ANALISIS KLASIFIKASI ALGORITMA C.45 DALAM MEMPREDIKSI TINGKAT PENJUALAN PERLENGKAPAN IBADAH
DOI:
https://doi.org/10.33884/comasiejournal.v11i1.8987Keywords:
Datamining, Prediction, C4.5 Algorithm, Weka, SalesAbstract
This research was conducted at a shop that sells goods or equipment for Buddhist worship called the Sinar Mas Indah shop. The Sinar Mas Indah shop operates every day except major holidays such as Chinese New Year. So far, the Sinar Mas Indah store has never used sales transaction data for analysis for the benefit of future business progress, sales transaction data is only stored in archive form, if it is old and feels no longer needed, it will simply be thrown away. , if used to predict future sales then decisions to increase sales in the future can be easily achieved. This research utilized datamining techniques with the C4.5 algorithm by testing the results using Weka software, from the 5 variables tested, category, brand, quantity, quality and price with a total of 160 test data. After calculating the entropy and gain values, the highest gain value was obtained. making consideration of consumer purchasing factors, namely Price, Quality, Quantity and category, into the main factors in decision making and there are results for Correctly Classified Instances 109 Data with a percentage value of 68.125% then for Incorrectly Classified Instances 51 data with a percentage value of 31.875%.
References
Adriansa, M., Yulianti, L., & Elfianty, L. (2022). Analisis Kepuasan Pelanggan Menggunakan Algoritma C4.5. Jurnal Teknik Informatika UNIKA Santo Thomas, 07(21), 115–121. https://doi.org/10.54367/jtiust.v7i1.1983
Amrin, A., & Pahlevi, O. (2021). Data Mining Optimization Based on Particle Swarm Optimization For Diagnosis of Inflammatory Liver Disease. Journal of Informatics and Telecommunication Engineering, 5(1), 152–159. https://doi.org/10.31289/jite.v5i1.5312
Arif, A., & Yulianto, A. (2022). Klasifikasi Penjualan Makanan Hewan Peliharaan di Muezza Petshop01 Bogor Menggunakan Metode Algoritma C4.5. Remik, 6(4), 840–854. https://doi.org/10.33395/remik.v6i4.11859
Baginda, B. (2023). Implementasi Data Mining Dalam Pemilihan Laptop Berbasis Algoritma C4.5 Pada Software WEKA. Jurnal Minfo Polgan, 12(1), 1065–1073. https://doi.org/10.33395/jmp.v12i1.12582
Darmawan, E. (2018). C4.5 Algorithm Application for Prediction of Self Candidate New Students in Higher Education. Jurnal Online Informatika, 3(1), 22. https://doi.org/10.15575/join.v3i1.171
Diansyah, T. M., & Exprada, Y. (2022). Penerapan Algoritma C4.5 Untuk Memprediksi Penjualan Lele Pada Kolam Pancing Galatama. Jurnal Sistem Komputer Dan Informatika (JSON), 3(4), 567. https://doi.org/10.30865/json.v3i4.4264
Elisa, E. (2022). Penerapan Algoritma C4.5 Untuk Memprediksi Penjualan Barang Pada Pt Batam Bangun Prathama. Jurnal Comasie, 7(1), 127–133.
Iftitah, A., & Setyadi, R. (2023). Penerapan Algoritma C.45 Untuk Analisis Pengadaan Peralatan dan Mesin Kantor. Journal of Information System Research (JOSH), 4(2), 434–442. https://doi.org/10.47065/josh.v4i2.2673
Julianto, I. T., Kurniadi, D., Nashrulloh, M. R., & Mulyani, A. (2022). Comparison of Data Mining Algorithm For Forecasting Bitccoin Crypto Currency Trends. Jurnal Teknik Informatika (Jutif), 3(2), 245–248. https://doi.org/10.20884/1.jutif.2022.3.2.194
Mulyanda, S., Defit, S., & Sumijan. (2023). Analisis Data Mining Menggunakan Algoritma C4.5 Untuk Prediksi Harga Pasar Mobil Bekas. Jurnal KomtekInfo, 10, 116–121. https://doi.org/10.35134/komtekinfo.v10i3.427
Rusdiansyah, R., Supendar, H., Suharyanti, N., & Tuslaela, T. (2022). Data Mining implementation on SMUN Scholarship recipient candidates using the C4.5 algorithm. Sinkron, 7(4), 2208–2213. https://doi.org/10.33395/sinkron.v7i4.11767
Salsabilla, T., & Sulastri, S. (2022). Implementasi Algoritma C4.5 Untuk Klasifikasi Produk Laris Sepeda Motor Honda Pada Cv Cendana Motor Cepiring. Rabit : Jurnal Teknologi Dan Sistem Informasi Univrab, 7(2), 164–171. https://doi.org/10.36341/rabit.v7i2.2489
Sulastri, R. (2022). Identifikasi Tingkat Penjualan Produk Herbal HWI Menggunakan Algoritma C4.5. Jurnal Informatika Ekonomi Bisnis, 4(3), 84–89. https://doi.org/10.37034/infeb.v4i3.141
Surahmat, A. (2023). Rancang Bangun Aplikasi Sistem Penjualan Pada Percetakan Cubic Art. JATI (Jurnal Mahasiswa Teknik Informatika), 7(1), 81–86. https://doi.org/10.36040/jati.v7i1.6064
Tanyu, B. F., Abbaspour, A., Alimohammadlou, Y., & Tecuci, G. (2021). Landslide susceptibility analyses using Random Forest, C4.5, and C5.0 with balanced and unbalanced datasets. Catena, 203(April), 105355. https://doi.org/10.1016/j.catena.2021.105355
Wahono, H., & Riana, D. (2020). Prediksi Calon Pendonor Darah Potensial Dengan Algoritma Naïve Bayes, K-Nearest Neighbors dan Decision Tree C4.5. JURIKOM (Jurnal Riset Komputer), 7(1), 7. https://doi.org/10.30865/jurikom.v7i1.1953
Wijaya, A., & Mutatkin Bakti, A. (2023). Implementasi Data Mining Menggunakan Algoritma C4.5 Untuk Memprediksi Penjualan Alat – Alat Telekomunikasi Dan IT (Information Technology) Pada PT Julian Adiputra Utama. Jupiter, 15, 597–606.
Yusuf Maulana, Riki Winanjaya, & Fitri Rizki. (2022). Penerapan Data Mining dengan Algoritma C.45 Dalam Memprediksi Penjualan Tempe. Bulletin of Computer Science Research, 2(2), 53–58. https://doi.org/10.47065/bulletincsr.v2i2.163
