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All Journal Proceedings of the International Conference on Applied Science and Health JTIM : Jurnal Teknologi Informasi dan Multimedia
Nina Rahmadiliyani
STIKES Husada Borneo, Jl. Akhmad Yani Km. 30,5 No. 4 Banjarbaru.
Computer Science & IT Education Health Professions Medicine & Pharmacology Nursing Public Health

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FAMILIYS SUPPORT AND ITS EFFECT IN INCREASING THE ELDERLY VISITATION TO POSYANDU Ariani, Wenty Ika; Rahmadiliyani, Nina; Widyawati, Widyawati
Proceedings of the International Conference on Applied Science and Health No 2 (2017)
Publisher : Proceedings of the International Conference on Applied Science and Health

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (668.846 KB)

Abstract

Introduction: Along with global tendency of increasing life expectancy, the number of elderly in Indonesia also tends to increase. To monitor the well-being of the elderly, both from the mental and the physical standpoints, the government-run integrated health service posts (Posyandu) hold a special program for the senior citizens. Aims: To analyze the association between families support and elderly visitation in Danau Panggang Health Center. Methods: This study used analytic survey with cross sectional design. The population were 378 elderly age 59 years old and older in Danau Panggang Health Center in 2015, and with Taro Yamane, the chosen sample was 194 elderly. The chi-square test was used for statistical analyses. Results: The study showed most of the respondents (56.7%) do not support and a majority of elderly do not actively participate (57.2%). Hypothesis test results showed that there is a correlation between family support and elderly participation to Posyandu with p-value = 0.000 < (α = 0.05). Conclusion: Family supports can increase elderly visitation to Posyandu. Participating in Posyandu activities and following the health officers’ directions prove beneficial to improve health conditions among the elderly. This research is expected to be an input for Posyandu to enhance its elderly program by optimizing the performance and presence of cadres in each activity. 
Implementasi Data Mining dalam Menentukan Prediksi Status Resiko Persalinan pada Ibu Hamil menggunakan Algoritma C4.5 Poernareksa, Dwidya; Rahmadiliyani, Nina
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2025): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i1.619

Abstract

High-risk of pregnancy refers to a situation where pregnancy will have a negative impact on the safety of the mother and baby. Since the beginning of pregnancy, high-risk pregnancy can be predicted by various factors such as the physical and psychological condition of the pregnant woman, nutritional intake, and congenital diseases. According to WHO, Indonesia ranks 5th in premature birth rates with 675,700 babies and this figure is 15.5% of the total birth rate in Indonesia. Estimates of high-risk pregnancies can be observed from patient medical record data, in this case, pregnancy data from pregnant women. Data that is processed into knowledge can be processed through the data mining process. The main objective of this study is to determine how data mining is implemented in determining the prediction of the birth process in pregnant women using the C4.5 algorithm. This research can provide knowledge about the combination of the Two Crows model and the C.45 algorithm to predict the risk status of childbirth in pregnant women. The C.45 algorithm is one of the most popular prediction techniques because it is easy for humans to interpret. The data analysis technique in this study uses the Two Crows model which is a development of the CRISP-DM model. The flow of the Two Crows model includes Understanding Business Problem, Building Data Mining Database, Data Explore, Prepare Data For Modeling, Building Model, and Evaluate Model. The data taken is examination data on pregnant women at the Health Center. Based on the results of the study, it was found that the highest root of the application of the C4.5 algorithm is in the height variable. The evaluation was carried out using a confusion matrix. From the evaluation results, it was found that the accuracy value reached 98.44%, the precision value reached 96%, and the recall value reached 100%.
Co-Authors Ariani, Wenty Ika Poernareksa, Dwidya Widyawati Widyawati