Klasifikasi Algoritma Support Vector Machine (SVM) Untuk Memprediksi Persebaya Suarabaya Juara BRI Liga 1
DOI:
https://doi.org/10.61132/manufaktur.v2i2.359Keywords:
Clustering, Support Vector Machine, OrangeAbstract
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.
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