Utilization of MLP and LSTM Methods in Hero Selection Recommendations for the Game of Mobile Legends: Bang Bang
DOI:
https://doi.org/10.34148/teknika.v14i1.1201Keywords:
Deep Learning, Multi Layer Perceptron, Long Short-Term Memory, Mobile Legends, Draft Pick RecommendationAbstract
Mobile Legends is one of the popular MOBA games played in real-time. The game begins with each player selecting one hero in the draft pick phase. Choosing the right hero is very important because it can affect the chances of winning. This study uses datasets from rank mode matches conducted by streamers, top global heroes, and top leaderboards in Indonesia to compare the accuracy of the MLP and LSTM methods in recommending the fifth hero for one's team. The Concatenate Layer is used in model development. Modifying the dataset was also done by reducing the number of target classes and performing data augmentation to increase data variation. The results show that LSTM excels in top-1 recommendations with an accuracy of up to 59%. Meanwhile, MLP outperforms in top-3 and top-5 recommendations, indicating that this model is more flexible in providing multiple hero alternatives. The conclusion is that players can use the LSTM method if they only want to select the best single hero. However, if players prefer a broader range of hero recommendations, the MLP method is more suitable.
Downloads
References
[1] A. T. Khomeiny and P. W. Aji, “DOTA 2, League of Legends, dan Paladins: Popularitas Game MOBA di Indonesia,” Buletin Sistem Informasi dan Teknologi Islam, vol. 1, no. 3, pp. 139–144, 2020, [Online]. Available: https://trends.google.com,
[2] L. Zhang, C. Xu, Y. Gao, Y. Han, X. Du, and Z. Tian, “Improved Dota2 Lineup Recommendation Model Based on a Bidirectional LSTM,” Tsinghua Sci Technol, vol. 25, no. 6, 2020.
[3] T. Inzitari, B. Lyons, and M. N. Al Islam, “Predicting pick-ban sequence in League of Legends games,” Association for Computing Machinery, Apr. 2022, doi: 10.1145/1122445.1122456.
[4] R. L. Zhu, J. Wang, and S. J. Zhao, “Categorical Learning-based Line-up Prediction in the Drafting Process of MOBA Games,” Journal of Internet Technology, vol. 24, no. 2, pp. 411–419, Mar. 2023, doi: 10.53106/160792642023032402019.
[5] M. B. Firdaus, E. Budiman, and M. F. Anshori, “Evaluasi Skema Panduan Game Berbasis Motion Graphic Animation Pada Esports Bergenre Multiplayer Online Battle Arena,” JURTI, vol. 4, no. 1, 2020.
[6] E. Fahrezi, S. Putra, B. Purwandari, I. Eitiveni, and M. Purwaningsih, “Faktor Pendorong Keputusan Pembelian Virtual Item Pada Mobile Commerce (Studi Kasus: Game Mobile Legends) Drivers of Decision to Purchase Virtual Items in Mobile Commerce (Case Study: Mobile Legends Game),” Research : Journal of Computer, vol. 5, no. 1, pp. 1–16, 2022.
[7] Irwanto I, “Pola Komunikasi Antar Gamers Pada Fitur Chat (IN-GAME) Studi Fenomenologi Pemain Game Online Mobile Legends di Bandung,” Jurnal Pendidikan Tambusai, 2023.
[8] M. Rizky and S. Dewata, “Penggunaan Bahasa Arab Pada Game Mobile Legends,” Seminar Nasional Bahasa Arab Mahasiswa V Tahun 2021 HMJ Sastra Arab Fakultas Sastra Universitas Negeri Malang, 2021.
[9] S. M. Listijo, T. Purwani, S. T. Galih, and T. Hafidzin, “Prediksi Kemenangan dan Susunan Tim pada Game Mobile Legends Bang Bang Menggunakan Algoritma Naive Bayes,” Jurnal KOMPUTAKI, vol. 50173, 2020.
[10] M. Riziq sirfatullah Alfarizi, M. Zidan Al-farish, M. Taufiqurrahman, G. Ardiansah, and M. Elgar, “Penggunaan Python Sebagai Bahasa Pemrograman Untuk Machine Learning dan Deep Learning,” 2023.
[11] A. Raup, W. Ridwan, Y. Khoeriyah, Q. Yuliati Zaqiah, and U. Islam Negeri Sunan Gunung Djati Bandung, “Deep Learning dan Penerapannya dalam Pembelajaran,” JIIP (Jurnal Ilmiah Ilmu Pendidikan), 2022, [Online]. Available: http://Jiip.stkipyapisdompu.ac.id
[12] I. Ilhamsyah, A. Y. Rahman, and I. Istiadi, “Klasifikasi Kualitas Biji Kopi Menggunakan MultilayerPerceptron Berbasis Fitur Warna LCH,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 5, no. 6, pp. 1008–1017, Dec. 2021, doi: 10.29207/resti.v5i6.3438.
[13] M. R. Firmansyah, R. Ilyas, and F. Kasyidi, “Klasifikasi Kalimat Ilmiah Menggunakan Recurrent Neural Network,” Prosiding The 11 th Industrial Research Workshop and National Seminar Bandung, 2020, pp. 26–27.
[14] M. D. Rhman, A. Djunaidy, and F. Mahananto, “Penerapan Weighted Word Embedding pada Pengklasifikasian Teks Berbasis Recurrent Neural Network untuk Layanan Pengaduan Perusahaan Transportasi,” Jurnal Sains dan Seni ITS, vol. 10, 2021.
[15] K. M. Nguyen-Duy, Q. Pham, and T. B. Nguyen, “Adaptive-Saturated RNN: Remember More With Less Instability,” ICLR, 2023.
[16] D. R. Alghifari, M. Edi, and L. Firmansyah, “Implementasi Bidirectional LSTM untuk Analisis Sentimen Terhadap Layanan Grab Indonesia,” Jurnal Manajemen Informatika (JAMIKA), vol. 12, no. 2, pp. 89–99, Sep. 2022, doi: 10.34010/jamika.v12i2.7764.
[17] A. Rahman et al., “Forecasting Zoonose Disease Infection and Death Trolls Using Long Short-Term Memory,” Elsevier, 2023, doi: 10.13140/RG.2.2.35565.97763/1.
[18] S. Norindah Sari, M. Reza Faisal, D. Kartini, I. Budiman, and T. Hamonangan Saragih, “Perbandingan Ekstraksi Fitur dengan Pembobotan Supervised dan Unsupervised pada Algoritma Random Forest untuk Pemantauan Laporan Penderita COVID-19 di Twitter,” Jurnal Komputasi, vol. 11, no. 1, 2023.
[19] Ismail and R. E. Syah, “Klasifikasi Data Mining Pada Tingkat Kepuasan Pengunjung Maccahaya Waterboom dengan Algoritma C.45,” Jurnal Ilmiah Sistem Informasi dan Teknik Informatika (JISTI), vol. 7, no. 2, 2024.
[20] N. Agustina Purwitasari, M. Soleh, J. Raya Puspiptek, and K. Tangerang Selatan, “Implementasi Algoritma Artificial Neural Network Dalam Pembuatan Chatbot Menggunakan Pendekatan Natural Language Processing,” Jurnal IPTEK, 2022.
[21] I. A. DLY, J. Jasril, S. Sanjaya, L. Handayani, and F. Yanto, “Klasifikasi Citra Daging Sapi dan Babi Menggunakan CNN Alexnet dan Augmentasi Data,” Journal of Information System Research (JOSH), vol. 4, no. 4, pp. 1176–1185, Jul. 2023, doi: 10.47065/josh.v4i4.3702.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Teknika
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
