📅 30 December 2023
DOI: 10.61132/manufaktur.v2i2.359
Klasifikasi Algoritma Support Vector Machine (SVM) untuk Memprediksi Persebaya Suarabaya Juara BRI Liga 1
Manufaktur: Publikasi Sub Rumpun Ilmu Keteknikan Industri
Asosiasi Riset Ilmu Teknik Indonesia (ARITEKIN)
📄 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.
🔖 Keywords
#Clustering; Support Vector Machine; Orange
ℹ️ Informasi Publikasi
Tanggal Publikasi
30 December 2023
Volume / Nomor / Tahun
Volume 1, Nomor 4, Tahun 2023
📝 HOW TO CITE
Wahyu Kurniawan; Dwi Sukma Donoriyanto, "Klasifikasi Algoritma Support Vector Machine (SVM) untuk Memprediksi Persebaya Suarabaya Juara BRI Liga 1," Manufaktur: Publikasi Sub Rumpun Ilmu Keteknikan Industri, vol. 1, no. 4, Dec. 2023.
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