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All Journal Manufaktur: Publikasi Sub Rumpun Ilmu Keteknikan Industri
Wahyu Kurniawan
Universitas Pembangunan Nasional Veteran Jawa Timur
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering

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Klasifikasi Algoritma Support Vector Machine (SVM) Untuk Memprediksi Persebaya Suarabaya Juara BRI Liga 1 Wahyu Kurniawan; Dwi Sukma Donoriyanto
Manufaktur: Publikasi Sub Rumpun Ilmu Keteknikan Industri Vol. 2 No. 2 (2024): Juni : Manufaktur: Publikasi Sub Rumpun Ilmu Keteknikan Industri
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/manufaktur.v2i2.359

Abstract

This research uses the Support Vector Machine (SVM) algorithm to predict Persebaya Surabaya's ranking in BRI Liga 1. The data used includes goals scored, goals given away, total end-of-season points, and status as champions. The results of the analysis using Orange software show that Persebaya Surabaya does not necessarily become a champion if it has a point value of 42 and an SVM value of 41. To become a champion, Persebaya Surabaya must score 69 points or more in a season and achieve an average of more than 54 goals per season. The suggestion of this research is to have more data so that the results of data processing using Orange software are more optimal and accuracy is more precise.
Co-Authors Dwi Sukma Donoriyanto