Analisis Prediksi Penjualan Lampu Dengan Metode Svm Pada PT. Terang Abadi Raya
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Predictive analytics is a type of data analysis technique used to make predictions about future events. In the Forecasting analysis of companies that buy and sell goods, it is necessary to facilitate the company's sales planning. In this study, an analysis of the Lamp Sales Forecast was carried out at PT. Great Eternal Light. Purpose The purpose of this study is to analyze the 2022 lamp sales forecast using the Support Vector Machine method. The results of the evaluation are carried out using the MAPE method to find out how much capacity the model has used to see the difference between the predicted and actual values. Haili test With MAPE 21.44 it can be said that the forecast model is quite good.
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Sariayu, V., & Sugiartawan, P. (2023). Analisis Prediksi Penjualan Lampu Dengan Metode Svm Pada PT. Terang Abadi Raya. Jurnal Sistem Informasi Dan Komputer Terapan Indonesia (JSIKTI), 5(1), 1-10. https://doi.org/10.33173/jsikti.172
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
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[5] W. Rizka, U. Fadilah, D. Agfiannisa, and Y. Azhar, “Analisis Prediksi Harga Saham PT . Telekomunikasi Indonesia Menggunakan Metode Support Vector Machine,” vol. 5, no. 2, 2020.
[6] B. A. Nugroho, A. Kurnia, A. Pradana, and E. Nurfarida, “Prediksi Waktu Kedatangan Pelanggan Servis Kendaraan Bermotor Berdasarkan Data Historis menggunakan Support Vector Machine,” vol. 7, no. 1, pp. 25–30, 2021.
[7] I. H. Pratama, U. Salamah, and U. M. Buana, “PERBANDINGAN ALGORITMA K-NEAREST NEIGHBOR DAN SUPPORT VECTOR MACHINE UNTUK MENENTUKAN PREDIKSI PRODUK-PRODUK TERLARIS PADA TOKO MADURA,” vol. 6, no. 2, pp. 846–858, 2022.
[8] E. Rohadi and R. Wakhidah, “Sistem Peramalan Penjualan Studi Kasus Topi Punggul H . M . Thoha dengan Metode Trend,” Semin. Inform. Apl. Polinema, 2021.
[9] C. Shofiya and S. Abidi, “Sentiment Analysis on COVID-19-Related Social Distancing in Canada Using Twitter Data,” 2021.
[10] B. Sugara, A. Subekti, S. Magister, I. Komputer, S. Vector, and S. Dataset, “PENERAPAN SUPPORT VECTOR MACHINE ( SVM ) PADA SMALL DATASET,” vol. 15, no. 2, pp. 177–182, 2019, doi: 10.33480/pilar.v15i2.649.
[11] H. P. P. Zuriel and A. Fahrurozi, “IMPLEMENTASI ALGORITMA KLASIFIKASI SUPPORT VECTOR MACHINE UNTUK ANALISA SENTIMEN PENGGUNA,” pp. 149–162, 2021.
[12] M. L. Ashari and M. Sadikin, “Prediksi Data Transaksi Penjualan Time Series Menggunakan Regresi Lstm,” J. Nas. Pendidik. Tek. Inform., vol. 9, no. 1, p. 1, 2020, doi: 10.23887/janapati.v9i1.19140.
[13] Fitri Ayu and Nia Permatasari, “perancangan sistem informasi pengolahan data PKL pada divisi humas PT pegadaian,” J. Infra tech, vol. 2, no. 2, pp. 12–26, 2018, [Online]. Available: http://journal.amikmahaputra.ac.id/index.php/JIT/article/download/33/25.