Penerapan Metode Random Forets dan Decision Tree Dalam Sistem Pendukung Keputusan Smartphone Gaming di bawah Harga Lima Juta
DOI:
https://doi.org/10.47065/bulletincsr.v6i5.1172Keywords:
Decision Support System (DSS); Smartphone Gaming; Decision Tree; Random Forets; ClassificationAbstract
The rapid advancement of gaming smartphone technology within an affordable price range (under five million rupiah) often makes it difficult for users to select a device that suits their specific needs and budget. This study aims to develop a Decision Support System (DSS) for classifying and recommending gaming smartphones based on criteria such as chipset, RAM, ROM, battery capacity, screen size, and price. The methodology employed is Knowledge Discovery in Databases (KDD), encompassing selection, cleaning, transformation, data mining, and evaluation. The classification process compares the performance of the Decision Tree and Random Forest algorithms. Testing results indicate that the Random Forest algorithm achieves an accuracy of 100%, outperforming the alternative. The system proves effective and accurate in providing optimal gaming smartphone recommendations. The study's primary contribution is the development of a hardware performance classification model integrated into an interactive web ecosystem, offering consumers a practical solution to translate technical specifications into specific device recommendations
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References
A. F. Mu’afi, M. G. Rohman, and M. R. Zamroni, “Implementation of the SAW Method for Mobile Phone Selection Recommendations at Holida Seluler Store,” Gener. J., vol. 10, no. 1, pp. 1–11, 2026, doi: 10.29407/gj.v10i1.26505.
Y. Diana, F. Hadi, S. N. Rahman, and F. Yenila, “Peningkatan Literasi Produk dalam Pembelian Handphone melalui Sistem Rekomendasi Berbasis Algoritma C4.5,” J. Ekon. Dan Bisnis, vol. 5, no. 4, pp. 818–823, 2025, doi: 10.47233/jebs.v5i4.3224.
A. N. Febriyanto, “Sistem Rekomendasi Pemilihan Laptop Menggunakan Metode Knowledge Based (Studi Kasus Rizky Comp),” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 12, no. 2, 2025, doi: 10.35957/jatisi.v12i2.10885.
S. Kali and A. S. Purnomo, “Sistem pendukung keputusan untuk memprediksi kualitas dengan metode analytical hierarchy process (ahp),” JATI (Jurnal Mhs. Tek. Inform., vol. 8, no. 2, pp. 1688–1695, 2024, doi: 10.36040/jati.v8i2.9150.
M. Juna Edi and Aryanto, “Implementasi XGBoost untuk Rekomendasi Smartphone Menggunakan Content-Based Filtering,” STATMAT J. Stat. dan Mat., vol. 7, no. 2, pp. 274–278, 2025, doi: 10.32493/sm.v7i2.49850.
I. Michael Siregar and L. W. Budi Putri, “Analisis Variasi Implementasi Algoritma Analytical Hierarchy Process (AHP) Dalam Menentukan Prioritas Produk Kalibrasi,” J. Nas. Teknol. dan Sist. Inf., vol. 10, no. 1, pp. 54–63, 2024, doi: 10.25077/teknosi.v10i1.2024.54-63.
H. A. Setyadi, G. S. Nurohim, and W. Nugroho, “Penentuan Kelayakan dan Jenis Lembaga Keuangan dalam Pemberian Modal UMKM Menggunakan Metode AHP dan Decision Tree,” J. Ilm. FIFO, vol. 16, no. 1, p. 64, 2024, doi: 10.22441/fifo.2024.v16i1.007.
?. ?. ????????? and ?. ?. ?????????, “??????????????? ????????? ??????, ???????? ?????? 2 ???? ? ??????? ?12,” ??????????, ??????? ?? ?????????? ??????? ? ?????? ?????, vol. 5, no. April, pp. 321–331, 2026, doi: 10.32447/bcet.2026.17.
J. Lemantara, “Penerapan Metode Weighted Product Pada Aplikasi Pemilihan Smartphone Berdasarkan Budget dan Kebutuhan,” Techno.COM, 2023. https://www.phonecurry.com/benchmarks
Putri Ayu Firnanda, Litasya Shofwatillah, Fauziah Rahma, and Fatkhurokhman Fauzi, “Analisis Perbandingan Decision Tree dan Random Forest dalam Klasifikasi Penjualan Produk pada Supermarket,” Emerg. Stat. Data Sci. J., vol. 3, no. 1, pp. 445–461, 2025, doi: 10.20885/esds.vol3.iss.1.art2.
N. Maulana and Supatman, “Sistem Pendukung Keputusan Pemilihan Smartphone Android Bekas Menggunakan Metode ELECTRE Berbasis Web,” J. Komputer, Inf. dan Teknol., vol. 5, no. 1, p. 12, 2025, doi: 10.53697/jkomitek.v5i1.2174.
S. N. Rakhmah and R. A. R. Yusuf, “Sistem Pendukung Keputusan Pemilihan Smartphone Gaming Android Terbaik Dengan Metode Weighted Product,” Reputasi J. Rekayasa Perangkat Lunak, vol. 3, no. 1, pp. 12–18, 2022, doi: 10.31294/reputasi.v3i1.1201.
Elisa Tri Ammah A’Fena, Aidina Ristyawan, and Arie Nugroho, “Pengaruh Normalisasi Fitur Pada Perbandingan Algoritma Random Forest Regressor Dan KNN Regressor Dalam Menentukan Harga Smartphone,” KRESNA J. Ris. dan Pengabdi. Masy., vol. 5, no. 1, pp. 74–83, 2025, doi: 10.36080/kresna.v5i1.226.
P. Satya Saputra, I. Putu Gede Abdi Sudiatmika, J. Akuntansi, P. Negeri Bali, and P. Korespondensi, “Analisis Prediksi Harga Smartphone Tahun 2023 Menggunakan Model Random Forest Regression Berdasarkan Fitur-Fitur Spesifikasi Teknis,” J. Komput. dan Teknol. Sains, vol. 3, no. 2, pp. 13–17, 2024, doi: 10.37637/komteks.v3i2.2233
T. Masringgit Marwiyah Nst, “KAJIAN ENTROPI SEBAGAI PARAMETER KETAKTERATURAN DALAM SISTEM FISIKA,” Journal of Maritime and Education (JME)., vol. 8, no. 1, pp. 62–66, 2026, doi: https://doi.org/10.54196/jme.v8i1.228
A. Tangkelayuk, “The Klasifikasi Kualitas Air Menggunakan Metode KNN, Naïve Bayes, dan Decision Tree,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 9, no. 2, pp. 1109–1119, 2022, doi: 10.35957/jatisi.v9i2.2048.
N. N. Amrutkar, “Data pre-processing in machine learning?: A Research Perspective,” International Journal of Scientific and Research Publications., vol. 16, no. 2, pp. 106–109, 2026, doi: 10.29322/IJSRP.16.02.2026.p17014.
A. D. Purwanto, A. Ibrahim, A. Ulfa, E. Parwati, and A. Supriyono, “Pengembangan Model Identifikasi Habitat Bentik Menggunakan Pendekatan Segmentasi Object-Based Image Analysis (OBIA) dan Algoritma Machine Learning (Studi Kasus: Pulau Pari, Kepulauan Seribu),” J. Kelaut. Nas., vol. 17, no. 2, p. 131, 2022, doi: 10.15578/jkn.v17i2.10377.
H. W. Raff and F. Ratnawati, “Klasifikasi Sentimen Ulasan Pengguna terhadap Aplikasi Video Editing Play Store Menggunakan Random Forest,” Techno.Com, vol. 24, no. 3, pp. 646–657, 2025, doi: 10.62411/tc.v24i3.12873.
H. Tantyoko, D. K. Sari, and A. R. Wijaya, “Prediksi Potensial Gempa Bumi Indonesia Menggunakan Metode Random Forest Dan Feature Selection,” IDEALIS Indones. J. Inf. Syst., vol. 6, no. 2, pp. 83–89, 2023, doi: 10.36080/idealis.v6i2.3036.
A. R. Pratama, R. R. Aryanto, and A. T. M. Pratama, “Model Klasifikasi Calon Mahasiswa Baru Untuk Sistem Rekomendasi Program Studi Sarjana Berbasis Machine Learning,” J. Teknol. Inf. dan Ilmu Komput., vol. 9, no. 4, pp. 725–734, 2022, doi: 10.25126/jtiik.2022934311.
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