Analisis Pemain Terbaik Sepak Bola dengan menggunakan Algoritma K-Means

Authors

  • Faviola Proba Wardhana Program Studi Teknik Informatika, Universitas Dian Nuswantoro
  • Sri Winarno Program Studi Teknik Informatika, Universitas Dian Nuswantoro

DOI:

https://doi.org/10.29408/edumatic.v8i2.27105

Keywords:

football player, k-means algorithm, performance

Abstract

The selection of players in soccer is crucial for developing strategies in matches. It serves as a decision support system that can be used to choose the starting line-up. The data for this research was obtained from the official and reliable website of Liga 1 Indonesia for the 2023 season. This study aims to analyze the top soccer players using the K-means algorithm based on their statistical performance throughout the 2023 Liga 1 Indonesia season. Data collection for each player included their percentage of appearances in the starting line-up. We used the K-means algorithm, which helps identify patterns and cluster players based on statistical metrics from the matches, such as the number of goals, assists, and other physical statistics across various player positions. The data comprised 197 players competing in Liga 1 2023. Our findings reveal that 62 players belong to Cluster 1 out of the total 197 analyzed. These players exhibited the best statistics and could be potential options for Liga 1 coaching staff to recruit or sign in order to strengthen their teams for the next season. Our research indicates that the players in this cluster demonstrated outstanding performance, helping coaches identify categories such as "efficient strikers" or "strong defenders." Therefore, this study can assist coaches or managers in selecting the most suitable players to meet the team’s needs for the upcoming season.

References

Andiani, D., Dwi, S., Septiani, R., & Riana, A. (2022). Analisis Teknik non-Hierarki untuk Pengelompokan Kabupaten/Kota di Provinsi Jawa Barat Berdasarkan Indikator Kesejahteraan Rakyat 2020. Jurnal Riset Matematika Dan Sains Terapan, 21(1), 21–28.

Ashari, I. A., Negara, I. S. M., & Sumantri, R. B. B. (2022). Evaluasi Pembayaran Keuangan Siswa berdasarkan Penghasilan Wali Siswa menggunakan Metode Clustering K-Means. Edumatic: Jurnal Pendidikan Informatika, 6(2), 324-333. https://doi.org/10.29408/edumatic.v6i2.6395

Augusto, D., Brito, J., Aquino, R., Paulucio, D., Figueiredo, P., Bedo, B. L. S., ... & Vasconcellos, F. (2022). Contextual variables affect peak running performance in elite soccer players: A brief report. Frontiers in Sports and Active Living, 4, 966146. https://doi.org/10.3389/fspor.2022.966146

Fitri, E. N., Winarno, S., Budiman, F., Rohmani, A., Zeniarja, J., & Sugiarto, E. (2023). Decision Tree Simplification Through Feature Selection Approach in Selecting Fish Feed Sellers. Jurnal Teknik Informatika (Jutif), 4(2), 301-309. https://doi.org/10.52436/1.jutif.2023.4.2.747

García, J., & Sanchis, E. (2020). Applying Machine Learning Algorithms to Assess Player Performance in Soccer. International Journal of Sports Science and Coaching, 15(3), 459-471.

García-Aliaga, A., Marquina, M., Coteron, J., Rodríguez-González, A., & Luengo-Sanchez, S. (2021). In-game behaviour analysis of football players using machine learning techniques based on player statistics. International Journal of Sports Science & Coaching, 16(1), 148-157. https://doi.org/10.1177/1747954120959762

Gosari, N. C., & Rismayani, R. (2023). Penerapan Data Mining Dalam Mengelompokkan Kunjungan Wisatawan Mancanegara Di Prov. Sulawesi Selatan Dengan K-Means Dan SVM. Jurnal Informatika: Jurnal Pengembangan IT, 8(3), 174-180. https://doi.org/10.30591/jpit.v8i3.4554

Hafiz, M., Rahman, T., & Susanto, D. (2024). Klasterisasi penyakit menular di Indonesia menggunakan metode K-Means Clustering. Journal of Computer, 4(1), 50-57. https://doi.org/10.33330/j-com.v4i1.3033

Harahap, L. M., Siregar, T., & Gultom, F. (2022). Klastering sayuran unggulan menggunakan algoritma K-Means. Jurnal Teknik Informatika dan Sistem Informasi, 8(3),567-579. https://doi.org/10.28932/jutisi.v8i3.5277

Kaukab, M. E. (2022). Football Player Market Value: Apakah Usia Pemain Berperan Dalam Penentuan Harga Pasar?. Jurnal Penelitian Dan Pengabdian Kepada Masyarakat UNSIQ, 9(1), 24-37. https://doi.org/10.32699/ppkm.v9i1.2208

Martanto, M., & Hayati, U. (2024). Pengelompokan Transaksi Penjualan Aksesoris Hp Dan Pulsa Dengan Metode K-Means Untuk Meningkatkan Strategi Pemasaran Di Toko Bagus Celluler. JATI (Jurnal Mahasiswa Teknik Informatika), 8(3), 2838-2849. https://doi.org/10.36040/jati.v8i3.9559

Mulyadi, T. A., & Purnomo, D. (2023). Optimasi Pelayanan Kapal Penumpang melalui Clustering Penumpang dengan Metode Silhouette Coefficient. Edumatic: Jurnal Pendidikan Informatika, 7(2), 217-226. https://doi.org/10.29408/edumatic.v7i2.21067

Nugraha, H. S., Mutaqin, H., Fathah, A., & Juliane, C. (2023). Mengidentifikasi Strategi Promosi pada Jasa Penjualan Saldo Digital menggunakan Pendekatan Clustering. Edumatic: Jurnal Pendidikan Informatika, 7(1), 11-19. https://doi.org/10.29408/edumatic.v7i1.7385

Nurzahputra, A., Pranata, A. R., & Puwinarko, A. (2017). Decision Support System for Football Players Lineup Selection using Fuzzy Multiple Attribute Decision Making and K-Means Clustering Methods. Jurnal Teknologi Dan Sistem Komputer, 5(3), 106–109. https://doi.org/10.14710/jtsiskom.5.3.2017.106-109.

Qirom, D. S., Faqih, A., & Dwilestari, G. (2024). Implementasi Algoritma K-Means Untuk Klasterisasi Pasien Hipertensi Bersadarkan Karakteristik Pasien. JATI (Jurnal Mahasiswa Teknik Informatika), 8(2), 2056-2063. https://doi.org/10.36040/jati.v8i2.8314

Rahman, F. D., Mulki, M. I. Z., & Taryana, A. (2024). Clustering dan klasifikasi data cuaca Cilacap dengan menggunakan metode K-Means dan Random Forest. Jurnal SINTA: Sistem Informasi dan Teknologi Komputasi, 1(2), 90-97. https://doi.org/10.61124/sinta.v1i2.15

Salam, A., Adiatma, D., & Zeniarja, J. (2020). Implementasi Algoritma K-Means Dalam Pengklasteran untuk Rekomendasi Penerima Beasiswa PPA di UDINUS. JOINS 5(1), 62–68. https://doi.org/10.33633/joins.v5i1.3350

Shelly, Z., Burch, R. F., Tian, W., Strawderman, L., Piroli, A., & Bichey, C. (2020). Using K-means clustering to create training groups for elite American football student-athletes based on game demands. International Journal of Kinesiology and Sports Science, 8(2), 47-63. https://doi.org/10.7575//aiac.ijkss.v.8n.2p.47

Sulastri, H., Mubarok, H., & Iasha, S. S. (2021). Implementasi Algoritma Machine Learning Untuk Penentuan Cluster Status Gizi Balita. Jurnal Rekayasa Teknologi Informasi (JURTI), 5(2), 184-191. https://doi.org/10.30872/jurti.v5i2.6779

Wadanur, A., & Sari, A. A. (2022). Implementasi Algoritma Apriori dan FP-Growth pada Penjualan Spareparts. Edumatic: Jurnal Pendidikan Informatika, 6(1), 107-115. https://doi.org/10.29408/edumatic.v6i1.5470

Downloads

Published

2024-12-19

Issue

Vol. 8 No. 2 (2024): Edumatic: Jurnal Pendidikan Informatika

Section

Articles

License

Copyright (c) 2024 Faviola Proba Wardhana, Sri Winarno

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Semua tulisan pada jurnal ini adalah tanggung jawab penuh penulis. Edumatic: Jurnal Pendidikan Informatika bisa diakses secara free (gratis) tanpa ada pungutan biaya, sesuai dengan lisensi creative commons yang digunakan.

Lisensi Creative Commons
This work is licensed under a Lisensi a Creative Commons Attribution-ShareAlike 4.0 International License.