Determinan Kejadian Anemia Pada Balita Di Indonesia

The prevalence of anemia in children under five tends to increase from year to year. The impact onmortality and the quality of human resources in the future due to the incidence of anemia, encourages thegovernment to carry out more optimal handling. There are many factors that cause the high prevalence ofanemia in children under five, this article aims to find the determinants associated with anemia in childrenunder five in Indonesia. The preparation of this article uses data from the integration of Riskesdas 2018 andSusenas in March 2018. The samples in this analysis are children under five who are the samples ofSusenas and Riskesdas. Sampling was carried out using the PPS method using Two-Stage SystematicSampling. To find out the determinants related to the incidence of anemia in children under five, BinaryLogistics Regression was used, unadjusted and adjusted. Unadjusted sees the relationship of eachindependent variable to the dependent variable without being influenced by other variables, while adjustedsees the relationship of all independent variables to the dependent variable simultaneously. The results ofthe analysis showed that the prevalence of anemia in children under five was 40.4%, unadjusted, thedeterminants related to anemia were the children under five, the number of household members (ART) andthe economic status of the family, while from the adjusted analysis the influential determinants were thechild's age and economic status. family. Determinants in the age group of children and economic status,both unadjusted and adjusted, have the same pattern, age groups are easier to have a higher risk ofdeveloping anemia compared to the older group, as well as based on family economic status, familyeconomy has a protective relationship to the incidence of anemia in children. children under five, familieswith better economic conditions, can prevent anemia in children under five. Efforts that can be made toreduce the incidence of anemia in children under five in Indonesia include reducing the incidence of anemiain pregnant women in order to reduce the incidence of anemia in children under 24 months. To overcomethis problem, there is counseling about the importance of consuming high-protein foods for children underfive, either in posyandu or other health service facilities, either actively (through face-to-face counseling) orthrough indirect counseling (through posters or leaflets). Abstrak Prevalensi anemia anak balita cenderung menunjukan kenaikan dari tahun ke tahun. Dampak terhadap kematian dan kualitas sumber daya manusia dimasa mendatang akibat kejadian anemia, mendorong pemerintah untuk melakukan penanganan yang lebih optimal. Ada banyak faktor yang menyebabkan tingginya prevalensi anemia pada anak balita, artikel ini bertujuan mencari determinan yang behubungan dengan anemia pada balita di Indonesia. Penyusunan artikel ini menggunakan data integrasi Riskedas 2018 dan Susenas bulan maret 2018. Sampel dalam analisis ini adalah anak balita yang menjadi sampel susenas dan riskesdas. Pengambilan sampel dilakukan dengan metode PPS menggunakan Two-Stage Systematic Sampling. Untuk mengetahui determinan yang berhubungan dengan kejadian anemia pada anak balita digunakan Regresi Logistics Binary, secara unadjusted dan adjusted. Unadjusted melihat keterkaitan masing-masing variabel independen terhadap dependen variabel tanpa dipengaruhi variabel lain, sedangkan adjusted melihat keterkaitan seluruh variabel independen terhadap dependen variabel secara bersamaan. Hasil analisis di dapatkan prevalensi anak balita anemia 40,4%, secara unadjusted diperoleh determinan yang berhubungan dengan anemia adalah usia balita, jumlah anggota rumah tangga (ART) dan status ekonomi keluarga, sedangkan dari analisis adjusted determinan yang berpengaruh adalah usia anak dan status ekonomi keluarga. Determinan pada kelompok usia anak dan status ekonomi baik secara unadjusted maupun adjusted mempunyai pola yang sama kelompok usia lebih muda mempunyai risiko lebih tinggi untuk mengalami anemia dibandingkan dengan kelompok lebih tua, begitu pula berdasarkan status ekonomi keluarga, ekonomi keluarga mempunyai hubungan protektif terhadap kejadian anemia pada anak balita, keluarga dengan ekonomi lebih baik, dapat mencegah terjadinya anemia pada anak balita. Upaya yang dapat dilakukan untuk menurunkan kejadian anemia pada anak balita di Indonesia diantaranya dengan menurunkan kejadian anemia pada ibu hamil agar dapat menurunkan kejadian anemia anak dibawah 24 bulan. Untuk mengatasi permasalahan tesebut penyuluhan tentang pentingnya mengonsumsi makanan tinggi protein bagi anak balita baik di posyandu ataupun fasilitas pelayanan kesehatan lainnya baik secara aktif (melalui penyuluhan tatap muka) atau melalui penyuluhan tidak langsung (melalui poster ataupun leaflet)

Province clustering based on the percentage of communicable disease using the BCBimax biclustering algorithm

Indonesia needs to lower its high infectious disease rate. This requires reliable data and following their temporal changes across provinces. We investigated the benefits of surveying the epidemiological situation with the imax biclustering algorithm using secondary data from a recent national scale survey of main infectious diseases from the National Basic Health Research (Riskesdas) covering 34 provinces in Indonesia. Hierarchical and k-means clustering can only handle one data source, but BCBimax biclustering can cluster rows and columns in a data matrix. Several experiments determined the best row and column threshold values, which is crucial for a useful result. The percentages of Indonesia’s seven most common infectious diseases (ARI, pneumonia, diarrhoea, tuberculosis (TB), hepatitis, malaria, and filariasis) were ordered by province to form groups without considering proximity because clusters are usually far apart. ARI, pneumonia, and diarrhoea were divided into toddler and adult infections, making 10 target diseases instead of seven. The set of biclusters formed based on the presence and level of these diseases included 7 diseases with moderate to high disease levels, 5 diseases (formed by 2 clusters), 3 diseases, 2 diseases, and a final order that only included adult diarrhoea. In 6 of 8 clusters, diarrhea was the most prevalent infectious disease in Indonesia, making its eradication a priority. Direct person-to-person infections like ARI, pneumonia, TB, and diarrhoea were found in 4-6 of 8 clusters. These diseases are more common and spread faster than vector-borne diseases like malaria and filariasis, making them more important