga kesehatan dan persalinan di fasyankes, dan beberapa tidak signifikan. Dan untuk model dari nilai R2 bervariasi, meskipun cenderung meningkat dari tahun 2021 ke 2023. Dari hasil penelitian ini diharapkan dapat menjadi bahan perencanaan bagi program kesehatan ibu dan anak di Jawa Timur, agar dapat fokus ke wilayah prioritas intervensi. Kata kunci: kematian ibu, spasial, sosial-ekonomi, layanan kesehatan
Maternal mortality remains a significant health issue. Indonesia’s maternal mortality rate (MMR) in 2020 reached 189 per 100,00 0 live births, still above the 2030 SDGs target. East Java is one of the provinces with the highest maternal mortality rates in Indonesia. Various factors can influence maternal mortality rates, both health-related and non- health-related. The spatial approach in study aims to examine the local influences of these factors across regions and over time. In this study, secondary data in the form of aggregates from East Java health profile publications and the East Java Central Statistics Agency (BPS) were used, with the dependent variable being maternal mortality and the independent variables being Average Years of Schooling (RLS), age at marriage, poor population, health worker ration, health center ratio, deliveries in health facilities, and ANC from 2021 – 2023. Spatial attributes include elevation, road density, and digital maps. The methods used include risk factors mapping with overlay and spatial statistics using Geographically Weighted Regression (GWR). The results indicate that risk factors for maternal mortality tend to be moderate to high ini 2021, 2022, and 2023. Additionally, maternal mortality events exhibit global autocorrelation with a clustered pattern. In terms of local autocorrelation, there were several significant regions in each year. For the GWR results, the significant local variable in 2021 was ANC across all regions, while in 2022 there were no significant variables, and in 2023, some regions were significant with the ratio of healthcare workers and births in healthcare facilities, while others were not significant. The R2 values of the models varied, though they tended to increase from 2021 to 2023. The findings of this study are expected to serve as a basis for planning maternal and child health programs in East Java, enabling a focus on priority intervention areas. Key words: maternal mortality, spatial, social-economic, health services
Unmet Need for Family Planning services is the proportion of women of childbearingage who do not want children anymore or want to delay childbirth but do not usecontraception to prevent pregnancy.Trends unmet need for family planning in Indonesiain the last five years has increased from 11,4% in 2012 to 15,8% in 2016. The studyaims to kmow determinants of the unmet need for family planning the individual at theindividual level and the at district/city in the four provinces with a high need proportion(Maluku, North Sumatera, DKI Jakarta and West Kalimantan. At the individual level,data were taken from Susenas 2016 and at the district/city data were taken from regularbkkbn and bps report. 23,276 married women of reproductive age in Maluku, NorthSumatera, Jakarta and West Kalimantan were used as sample which is part of theSusenas sample in 2016. Data analysis was done by using multilevel logistic regression.Overall, determinants of unmet need for family planning in Maluku, North Sumatera,Jakarta and West Kalimantan are factors at the individual level ie women age, the age offirst marriage, number of living child, residence, BPJS health insurance ownership.Women age is the factor with the greatest contribution to unmet need for familyplanning status. Factors at the individual level have a greater influence on the unmetneed of family planning compared to the factors at the district/city level.Key words:unmet need; women of childbearing age; individual; district/city.
Gizi buruk merupakan masalah kesehatan yang menjadi beban bagi negara-negara berkembang termasuk Indonesia. Pada anak-anak, gizi buruk dapat mengakibatkan terhambatnya pertumbuhan, rentan terhadap penyakit terutama penyakit infeksi, serta dapat pula mengakibatkan penurunan kecerdasan. Sedang pada orang dewasa, kekurangan gizi dapat menyebabkan penurunan produktifitas serta penurunan daya tahan, sehingga mudah terkena penyakit. Di Kabupaten Sambas, hasil pemantauan status gizi (PSG) balita tahun 2003 sampai dengan tahun 2005 menunjukan adanya kecenderungan kasus gizi buruk dan gizi kurang yang terus meningkat dari tahun ke tahun. Selama informasi yang dihasilkan dari sistem informasi gizi baru berupa data cakupan program penanggulangan, belum mengarah pada kondisi wilayah mana yang menjadi prioritas program penanggulangan gizi buruk serta tindakan apa yang akan dilakukan untuk penanggulangan gizi buruk tersebut. Hal ini menyebabkan kurang efektifnya program yang direncanakan. Penelitian ini bertujuan untuk mengembangkan adanya suatu sistem pendukung keputusan untuk program penanggulangan gizi buruk pada balita di Kabupaten Sambas yang dapat membantu dalam proses pengambilan keputusan dengan menggunakan data- data yang telah ada, sehingga keputusan yang diambil dapat lebih efektif dalam penanggulanan gizi buruk. Penelitian yang dilakukan merupakan pengembangan sistem dengan metodologi Structure System Analysis and Design (SSAD) atau metodologi yang berorientasi data (Data Oriented Methodologies). Metodologi ini menekankan pada karakteristik data yang akan diproses. Penelitian ini juga menggunakan Data Flow Diagram (DFD) sebagai alat untuk menggambarkan sistem yang sedang berjalan ataupun sistem yang akan dikembangkan. Hasil penelitian ini menunjukan bahwa pelaksanaan Permantauan Wilayah Setempat (PWS) Gizi di Kabupaten Sambas sudah sesuai prosedur. Permasalahan yang dihadapi pada sistem informasi gizi di Kabupaten Sambas adalah : (1) Laporan dari Puskesmas masih sering terlambat dan tidak tepat waktu (2) Minimnya tenaga pengelola gizi di yang hanya berjumlah 2 orang (3) Data belum dianalisis secara terintegrasi, analisis masih dilakukan secara manual sehingga sering terjadi kesalahan perhitungan baik dalam jumlah maupun hasil akhir dalam bentuk prevalensi. (4) Keluaran yang dihasilkan hanya terbatas pada informasi cakupan program. Untuk mengatasi permasalahan tersebut, diupayakan pembinaan administratif kepada Puskemas, peningkatan kualitas pengelola program gizi, serta dukungan sarana dan prasarana dalam upaya peningkatan pengelolan informasi gizi di Kabupaten Sambas. Sistem Pendukung Keputusan (SPK) yang dihasilkan berupa, pengembangan basis data pemantauan pertumbuhan balita dan pemantauan status gizi (PSG). Keluaran yang dihasilkan sistem berupa data pencapaian cakupan program penanggulangan gizi buruk dalam bentuk tabel, grafik maupun skala prioritas wilayah maupun skala prioritas program dalam bentuk pemetaan sederhana.
Malnutrition is known as one of health problems that still a burden in most developing countries, including Indonesia. It manifests to children in causing growth disorder, vulnerability to some diseases, especially infectious one, and also decreasing the child intelligence. Meanwhile, toward the adult, malnutrition can cause on reducing the productivity, as well as reducing the body resistance that make them vulnerable to some diseases. At Kabupaten of Sambas, the result of the state of nutrition monitoring (PSG) toward under-five in the year of 2003 to 2005 showed from year to year that there is a trend on the increasing of cases on malnutrition and under-nutrition. However, in dealing with the situation, during the malnutrition management program, there has no decision been made in which region will be the priority of the program and what action should be done in order to improve the condition. The situation that produce an ineffective process on program that has been planned. The study has a purpose on developing a decision supporting system for the malnutrition management program toward under-five at Kapubaten of Sambas, by assisting the process on decision making with some existing data at the region, in order to have an effective way on managing the malnutrition problems. The study is using a system development with Structure System Analysis and Design (SSAD) method, or Data Oriented Method, which is emphasized on data characteristic processed. The study is also developing the Data Flow Diagram System. The result of the study on the implementation of Nutrition Local Monitoring Area (NLAM) at Kabupaten Sambas showed that (1) The report from Puskesmas is mostly still delayed and always not on-time; (2) Inadequacy on nutrition management personnel, which is only 2; (3) The existing data has not been well integrated analyzed, and usually using manually, in which make the erroneous on calculation and result for producing the prevalence measurement; (4) The outcome of the NLAM is only limited to the result of the program coverage. Therefore, in order to cope with those issues mentioned above, a capacity building for Puskesmas administration, and quality improvement for nutrition informatics personnel are proposed. The Decision Supporting System (DSS) that has been made is consisting of the development of data base on under-five growth monitoring and state nutrition monitoring (SNM). The outcome of the system development is the data of program coverage on malnutrition management program, in the form of a simple mapping.
