Penerapan Data Deret Waktu dalam Peramalan Permintaan Semen Curah Tipe Ezpro Menggunakan Perangkat Lunak  POM QM (Studi Kasus di PT. WXY)

Farhan Aufa Sholihin; Dira Ernawati

doi:10.37090/indstrk.v9i3.2101

Authors

Farhan Aufa Sholihin Universitas Pembangunan Nasional "Veteran" Jawa Timur
Dira Ernawati Universitas Pembangunan Nasional "Veteran" Jawa Timur

DOI:

https://doi.org/10.37090/indstrk.v9i3.2101

Abstract

PT WXY, which operates in the cement industry, seeks to improve operational efficiency by forecasting demand for EzPro type bulk cement for the coming period. This study aims to determine the most effective forecasting method using two approaches, namely Moving Average and Single Exponential Smoothing, and analyzing historical data for 10 months using POM QM V5 software. The accuracy of the forecasting results is evaluated by Mean Squared Error (MSE). The results show that the Single Exponential Smoothing method has an MSE of 1,113,479,000, lower than the Moving Average method which reaches 1,721,099,000. Therefore, Single Exponential Smoothing is chosen as the best forecasting method to improve accuracy, optimize distribution schedules, and reduce operational risks such as excess or shortage of stock. Consistent application of this method is expected to support the smoothness of the supply chain and improve the company's operational efficiency.

Keywords: Demand Forecasting, POM QM V5, Single Exponential Smoothing, Single Moving Average.

Downloads

Download data is not yet available.

References

Ajiono, & Hariguna, T. (2023). Comparison of Three Time Series Forecasting Methods on Linear Regression, Exponential Smoothing and Weighted Moving Average. International Journal of Informatics and Information Systems, 6(2), 89–102.

Anbar, L. A., & Wahyudin, W. (2022). Peramalan permintaan tas laptop menggunakan model time series. Journal Industrial Servicess, 7(2), 285–288.

Daryani, S., Aritonang, S. S., & Panggabean, S. (2024). Optimasi Keuntungan Produksi UMKM Keripik Pisang Menggunakan Linear Programming Metode Simpleks Dan Software POM-QM. Jurnal Riset Rumpun Matematika Dan Ilmu Pengetahuan Alam, 3(1), 69–88.

Hulu, E., Zebua, S., Mendora, M. S. D., & Hulu, P. F. (2024). Analisis Ramalan Volume Penjualan Semen Dengan Metode Time Series Di UD.Denis Kota Gunungsitoli. Jurnal Ekonomi Bisnis, Manajemen Dan Akuntansi (Jebma), 4(3), 2047–2056.

Kurniawan, R., Samari, & Ratnanto, S. (2022). Komparasi Model Single Moving Avarage & Exponential Smoothing Untuk Peramalan Penjualan AMDK NuClees. Jurnal Nusantara Aplikasi Manajemen Bisnis, 7(1), 84–92.

Meliana, D., Suharto, S., & Suwarni, P. E. (2021). ANALISIS PERAMALAN PENJUALAN AIR MINUM DALAM KEMASAN 240ml PADA PT TRIJAYA TIRTA DARMA (GREAT) DENGAN METODE SINGLE MOVING AVARAGE DAN EXPONENTIAL SMOOTHING. Industrika: Jurnal Ilmiah Teknik Industri, 4(2), 114–120.

Muluk, R. K. A., & Suryopratomo, A. (2022). Comparative Analysis of Four Time-Series Models in an Effort to Determine The Optimal Forecasting Results. Sainteks: Jurnal Sains Dan Teknik, 4(2), 111–122.

Rini, M. W., & Ananda, N. (2022). Perbandingan Metode Peramalan Menggunakan Model Time Series. Tekinfo: Jurnal Ilmiah Teknik Industri Dan Informasi, 10(2), 88–101.

Septiansyah, R., & Wahyudin. (2023). Perbandingan Peramalan Permintaan Produk Hollow Alumunium Menggunakan Metode Single Moving Average Dan Exponential Smoothing Pada PT. MU. Industrika : Jurnal Ilmiah Teknik Industri, 7(3), 257–268.

Sigit, R. A. P., & Herwanto, D. (2024). Penerapan Metode Double Exponential Smoothing dan Moving Average pada Peramalan Persediaan Spare Part Oil Filter di PT . X Cabang Karawang. Industrika : Jurnal Ilmiah Teknik Industri, 8(4), 935–946.

Sipayung, T., Zulfikar, M. K., & Tarigan, W. J. (2023). Pengaruh Likuiditas Dan Struktur Modal Terhadap Profitabilitas Perusahaan (Studi Kasus Perusahaan Pabrik Semen Yang Terdaftar Di Bursa Efek Indonesia Periode 2018 - 2022). Jurnal Ilmiah Accusi, 5(2), 146–155.

Utami, Y., Vinsensia, D., & Panggabean, E. (2024). Forecasting Exponential Smoothing untuk Menentukan Jumlah Produksi. Jurnal Ilmu Komputer Dan Sistem Informasi (JIKOMSI), 7(1), 154–160.

Wardah, S., & Iskandar. (2016). ANALISIS PERAMALAN PENJUALAN PRODUK KERIPIK PISANG KEMASAN BUNGKUS (Studi Kasus: Home Industry Arwana Food Tembilahan). Jurnal Teknik Industri, 11(3), 135–142.

Wijaya, R. A., Rr. Erlina, & Mardiana, N. (2023). Comparison of Moving Average and Exponential Smoothing Methods in Sales Forecasting of Banana Chips Products in Pd. Dwi Putra Tulang Bawang Barat. Journal of Finance and Business Digital, 2(6), 193–208.

Wildan, K., & Asy’ari, S. (2023). Penentuan Metode Peramalan (Forecasting) Pada Permintaan Penjualan Di Cv. Lia Tirta Jaya Prigen. Jurnal Cakrawala Ilmiah, 2(11), 4077–4088.