Prediksi Stok Barang di Toko Eko Helm Menggunakan Metode Time series Analysis

Betran Dwi Fadillah; Nirwana Hendrastuty

doi:10.30591/jpit.v10i2.8584

Prediksi Stok Barang di Toko Eko Helm Menggunakan Metode Time series Analysis

Betran Dwi Fadillah, Nirwana Hendrastuty

Abstract

Eko Helm Store located in South Lampung, faces challenges in managing helmet inventory, particularly in determining the optimal stock levels for two categories: affordable and premium helmets. This study aims to forecast helmet stock requirements for the year 2024 using the ARIMA method. Weekly sales data from January to December 2024 were analyzed through stationarity testing using the Augmented Dickey-Fuller (ADF) test and differencing, followed by parameter identification based on ACF and PACF plots. The best-fitting models were identified as ARIMA(2,1,0) for premium helmets, with a Mean Squared Error (MSE) of 24.5101 and an Akaike Information Criterion (AIC) of 249.4062, and ARIMA(1,1,0) for affordable helmets, with an MSE of 32.6102 and an AIC of 250.5381. ARIMA was selected due to its ability to capture trends and seasonal fluctuations more effectively than methods such as moving average or exponential smoothing. The forecasting results estimate a stock requirement of 112 units for affordable helmets and 64 units for premium helmets over the next four weeks. The ARIMA model is integrated into an automated forecasting system that runs scheduled scripts without manual intervention. This system supports timely and precise inventory procurement decisions.

Keywords

Helmet; Demand Prediction; Time series Analysis Method; ARIMA

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References

“Artikel – Balai Besar Kimia dan Kemasan.” Accessed: Feb. 19, 2025. [Online]. Available: https://bbkk.kemenperin.go.id/page/bacaartikel.php?id=r0x6uA0PtzVSc7FUcqJcUlnsw0OFug5ggCEf_en2Gjo

I. Y. Musyawarah, “Pengaruh Harga Dan Kualitas Produk Terhadap Keputusan Pembelian Produk Busana Muslim Pada Toko Rumah Jahit Akhwat (Rja) Di Kabupaten Mamuju,” vol. 1, no. 1, 2020.

S. A. Sinaga, “Implementasi Metode Arima (Autoregressive Moving Average) Untuk Prediksi Penjualan Mobil,” J. Glob. Technol. Comput., vol. 2, no. 3, pp. 102–109, Aug. 2023, doi: 10.47065/jogtc.v2i3.4013.

S. R. A. Arifai and Lukman Junaedi, “Prediksi Permintaan Barang Bedasarkan Penjualan Menggunakan Metode Arima Box-Jenkins (Studi Kasus : Pt. Beststamp Indonesia),” J. E-Bis Ekon.-Bisnis, vol. 4, no. 2, pp. 138–146, Nov. 2020, doi: 10.37339/e-bis.v4i2.227.

I. B. B. Mahayana, I. Mulyadi, and S. Soraya, “Peramalan Penjualan Helm dengan Metode ARIMA (Studi Kasus Bagus Store),” Inferensi, vol. 5, no. 1, p. 45, Apr. 2022, doi: 10.12962/j27213862.v5i1.12469.

M. A. Setiawan and A. D. Hartono, “Menggunakan Metode Machine Learning Untuk Memprediksi Nilai Mahasiswa Dengan Model Prediksi Multiclass,” J. Inform., vol. 10, no. 1, 2025.

A. Yaqin, “Penilaian Kredit Menggunakan Algoritma XGBoost dan Logistic Regression,” J. Inform. J. Pengemb. IT, vol. 8, no. 1, pp. 4–10, Dec. 2022, doi: 10.30591/jpit.v8i1.4337.

S. P. Fauzani and D. Rahmi, “Penerapan Metode ARIMA Dalam Peramalan Harga Produksi Karet di Provinsi Riau,” J. Teknol. Dan Manaj. Ind. Terap., vol. 2, no. 4, pp. 269–277, Dec. 2023, doi: 10.55826/tmit.v2i4.283.

E. I. Sihombing, C. D. Suhendra, and L. F. Marini, “Analisis Data Time series Untuk Prediksi Harga Komoditas Pangan Menggunakan Autoregressive Integrated Moving Average”.

S. R. Catur Putri and L. Junaedi, “Penerapan Metode Peramalan Autoregressive Integrated Moving Average Pada Sistem Informasi Pengendalian Persedian Bahan Baku: (Studi Kasus: Toko Kue Onde-Onde Surabaya),” J. Ilmu Komput. Dan Bisnis, vol. 13, no. 1, pp. 164–173, May 2022, doi: 10.47927/jikb.v13i1.293.

Y. D. Cahyani, “Penerapan Metode Arima (Autoregressive Integrated Moving Average) Berbasis Minitab Untuk Memprediksi Tingkat Pengajuan Klaim Asuransi Kecelakaan Di Pt Jasa Raharja Perwakilan Malang,” 2023.

U. A. Yakubu and M. P. A. Saputra, “Time series Model Analysis Using Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) for E-wallet Transactions during a Pandemic,” Int. J. Glob. Oper. Res., vol. 3, no. 3, pp. 80–85, Aug. 2022, doi: 10.47194/ijgor.v3i3.168.

G. T. Meilania, A. V. Septiani, E. Erianti, K. A. Notodiputro, and Y. Angraini, “Pemodelan ARIMA-GARCH dalam Peramalan Kurs Rupiah Terhadap Yen dengan Masalah Keheterogenan Ragam,” Ekon. J. Econ. Bus., vol. 8, no. 1, p. 165, Mar. 2024, doi: 10.33087/ekonomis.v8i1.1294.

A. H. Al Rosyid, C. D. N. Viana, and W. A. Saputro, “Penerapan Model Box Jenkins (Arima) Dalam Peramalan Harga Konsumen Bawang Merah Di Provinsi Jawa Tengah,” Agri Wiralodra, vol. 13, no. 1, pp. 29–37, Apr. 2021, doi: 10.31943/agriwiralodra.v13i1.19.

M. Hidayat, “Analisis Perbandingan Kinerja Keuangan Dan Nilai Perusahaan Sebelum Dan Disaat Pandemi Covid 19,” Meas. J. Akunt., vol. 15, no. 1, pp. 9–17, Jun. 2021, doi: 10.33373/mja.v15i1.3332.

A. Yudhira, “Efektivitas Pembelajaran Daring Pada Masa Pandemi Covid-19: (Studi Komparasi Pembelajaran Luring Dan Daring Pada Mata Kuliah Pengantar Akuntansi Di Universitas Tjut Nyak Dhien),” vol. 2, no. 1, 2021.

I. H. H. Sumbri and A. A. Dzikrullah, “Implementasi Uji Mann Whitney Data Pengamatan Automatic Weather Station (AWS) Digi dan Pengamatan Manual di Stasiun Meteorologi Bandar Udara Internasional Juanda Tahun 2021-2022: Implementasi Uji Mann Whitney Data Pengamatan Automatic Weather Station (AWS) Digi dan Pengamatan Manual di Stasiun Meteorologi Bandar Udara Internasional Juanda Tahun 2021-2022,” Emerg. Stat. Data Sci. J., vol. 2, no. 1, pp. 53–66, Mar. 2024, doi: 10.20885/esds.vol2.iss.1.art6.

A. Kumala, A. Sari, V. Atryes, and M. I. Adelino, “Evaluasi Proses Mental Mahasiswa Teknik Industri Menggunakan Pendekatan Uji Statistik Dengan Metodologi RSME,” J. ARTI Apl. Ranc. Tek. Ind., vol. 19, no. 2, pp. 137–145, Nov. 2024, doi: 10.52072/arti.v19i2.1069.

F. Setiawan, “Perancangan Aplikasi Pengendalian Persediaan Barang Dengan Metode Safety Stock Dan Reorder Point (Studi Kasus : PT. Airlangga Jaya Mandiri),” vol. 2, no. 2, 2024.

R. Sholehah, M. Marsudi, and A. G. Budianto, “Analisis Persediaan Bahan Baku Kedelai Menggunakan Eoq, Rop Dan Safety Stock Produksi Tahu Berdasarkan Metode Forecasting Di Pt. Langgeng,” J. Ind. Eng. Oper. Manag., vol. 4, no. 2, Nov. 2021, doi: 10.31602/jieom.v4i2.5884.

J. Barros, P. Cortez, and M. S. Carvalho, “A systematic literature review about dimensioning safety stock under uncertainties and risks in the procurement process,” Oper. Res. Perspect., vol. 8, p. 100192, 2021, doi: 10.1016/j.orp.2021.100192.

DOI: https://doi.org/10.30591/jpit.v10i2.8584