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Elfina Novalia
Program Studi Sistem Informasi, Universitas Buana Perjuangan Karawang
Computer Science & IT

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Penerapan Metode K-Nearest Neighbor Untuk Prediksi Jumlah Kasus HIV di Provinsi Jawa Barat Muhammad Adam Rizky Habibi; Shofa Shofia Hilabi; Bayu Priyatna; Elfina Novalia
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 2 (2025): May
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i2.721

Abstract

The high number of HIV/AIDS cases in Indonesia, especially in West Java Province, is a serious challenge in the field of public health. Limitations in understanding the pattern of spread and predicting the trend of HIV cases cause countermeasures to be less than optimal. To overcome this, this study was conducted with the aim of predicting the number of HIV cases in West Java using the K-Nearest Neighbor (KNN) algorithm, based on historical data from Open Data Jabar from 2019 to 2023 which includes 1,617 data from various districts / cities. The research stages include data collection, preprocessing, feature selection, normalization, division of training and test data, and model evaluation using regression metrics: Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared (R²). The evaluation results show that the KNN model with an optimal K value of 19 produces an MAE of 142.31, MSE of 40,442.92, RMSE of 201.10, and R² value of 0.2397. Predictions for 2024 show that areas with the highest number of HIV cases are in Bandung City, Bogor Regency, Bekasi City, Bekasi Regency, and Indramayu Regency.
Implementasi Sistem Pengadaan Material pada SAC dengan Metode Waterfall Deva Defrina Aldeana; Agustia Hananto; Tukino Tukino; Fitria Nurapriani; Elfina Novalia
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 3 (2025): August
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i3.745

Abstract

Decision support systems in the material procurement process are important solutions to improve operational efficiency and accuracy, especially in retail companies such as SAC (Store Adede Cikampek) which is engaged in the sale of dolls. This study aims to design and build a web-based material procurement system that is able to manage the ordering process, stock recording, verification of incoming goods, and reporting automatically. The system development was carried out using the Waterfall method because its systematic stages are very suitable for handling the material procurement process at SAC which was previously manual and undocumented. With the Waterfall approach, each stage such as needs analysis, design, implementation, testing, to maintenance can be carried out in a structured manner, thus ensuring that the system built is able to overcome problems such as late ordering and errors in recording raw materials. At the implementation stage, this system was developed with various features such as supplier data management, raw material stock management, order history, and periodic report generation. To ensure the effectiveness of the system, testing was carried out using the System Usability Scale (SUS) approach involving twenty respondents from internal operational parties. The evaluation results showed that the developed system succeeded in meeting user needs and increasing the effectiveness of the procurement process by obtaining an average score of 96 which was categorized as "Excellent". This system is also considered easy to use, efficient, and can support the decision-making process in real time. It is expected that the implementation of this system can not only solve the problem of material procurement in SAC, but can also be used as a model for implementing similar systems in similar businesses. This research provides a practical contribution in the development of an integrated information system to support more optimal business processes.
Co-Authors Bayu Priyatna Deva Defrina Aldeana Fitria Nurapriani Hananto, Agustia Muhammad Adam Rizky Habibi Shofa Shofia Hilabi Tukino Tukino