Journal of Intelligent Computing & Health Informatics

Journal Information
ISSN / EISSN : 2715-6923 / 2715-6923
Current Publisher: Unimus Press (10.26714)
Total articles ≅ 5
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Articles in this journal

Astia Weni Syaputri, Erno Irwandi, Mustakim Mustakim
Journal of Intelligent Computing & Health Informatics, Volume 1, pp 17-19; doi:10.26714/jichi.v1i1.5570

Abstract:
Majors are important in determining student specialization. If there is an error in the direction of the student, it will certainly affect the education of subsequent students. In SMA Negeri 1 Kampar Timur, there are two majors, namely Natural Sciences and Social Sciences. To determine these majors, it is necessary to reference the average value of student grades from semester 3 to semester 5 which includes the average value of Islamic religious education, Indonesian, Citizenship Education, English, Natural Sciences, Social Sciences, and Mathematics. Naive Beyes algorithm is an algorithm that can be used in classifying majors found in SMA Negeri 1 Kampar Timur. To determine the classification of majors in SMA Negeri 1 Kampar Timur, training data and test data are used, respectively at 70% and 30%. This data will be tested for accuracy using a confusion matrix and produces a fairly high accuracy of 96.19%. With this high accuracy, the Naive Bayes algorithm is very suitable to be used in determining the direction of students in SMA Negeri 1 Kampar Timur.
Alwan Fadlurrohman
Journal of Intelligent Computing & Health Informatics, Volume 1, pp 23-25; doi:10.26714/jichi.v1i1.5583

Abstract:
Inflation is a tendency to increase prices of goods and services that take place continuously. Inflation is a monthly time series data that is thought to be influenced by location elements. Modeling for inflation forecasting that involves time and location (spatio temporal) can use the Generalized Space Time Autoregressive (GSTAR) method. To increase accuracy in modeling and forecasting, the GSTAR model was developed into the GSTARX model by involving exogenous variables. Exogenous Variavel used in GSTARX modeling for forecasting Inflation is a variation of the Eid calendar. This GSTARX modeling is applied for inflation forecasting in six cities Cost of Living Survey (SBH) in Central Java, namely Cilacap, Purwokerto, Semarang, Kudus, Magelang and Surakarta. The purpose of this study is to get the best GSTARX model for inflation forecasting for six SBH cities in Central Java. The selection of the best model from the GSTARX method is seen with the smallest RMSE value of each model. Obtained that the GSTARX model with uniform weights is the best model because it has a smaller RMSE compared to the GSTARX model with inverse distance weights, the RMSE values are 0.6122 and 0.6137, respectively. It can be concluded that the GSTARX method with Uniform weighting can provide better performance and can be used to predict the inflation of the six SBH cities in Central Java in the next 12 periods.
Ahmad Fauzan, Noviandi Noviandi
Journal of Intelligent Computing & Health Informatics, Volume 1, pp 9-14; doi:10.26714/jichi.v1i1.5397

Abstract:
The Information technology development has affected various sectors, including health services. The several technologies have been used to improve health facilities performance. At Johar Baru Health center, central Jakarta, SIKDA (Sisitem Informasi Kesehatan Daerah) Optima application has been applied. Meanwhile, the implementation of SIKDA Optima is not as good as expected. There still many disruptions during the use of this application such a delay service and delivery of report was not in a real time, therefore an evaluation is needed. The purpose of this study was to determine the quality of system, information, and service which is affecting the satisfaction of SIKDA Optima users at Johar Baru Health Center, Central Jakarta. This study used a quantitative approach with observational survey and cross-sectional design. The population in this study was 98 persons and the sample were 79 users of SIKDA Optima, consist of 19 doctors, 22 nurses, 17 midwives, 9 pharmacies, 2 medical recorder and 10 administration staffs. Data analysis was performed using multiple linear regression. The results of multiple linear regression test showed that the user satisfaction of SIKDA Optima = -3.832 + 0.549 (KS) + 0.757 (KI) + 0.359 (KL) with a p-value of KS 0.001
Deden Istiawan
Journal of Intelligent Computing & Health Informatics, Volume 1, pp 1-4; doi:10.26714/jichi.v1i1.5380

Abstract:
Prosperity has a relative, dynamic, and quantitative meaning. Until now, the formula is not finished because it will continue to grow along with the times. Public welfare is a condition where all citizens are always in a condition that is completely adequate in all their needs. Poverty in Central Java Province is still above national poverty. Poverty grouping is one way to focus on the people's budget in each region so that they can take development policies and strategies that are right on target and effective. In this study, the proposed K-means algorithm for classifying poverty in Central Java is based on poverty indicators. The results of the first cluster study consisted of 22 districts / cities with the category of not poor, the second cluster consisted of 13 districts / cities that were categorized as poor.
Sendi Nugraha Nurdiansah, Laelatul Khikmah
Journal of Intelligent Computing & Health Informatics, Volume 1, pp 5-8; doi:10.26714/jichi.v1i1.5381

Abstract:
The phenomenon of poverty is a serious problem faced by almost every country in the world. This is because poverty can affect various aspects of people's lives. One of the causes of poverty is due to lack of income and assets to meet basic needs such as food, clothing, housing, health level and acceptable education. In addition, poverty occurs because of the powerlessness of society to get out of the problems it faces. The Central Java regional government incorporated poverty issues into the Regional Medium-Term Development Plan (RPJMD) because Central Java has a high number of poor people. This was done as an effort by the Central Java government to reduce poverty. Therefore, research is needed to find out the variables that most influence poverty in order to assist the government in developing the RPJMD. To find out what factors influence poverty in Central Java with the dichotomous categorical response variable, binary logistic regression analysis was used. The results showed that based on the analysis conducted did not obtain a logistic regression equation model because there were no significant parameters because there were no variables that had a sig value
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