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All Journal JUSIFO : Jurnal Sistem Informasi PREDATECS: Public Research Journal of Engineering, Data Technology and Computer Science
Al-Qadr, Nola Ardelia
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Sales Management System with Rapid Application Development and PIECES Approach Al-Qadr, Nola Ardelia; Novita, Rice; Ahsyar, Tengku Khairil; Zarnelly, Zarnelly
JUSIFO : Jurnal Sistem Informasi Vol 10 No 1 (2024): JUSIFO (Jurnal Sistem Informasi) | June 2024
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v10i1.22222

Abstract

In this era of rapid technological advancement, the computer business plays a crucial role in providing goods and services to meet societal needs. However, Andalas Computer, despite offering a diverse range of products and services, faces challenges in its sales process and stock management, which still rely on manual methods. This study aims to develop a sales management system to facilitate the company's sales. By employing the Rapid Application Development (RAD) method, system requirements analysis can be addressed with feedback from users. This research utilizes PIECES analysis to identify opportunities from various aspects. The study results in a sales management system tailored to user needs. System testing was conducted using blackbox testing, followed by user acceptance testing to gauge user reception of the system. The results of the testing showed a positive acceptance rate of 90%.
Implementation of C4.5 and Support Vector Machine (SVM) Algorithm for Classification of Coronary Heart Disease Anugrah, Muhammad Ridho; Al-Qadr, Nola Ardelia; Nazira, Nanda; Ihza, Nurul
Public Research Journal of Engineering, Data Technology and Computer Science Vol. 1 No. 1: PREDATECS July 2023
Publisher : Institute of Research and Publication Indonesia (IRPI).

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/predatecs.v1i1.805

Abstract

Coronary Heart Disease (CHD) is a chronic disease that is not contagious and can cause heart attacks. This makes CHD one of the diseases that cause the highest mortality globally. CHD can be caused by the main factor, namely an unhealthy lifestyle, so that in an effort to identify and deal with CHD, many studies have been conducted, one of which is the use of information technology. With so many CHD patient data, data mining can be used using. classification methods include C4.5 algorithm and Support Vector Machine (NBC). The C4.5 algorithm is a decision tree-like algorithm that groups attribute values into classes so that it resembles a tree, while SVM is an algorithm that separates data with a hyperplane. This study aims to classify the CHD dataset by comparing the C4.5 and SVM algorithms. So that the best accuracy value for this data is produced, namely the SVM algorithm of 64.51% and followed by the C4.5 algorithm of 64.30%.
Co-Authors Ahsyar, Tengku Khairil Anugrah, Muhammad Ridho Ihza, Nurul Nazira, Nanda Rice Novita Zarnelly Zarnelly