Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Journal of Information Systems and Business Technology Journal of Information Technology and Informatics Engineering
Sukrinah
Universitas Pamulang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Library & Information Science

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Perancangan Sistem Manajemen Stok Buku Perpustakaan Berbasis Web Menggunakan Metode Agile Sukrinah; Tetta Thirza Herdyawan
Journal of Information Systems and Business Technology Vol 1 No 1 (2025): Journal of Information Systems and Business Technology
Publisher : PT Jurnal Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

School libraries are very important as a place to get information and references during the learning process. However, the manual management system that is still used causes a number of problems. Some of them are recording errors, delays in returning books, and limited access for teachers and students to information. This study develops a web-based book stock information system using the Agile method. This method was chosen because it is flexible and allows gradual development through sprint iterations, which makes it more responsive to changes in user needs. This system allows printing reports, borrowing and returning, book and category management, and multi-role login features. Testing shows that all features run as expected without significant errors. The implementation results show that the system can speed up book management, make data clearer, and allow everyone in the school to access information. It is hoped that this study will provide solutions to library digitization problems and also be a reference for the development of similar systems in other educational institutions.
Implementasi Algoritma K-nearest Neighbor (KNN) Menggunakan Rapid Miner Untuk Prediksi Penyakit Diabetes Berdasarkan Dataset Pima Indian Tetta Thirza Herdyawan; Dimas Cahyo Saputra; Gabriel Carol Aldosion; Salsha Sabilla Nurhidayat; Sukrinah
Journal of Information Technology and Informatics Engineering Vol 1 No 1 (2025): Journal of Information Technology and Informatics Engineering (JITIE)
Publisher : PT Jurnal Cendekia Indonesi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The objective of this research is to use the publicly accessible Pima Indian dataset to use the K-Nearest Neighbor (KNN) algorithm for diabetes prediction. A straightforward yet powerful classification technique, the KNN method is particularly useful for processing medical data. RapidMiner software was utilized for this study's analysis method, which included data pre-processing, training and test data separation, and classification model validation. Numerous health indicators, including age, blood pressure, body mass index, and glucose levels, are included in the Pima Indian dataset and are utilized as predictive features. The test results demonstrate that the KNN algorithm can categorize patients with or without diabetes with a reasonably high degree of accuracy. Accuracy, precision, recall, and confusion matrix metrics were used to assess the model's performance. As a result, using KNN to this dataset may be a way to help the decision support system for diabetes early diagnosis.
Co-Authors Dimas Cahyo Saputra Gabriel Carol Aldosion Salsha Sabilla Nurhidayat Tetta Thirza Herdyawan