Forecasting Sales of Clothing Products with a Combination Support Vector Regression and Particle Swarm Optimization Algorithm
Peramalan Penjualan Produk Pakaian dengan Kombinasi Metode Support Vector Regression dan Algoritma Particle Swarm Optimization
DOI:
https://doi.org/10.21070/ups.1832Keywords:
Forecasting, Product Sale, Support Vector Regression, Particle Swarm OptimizationAbstract
One of new business concepts in e-commerce is twin date events which result in an increase in product sales so that there is a difference or fluctuation of around 20%, one of them is in the business in textile sector. This study aims to predict number of sales of clothing products at Nara Gallery Collection Boutique using support vector regression method which is known to have reliable performance in predicting time series data. However, it should be noted that the level of accuracy in forecasting is not necessarily high. Therefore, parameters in support vector regression method are optimized using particle swarm optimization algorithm. From this study, results of forecasting were obtained with a MAPE value = 8,98% were obtained by entering optimal parameter value of SVR is C value was 34,3642, ε value was 0,0110, σ value was 0,3677, cLR value was 0,1062, and λ value was 0,0117.
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References
N. Ardiansyah and H. C. Wahyuni, “Analisis Kualitas Produk Dengan Menggunakan Metode FMEA Dan Fault Tree Analisys ( FTA ) Di Exotic UKM Intako,” Prozima, vol. 2, no. 2, pp. 58–63, 2018.
M. Farhan, “Perancangan Sistem Inventori Dan Penjualan Pakaian Di Konveksi Aulia Collection,” JRAMI (Jurnal Ris. dan Apl. Mhs. Inform., vol. 01, no. 02, pp. 171–176, 2020.
M. Efriyanti, Garaika, and R. Irviani, “Analisis Implementasi Electronic Commerce Untuk Meningkatkan Omset Penjualan Butik Mery Berbasis Web Mobile,” J. Signal. STMIK Pringsewu, vol. 7, no. 2, pp. 45–51, 2018.
F. Alfiah, R. Tarmizi, and A. A. Junidar, “Perancangan Sistem E – Commerce Untuk Penjualan Pakaian Pada Toko A & S,” vol. 6, no. 1, pp. 70–81, 2020.
C. Nurlaila and H. Fitriyah, “Effect of E-Commerce, Use of Accounting Information Systems and Business Capital in Student Decision Making for Entrepreneurship,” Indones. J. Law Econ. Rev., vol. 11, pp. 1–13, 2021.
R. E. Utama, N. A. Gani, Jaharuddin, and A. Priharta, Manajemen Operasi, 1st ed. Tangerang Selatan: UM Jakarta Press, 2019.
H. Prasetya and F. Lukiastuti, Manajemen Operasi, 1st ed. Jakarta: MedPress, 2009.
Rahmawati, R. S. Muminin, I. Denni, and R. Ramdhani, “Implementation Of The Support Vector Regression Algorithm And Particle Swarm Optimization In Sales Forecasting,” J. RISTEC Res. Inf. Syst. Technol., vol. 1, no. 1, pp. 1–10, 2021.
D. P. Utomo and B. Purba, “Penerapan Datamining pada Data Gempa Bumi Terhadap Potensi Tsunami di Indonesia,” Pros. Semin. Nas. Ris. Inf. Sci., vol. 1, pp. 846–853, 2019.
Mulaab, Data Mining Konsep dan Aplikasi, 1st ed. Malang: Media Nusa Creative, 2017.
A. B. Raharjo, Z. Z. Dinanto, D. Sunaryono, and D. Purwitasari, “Prediksi Akumulasi Kasus Terkonfirmasi Covid-19 di Indonesia Menggunakan Support Vector Regression,” Techno.COM, vol. 20, no. 3, pp. 372–381, 2021.
D. I. Purnama, “Peramalan Harga Emas Saat Pandemi Covid-19 Menggunakan Model Hybrid Autoregressive Integrated Moving Average - Support Vector Regression,” Jambura J. Math., vol. 3, no. 1, pp. 52–65, 2021.
D. A. Mardhika, B. D. Setiawan, and R. C. Wihandika, “Penerapan Algoritma Support Vector Regression Pada Peramalan Hasil Panen Padi Studi Kasus Kabupaten Malang,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 3, no. 10, pp. 9402–9412, 2019.
V. Rusmalawati, M. T. Furqon, and Indriati, “Peramalan Harga Saham Menggunakan Metode Support Vector Regression ( SVR ) Dengan Particle Swarm Optimization ( PSO ),” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 2, no. 5, pp. 1980–1990, 2018.
M. R. Rifqi, B. D. Setiawan, and F. A. Bacthiar, “Support Vector Regression Untuk Peramalan Permintaan Darah : Studi Kasus Unit Transfusi Darah Cabang – PMI Kota Malang,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 2, no. 10, pp. 3332–3342, 2018.
A. Umiyati, D. Dasari, and F. Agustina, “Peramalan Harga Batubara Acuan Menggunakan Metode PSOSVR Dan IPSOSVR,” EurekaMatika, vol. 9, no. 2, pp. 175–198, 2021.
K. F. Irnanda, A. P. Windarto, and I. S. Damanik, “Optimasi Particle Swarm Optimization Pada Peningkatan Prediksi dengan Metode Backpropagation Menggunakan Software RapidMiner,” JURIKOM (Jurnal Ris. Komputer), vol. 9, no. 1, pp. 122–130, 2022.
K. R. P. Irawan and T. Sukmono, “Planning Total Veener Production PT . XYZ,” Procedia Eng. Life Sci., vol. 1, no. 2, pp. 1–8, 2021.
T. D. Anggraeni and L. Wachidah, “Metode Single Exponential Smoothing dan Fuzzy Time Series Pada Peramalan Permintaan Penjualan Pakaian Thrift Shop Garagesaleinaja,” Bandung Conf. Ser. Stat., vol. 2, no. 2, pp. 254–265, 2022.
N. Hudaningsih, S. F. Utami, and W. A. A. Jabbar, “Perbandingan Peramalan Penjualan Produk Aknil PT. Sunthi Sepuri Menggunakan Metode Single Moving Average Dan Single Exponential Smooting,” J. JINTEKS, vol. 2, no. 1, pp. 15–22, 2020.
C. D. Kusmindari, A. Alfian, and S. Hardini, Production Planning And Inventory Control, 1st ed. Yogyakarta: Deepublish, 2019.
A. K. Wardhani et al., Teknik Peramalan Pada Teknologi Informasi, 1st ed. Padang: PT Global Eksekutif Teknologi, 2022.
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