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All Journal SMATIKA Journal of Information Technology
Rahmatina Hidayati
Sistem Informasi, Universitas Merdeka Malang, Indonesia
Computer Science & IT Education

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Komparasi Metode K-Nearest Neighbor dan Naïve Bayes untuk Mengklasifikasi Resiko Diabetes Di Posbindu Desa Bulupitu Rizki Alifia Safitri; Rahmatina Hidayati
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 14 No 02 (2024): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v14i02.1350

Abstract

Diabetes mellitus is one of the fastest-growing health problems in the 21st century. One of the causes is the lack of public awareness for regular health check-ups, while the lifestyle being led is quite unhealthy. Hemoglobin A1c (HbA1c) examination is highly recommended to detect diabetes. However, this service is not yet available at Posbindu in Bulupitu Village. Therefore, another approach is needed to detect the risk of diabetes early, namely through data mining. The data mining methods used in this research are the Naïve Bayes and kNN classification methods. The variables to determine the risk of diabetes include gender, age, family history of diabetes, frequent urination, Body Mass Index (BMI), blood sugar levels, and diabetes risk output. The division of testing and training datasets uses cross-validation and ratio (60:40, 70:30, 80:20, and 90:10). The best accuracy of the Naïve Bayes method was obtained by dividing the dataset using k-fold cross-validation with k=2, achieving 96.1%. In the kNN method, the best results were obtained from the 80:20 dataset ratio. Manhattan distance was found to be the best distance calculation in this study compared to Euclidean distance and Chebyshev distance.
Penerapan Metode Electre Dan SAW Dalam Menentukan Kelayakan Penerima Bantuan Pangan Beras Bulog Amanda Veby Dwi Candra; Rahmatina Hidayati
J-INTECH ( Journal of Information and Technology) Vol 12 No 02 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i02.1330

Abstract

Poverty is a complex social problem, especially in areas where basic needs are difficult. The Indonesian government itself has developed various aid programs, including the provision of food aid in the form of rice. The provision of rice food assistance is often not on target due to various factors, including errors in collecting recipient information. The importance of determining the eligibility of Bulog rice food aid recipients by considering several criteria simultaneously to ensure that the aid is on target. This study discusses the application of the Electre and Simple Additive Weighting (SAW) method in determining the eligibility of Bulog rice food aid recipients of Sukomalo Village residents. Some of the criteria used in this study were age, employment, income level, number of children, status of home ownership, drinking water source, quality of house, and electric power. Research results show that alternative A6 has a total value of E_kl=4, referred to as a primary alternative with the Electre method, while alternative A9 has a total preference value of 18 and processed by the SAW method. Based on the results of the calculation, Bulog rice food aid recipients are on target according to the conditions and conditions of recipients who are very suitable for receiving assistance.
Co-Authors Amanda Veby Dwi Candra Rizki Alifia Safitri