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All Journal JoDENS: Journal of Digital Ecosystem for Natural Sustainability
Itan, Vincent
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Computer Science & IT Decision Sciences, Operations Research & Management

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Implementasi Support Vector Machine untuk Klasifikasi Kasus Monkeypox: Pendekatan Oversampling dan Undersampling untuk Mengatasi Ketidakseimbangan Kelas Cindy; Sabatini, Tiffany; Itan, Vincent
Journal of Digital Ecosystem for Natural Sustainability Vol 4 No 1 (2024): Juli 2024
Publisher : Fakultas Komputer - Universitas Universal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63643/jodens.v4i1.234

Abstract

Monkeypox is an infectious disease caused by the monkeypox virus. This study applies the Support Vector Machine (SVM) method to classify monkeypox cases. Utilizing SVM aids in accurate diagnosis and prevention measures. Preprocessing involves Random Oversampling (ROS) and Random Undersampling (RUS) to address class imbalance in symptom datasets. SVM classification is based on systemic symptoms and clinical signs. Evaluation via Confusion Matrix assesses accuracy, sensitivity, specificity, and AUC, with average accuracy reaching 67.1% for imbalanced data and 36.5% for balanced data. The method outperforms conventional techniques, demonstrating its potential in monkeypox symptom pattern recognition. Results indicate higher accuracy in diagnosing monkeypox using SVM, despite class imbalances. This study contributes to understanding, predicting, and managing monkeypox outbreaks effectively.
Sistem Pendukung Keputusan Pemilihan Pengajar Les untuk Siswa Lembaga Bimbingan Belajar Dengan Metode Simple Additive Weight Felix, Kendrick; Mettalia, Maitriyana; Sabatini, Tiffany; Itan, Vincent
Journal of Digital Ecosystem for Natural Sustainability Vol 4 No 2 (2024): Desember 2024
Publisher : Fakultas Komputer - Universitas Universal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63643/jodens.v4i2.253

Abstract

The goal of education is to help students develop their potential for personal, societal, and national benefits through an organized learning process between teachers and students. Through one-on-one or group tutoring sessions, tutoring centers are essential in helping students overcome scholastic obstacles and advance their abilities. Nevertheless, a lot of tutoring facilities, including "Let's Shine," continue to use manual scheduling techniques, sometimes with Excel, which results in inefficiencies and frequent changes. In order to improve tutor scheduling, this study suggests using the Simple Additive Weighting (SAW) method, which gives priority to factors such tutor status, subject type, time, day, number of students, and difficulty level. Management interviews and observation were used in the data collection process. The SAW method streamlines scheduling with an objective, data-driven approach that should increase productivity and decrease revisions.
Co-Authors Cindy Felix, Kendrick Mettalia, Maitriyana Sabatini, Tiffany