Implementation of the Triple Exponential Smoothing Method for Predicting Helmet Sales Implementasi Metode Triple Exponential Smoothing untuk Prediksi Penjualan Helm

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Published: Nov 30, 2022
DOI: https://doi.org/10.21070/joincs.v5i2.1607
Keywords:
Forecasting, Triple Exponential Smoothing, Holt Winter

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Ronggo Bayu Saputro
Universitas Islam Balitar Blitar
Kurnia Paranita Kartika
Universitas Islam Balitar Blitar
Wahyu Dwi Puspitasari
Universitas Islam Balitar Blitar

Abstract

Helmet stock at the Trend Helmet store is very important to prepare, because it is for the readiness of goods to be sold in the future. Therefore, it is necessary to do forecasting to find out the estimated stock in the future. The method that can be used to predict the stock of goods for several periods at once is Triple Exponential Smoothing. Helmet stock forecasting results with Cargloss helmet sales data obtained a forecast for 2022. Alpha, beta and gamma used in this study were 0.3. Cargloss helmet sales forecast results in January as many as 379, February as many as 449, March as many as 431, April as many as 500, May as many as 483, June as many as 552, July as many as 534, August as many as 604, September as many as 586, October as many as 656, November as many as 638 , December as many as 707. The results of the calculation of accuracy with Mean Absolute Percentage Error with Alpha, Beta and Gamma values of 0.3 are 44.4%. Based on the value of Mean Absolute Percentage Error helmet sales forecasting with Triple Exponential Smoothing method is feasible to use.

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How to Cite
Saputro, R. B., Kartika, K. P., & Puspitasari, W. D. (2022). Implementation of the Triple Exponential Smoothing Method for Predicting Helmet Sales. JOINCS (Journal of Informatics, Network, and Computer Science), 5(2), 30-34. https://doi.org/10.21070/joincs.v5i2.1607
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Vol 5 No 2 (2022): November
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Articles

Copyright (c) 2022 Ronggo Bayu Saputro, Kurnia Paranita Kartika, Wahyu Dwi Puspitasari

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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Islamiati, N., AP, I., & Wajidi, F. (2020). Metode Triple Exponential Smoothing ( Tes ) Dalam. 2020(Semnasif).
[2] Nurlaily, D., Silfiani, M., & Hayati, N. F. (2022). Perbandingan Metode Arima, Dan Triple Exponential Smoothing Pada Studi Kasus Data Ekspor Non Migas Di Kalimantan Timur.
[3] Hayuningtyas, R. Y. (2020). Implementasi Metode Triple Exponential Smoothing Untuk Prediksi Penjualan Alat Kesehatan. EVOLUSI : Jurnal Sains Dan Manajemen, 8(1), 29–35. https://doi.org/10.31294/evolusi.v8i1.7404.
[4] Hartomo, K. D., Prasetyo, S. Y., & Suharjo, R. A. (2020). Prediksi Stok dan Pengaturan Tata Letak Barang Menggunakan Kombinasi Algoritma Triple Exponential Smoothing dan FP-Growth. Jurnal Teknologi Informasi Dan Ilmu Komputer, 7 869. https://doi.org/10.25126/jtiik.2020751863.
[5] Yulian, I., Anggraeni, D. S., & Aini, Q. (2020). Penerapan Metode Trend Moment Dalam Forecasting Penjualan Produk CV. Rabbani Asyisa. JURTEKSI (Jurnal Teknologi Dan Sistem Informasi), 6(2), 193–200.
[6] Arifin, Z., Herliani, J., & Hamdani. (2019). Peramalan Pengangguran Menggunakan Metode Double Exponential Smoothing Di Provinsi Kalimantan Timur. Prosiding Seminar Nasional Ilmu Komputer Dan Teknologi Informasi, 4(1), 24–29.