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All Journal Jurnal Teknologi Komputer dan Sistem Informasi JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)
Sidik Rahmatullah
Institut Teknologi Bisnis dan Bahasa Dian Cipta Cendikia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Implementasi Data Mining Untuk Memprediksi Status Gizi Anak Balita Pada Puskesmas Gedung Sari Menggunakan Polynomial Regression Evi Marlena; Sidik Rahmatullah; Sigit Mintoro; Ngajiyanto Ngajiyanto
JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi) Vol 6, No 2 (2023): JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)
Publisher : STMIK Pringsewu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/jtksi.v6i2.1490

Abstract

Predictions of children's nutritional Status can provide important input to. efforts to monitor and intervene in child nutrition, as well as support better decision-making in the field of child health. This study took data from Puskesmas data. Gedung Sari Health Center is a community health center located in Anak Ratu Aji District, Central Lampung Regency. Based on the results and discussion of the data analysis on the data above, related to the prediction of the nutritional status of toddlers at the Gedung Sari Health Center using polynomial regression, a conclusion is obtained. The conclusion of predicting nutritional status using polynomials depends on specific data analysis and modeling and the methods used. However, in general, polynomials can be used to model the relationship between input and output variables in the case of predicting nutritional status. predicted nutritional status of children and total predicted nutritional status obtained Predictions based on age in 2019 = 290,806; Predictions based on nutritional status in 2020 = 68,176; Predictions based on nutritional status in 2021 = 122,239. More research needs to be done to validate and increase the reliability of a prediction and integrate the results into health practice to improve child nutrition monitoring and interventions in the community health center.
Penerapan Data Mining Menggunakan K-Means Untuk Penentuan Penerima Bantuan Langsung Tunai (BLT) Dana Desa Pada Desa Cempaka Timur Huswatun Hasanah; Pakarti Riswanto; Sidik Rahmatullah
JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi) Vol 6, No 3 (2023): JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)
Publisher : Institut Bakti Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/jtksi.v6i3.1508

Abstract

Direct Cash Assistance is the provision of a sum of money to underprivileged people. This assistance is to help underprivileged communities in dealing with the corona virus (Covid19). In the distribution of Direct Cash Assistance, problems often occur as the distribution is not fully on target. BLT recipients were not on target because the determination process still used manual bookkeeping and the computerized process used MS. Excel so that the level of accuracy of data processing is still in doubt. Therefore to predict the determination of BLT recipients using the K-Means method and its implementation using MS. Excel and Python. Given that this method is one of those utilized to group data as a reference in making decisions on clustering sizable amounts of data, it is quite ideal for applying the predictions of BLT-DD Assistance recipients. From the results obtained in the processing of Direct Cash Assistance data using attributes that greatly influence, namely work, status of residence, income and number of dependents by obtaining two clusters, namely feasible or not feasible. In 2020 there were 38 eligible recipients of direct cash assistance and 72 inappropriate categories, in 2021 there were 30 eligible recipients of cash assistance and 70 inappropriate categories, in 2022 there were recipients of direct cash assistance with the category 29 people are eligible and 61 people are not eligible.
Implementasi Data Mining Untuk Memprediksi Status Gizi Anak Balita Pada Puskesmas Gedung Sari Menggunakan Polynomial Regression Evi Marlena; Sidik Rahmatullah; Sigit Mintoro; Ngajiyanto Ngajiyanto
JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi) Vol 6, No 2 (2023): JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)
Publisher : Institut Bakti Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/jtksi.v6i2.1490

Abstract

Predictions of children's nutritional Status can provide important input to. efforts to monitor and intervene in child nutrition, as well as support better decision-making in the field of child health. This study took data from Puskesmas data. Gedung Sari Health Center is a community health center located in Anak Ratu Aji District, Central Lampung Regency. Based on the results and discussion of the data analysis on the data above, related to the prediction of the nutritional status of toddlers at the Gedung Sari Health Center using polynomial regression, a conclusion is obtained. The conclusion of predicting nutritional status using polynomials depends on specific data analysis and modeling and the methods used. However, in general, polynomials can be used to model the relationship between input and output variables in the case of predicting nutritional status. predicted nutritional status of children and total predicted nutritional status obtained Predictions based on age in 2019 = 290,806; Predictions based on nutritional status in 2020 = 68,176; Predictions based on nutritional status in 2021 = 122,239. More research needs to be done to validate and increase the reliability of a prediction and integrate the results into health practice to improve child nutrition monitoring and interventions in the community health center.
Co-Authors Evi Marlena Huswatun Hasanah Ngajiyanto Ngajiyanto Pakarti Riswanto Sigit Mintoro