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All Journal JUITA : Jurnal Informatika Bina Insani ICT Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Information System for Educators and Professionals : Journal of Information System Information Management For Educators And Professionals (IMBI) JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Riset Informatika Journal of Information System, Applied, Management, Accounting and Research JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Paradigma INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System
Slamet Widodo
Universitas Bina Sarana Informatika
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Mathematics Other

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Building a Predictive Model for Chronic Kidney Disease: Integrating KNN and PSO Slamet Widodo; Herlambang Brawijaya; Samudi Samudi
Paradigma - Jurnal Komputer dan Informatika Vol. 26 No. 1 (2024): March 2024 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v26i1.3282

Abstract

This study examines the improvement of prediction accuracy for Chronic Kidney Disease (CKD) through the integration of the K-Nearest Neighbors (KNN) method with Particle Swarm Optimization (PSO). Amidst the rising prevalence of CKD, closely related to diabetes and hypertension, early detection of CKD becomes a significant challenge, especially in Indonesia where access to healthcare facilities and public awareness remain limited. This study utilizes the Chronic Kidney Disease dataset from the UCI Machine Learning repository, encompassing 400 patient records with 24 clinical, laboratory, and demographic variables. With the KNN method, this approach classifies data based on feature proximity, while PSO is used for feature selection and parameter optimization, enhancing the model's accuracy and efficiency in identifying CKD at early stages. The findings indicate a significant improvement in prediction accuracy, from 80.00% using KNN to 97.75% after integration with PSO. These results affirm that the combined approach of KNN and PSO holds great potential in improving early detection and management of CKD, paving the way for further research into practical applications in the healthcare field.
Implementation of PDDIKTI Neo Feeder Web Service in Recording of Independent Campus Activities Herlambang Brawijaya; Slamet Widodo; Samudi Samudi
Jurnal Riset Informatika Vol. 5 No. 2 (2023): March 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i2.210

Abstract

Independent Learning-Independent Campus Program (MBKM) is a policy of granting the right for students to be able to take study activities outside the study program as many as three semesters with the division of two semesters of study outside the college and one semester in different study programs in one college. As well as teaching and learning activities, universities must report Independent Learning-Independent Campus activities to DIKTI every semester through the Neo Feeder PDDIKTI application. The Neo Feeder PDDIKTI application has a feature to enter the activities the operator will carry out. The operator enters this data individually on the Neo Feeder PDDIKTI application. This is a significant problem because the data entry process will take quite a lot of time, even though PDDIKTI has provided web service access to universities to optimize the data reporting process using the Neo Feeder PDDIKTI application. Building an application that can be used for recording MBKM activities by utilizing web services provided by PDDIKTI is the primary purpose of this study. The development of an application certainly requires a method as a framework or guide in facilitating the manufacturing process. The extreme Programming (XP) method becomes essential for applications with variable or non-fixed needs. This method has four working elements: planning, designing, coding, testing and software increment. The output generated by this study is an application for recording MBKM activities that use web service restful API technology so that data entry can be done en masse and not one by one.
Co-Authors Endang Retnoningsih Herlambang Brawijaya Herlambang Brawijaya Samudi Samudi Samudi