Article Sidebar

Download
PDF (Bahasa Indonesia)
Statistic
Read Counter : 58 Download : 56

Downloads

Download data is not yet available.

Main Article Content

Abstract

In carrying out a business that operates in the field of selling goods, predictions are very necessary. Predictions are very necessary because making predictions can help predict what will happen in the future so that the risks that will occur can be minimized as small as possible. This research focuses on sales predictions in 2023 for the HT Motorola XiR C2660 brand using the SVR (support vector regression) algorithm and using linear type kernel parameter testing and c(cost) with a test value of 0.1. To obtain parameter types and parameter test values, use the GridSearchCV technique. Apart from that, this research uses error value testing with mean absolute percentage error (MAPE). So the results of the HT Motorola XiR C2660 sales prediction for 2023 with the SVR algorithm were obtained. In 2023, 209 units were sold with an error value of 11.23%, which means the forecasting ability with the SVR algorithm is good.

Keywords

MAPE, prediction, sale, SVR

Article Details

How to Cite
Wildwina, & Ryan Putranda Kristianto. (2024). Prediksi Penjualan HT Motorola XiR C2660 Menggunakan Algoritma Support Vector Regression (Studi Kasus: CV. Alfacoms). Jurnal Teknik Informatika Dan Komputer, 3(1), 11–16. https://doi.org/10.22236/jutikom.v3i1.13836
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Aditya Quantano Surbakti, Regiolina Hayami, & Januar Al Amien. (2021). Analisa Tanggapan Terhadap Psbb Di Indonesia Dengan Algoritma Decision Tree Pada Twitter. Jurnal CoSciTech (Computer Science and Information Technology), 2(2), 91–97. https://doi.org/10.37859/coscitech.v2i2.2851
  2. Aulia, A. (2022). Prediksi Harga Emas dengan Menggunakan Algoritma Support Vector Regression (SVR) dan Linear Regression (LR). Jurnal Ilmiah Wahana Pendidikan, 8(5), 84–88. https://doi.org/10.5281/zenodo.6408864
  3. Hatta, M., & Fauziah Fitri, A. (2020). Sistem Prediksi Persediaan Stok Darah Dengan Metode Least Square Pada Unit Transfusi Darah Studi Kasus PMI Kota Cirebon. Jurnal Ilmiah Ilmu Komputer, 6(1), 41–45. https://doi.org/10.35329/jiik.v6i1.130
  4. Hermanto, B., Yusman, M., & Nagara, N. (2019). Sistem Informasi Manajemen Keuangan pada PT. Hulu Balang Mandiri Menggunakan Framework Laravel. Jurnal Komputasi, 7(1), 17–26. https://doi.org/10.23960/komputasi.v7i1.2051
  5. Ismanto, T., & Azwir, H. H. (n.d.). Penentuan Metode Peramalan Yang Tepat Untuk Perencanaan Bahan Baku Di Pt. Acp. Academia.Edu. https://www.academia.edu/download/53325007/Thesis_Journal_004201000151_Tommy_Ismanto.pdf
  6. Kafil, M. (2019). Penerapan Metode K-Nearest Neighbors Untuk Prediksi Penjualan Berbasis Web Pada Boutiq Dealove Bondowoso. JATI (Jurnal Mahasiswa Teknik Informatika), 3(2), 59–66. https://doi.org/10.36040/jati.v3i2.860
  7. Laminullah, R. S., Annur, H., & I, I. S. K. (2020). Prediksi Penjualan Pertalite Menggunakan Metode Support Vector Regression. Jurnal Nasional CosPhi, 4(1), 12–14.
  8. Lature, H. (2022). Implementasi Metode Support Vector Regression (SVR) dalam Prediksi Persediaan Sarang Walet. Bulletin of Information System and Technology, 1(1), 27–31.
  9. Maricar, A. M. (2019). Analisa Perbandingan Nilai Akurasi Moving Average dan Exponential Smoothing untuk Sistem Peramalan Pendapatan pada Perusahaan XYZ. Jurnal Sistem Dan Informatika (JSI), 13(2), 36–45. https://www.jsi.stikom-bali.ac.id/index.php/jsi/article/view/193
  10. Maulana, N. D., Setiawan, B. D., & Dewi, C. (2019). Implementasi Metode Support Vector Regression (SVR) Dalam Peramalan Penjualan Roti (Studi Kasus : Harum Bakery). Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 3(3), 2986–2995.
  11. Nabillah, I., & Ranggadara, I. (2020). Mean Absolute Percentage Error untuk Evaluasi Hasil Prediksi Komoditas Laut. JOINS (Journal of Information System), 5(2), 250–255. https://doi.org/10.33633/joins.v5i2.3900
  12. Nugroho, P. A., Fenriana, I., & Arijanto, R. (2020). Implementasi Deep Learning Menggunakan Convolutional Neural Network ( Cnn ) Pada Ekspresi Manusia. Algor, 2(1), 12–21.
  13. Prakoso, B. H. (2019). Implementasi Support Vector Regression pada Prediksi Inflasi Indeks Harga Konsumen. MATRIK : Jurnal Manajemen, Teknik Informatika Dan Rekayasa Komputer, 19(1), 155–162. https://doi.org/10.30812/matrik.v19i1.511
  14. Selay, A., Andgha, G. D., Alfarizi, M. A., Wahyudi, M. I. B., Falah, M. N., Encep, M., & Khaira, M. (2023). Skripsi,Sistem Informasi Penjualan. 2, 1–6.
  15. Suharjanto, S., & Rahayu, A. T. (2020). Pengaruh Filter untuk Meredam Gangguan Sinyal pada Repeater Radio Komunikasi Jalur VHF (Very High Frequency). Jurnal Teknika, 6(4), 204–208.