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All Journal JOISIE (Journal Of Information Systems And Informatics Engineering) Indonesian Journal of Education And Computer Science Jurnal Testing dan Implementasi Sistem Informasi CSRID
Muhammad Siddik
Institut Bisnis dan Teknologi Pelita Indonesia
Computer Science & IT Education

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Journal : csrid

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Pengembangan Sistem Pendukung Keputusan Pemilihan Siswa Berprestasi Berbasis Multi-Kriteria Menggunakan Metode Simple Additive Weighting (SAW) pada Sekolah Menengah Kejuruan Samsir; Maisarah Ritonga; Muhammad Siddik
CSRID (Computer Science Research and Its Development Journal) Vol. 18 No. 2 (2026): Juni 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.18.2.2026.205-217

Abstract

The selection process of outstanding students in Vocational High Schools (SMK) often suffers from subjectivity and inefficiency due to manual assessment procedures. This study aims to develop a web-based Decision Support System (DSS) using the Simple Additive Weighting (SAW) method to determine outstanding students more objectively. The system integrates three achievement categories—academic, professional, and sports achievements—represented by nine evaluation indicators with different weights according to their importance. The SAW method was applied through decision matrix construction, normalization, weighting, and preference value calculation. The results show that the best alternative obtained a preference value of 6.77 and was recommended as the outstanding student. Black Box testing indicated that all system functions operated successfully with a 100% success rate. Furthermore, the system reduced the selection process time from 40 minutes to 8 minutes, representing an 80% efficiency improvement compared with the manual process. These findings demonstrate that the implementation of the SAW method effectively improves objectivity, transparency, and efficiency in the outstanding student selection process in vocational high schools.
Sistem Pakar Deteksi Penyakit THT Menggunakan Metode SAW Samsir; Muhammad siddik; Azrai Sirait
CSRID (Computer Science Research and Its Development Journal) Vol. 18 No. 2 (2026): Juni 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.18.2.2026.409-425

Abstract

Ear, Nose, and Throat (ENT) disorders are common health issues that require timely intervention from the early stages to prevent complications. However, a shortage of ENT specialists and the unequal distribution of healthcare services hinder optimal consultation and initial diagnosis, particularly in areas with limited access to healthcare. While various studies have developed disease diagnosis systems using inference methods—such as Forward Chaining and Certainty Factor—the application of the Simple Additive Weighting (SAW) method as a Multi-Criteria Decision Making (MCDM) approach to rank potential diseases based on symptom combinations remains relatively limited. This study aims to develop a web-based expert system for the initial diagnosis of ENT disorders by utilizing a knowledge base derived from ENT specialists and implementing the SAW method as a decision-making mechanism to identify the most likely disease (the alternative with the highest preference value). The knowledge base is represented through relationships between symptoms, diseases, symptom weights, and management guidelines. The diagnostic process involves constructing a decision matrix, normalizing values, weighting symptoms, and calculating preference values ​​using the SAW method. Developed using PHP and MySQL, the system provides initial diagnostic recommendations and management advice based on user-selected symptoms. This research contributes by applying the SAW method as a multi-criteria decision-making mechanism within an ENT diagnosis system, thereby making the process of identifying potential diseases more systematic, transparent, and adaptable to changes in the knowledge base
Co-Authors Alyauma Hajjah Azrai Sirait Deny Jollyta Desnelita, Yenny Fahruzi Sirait Gusrianty Gusrianty Gustientiedina Johan Johan Juan Veron Wie Lita Lita Maisarah Ritonga Samsir Zulkifli