A Comparison of SES and SMA Method Against Production Level Property of Fabrication Precision Engineering and Its Effect on Production Planning (Case Study PT X)

Via Rensi Novita Alfa Reza; Ancala Laras Putri

doi:10.4108/eetel.3709

Authors

Via Rensi Novita Alfa Reza Politeknik Negeri Batam
Ancala Laras Putri Politeknik Negeri Batam

DOI:

https://doi.org/10.4108/eetel.3709

Keywords:

Forecasting, SES, SMA, Aluminum

Abstract

One of the goals of forecasting is to be able to predict the data needed in the future, one of which is the data on demand for the amount of production in a company. PT X is a manufacturing company based on demand or custom. This leads to uncertainty in the use of required materials, so proper forecasting is needed to estimate the material stock requirements. This study used single exponential smoothing and single moving average methods with quantitative approaches to aluminum materials. By calculating forecasting using these two methods, it is possible to find the best method for use by PT X. Based on the test, the SES method has the smallest error rate so it can be used to analyze the data, with α=0.8 yielding a forecast in the 13th month of 308.71408 pcs.

References

Andriana, A. D., & Susanto, R. (2017). Peramalan Jumlah Produksi Teh Menggunakan Metode. Prosiding SAINTIKS FTIK UNIKOM.

Anis, Nandiroh, & Utami. (2007). Optimasi Perencanaan Produksi dengan Metode Goal Programming. Jurnal Teknik Industri, 133 - 143.

Assauri, S. (1984). Teknik Model Peramalan. Jakarta: Universitas Indonesia.

Daniarsyah, A. (2021, Februari 12). Fabrikasi dalam Industri - Definisi, Jenis, Proses, dan Contoh Produknya. Diambil kembali dari WIRA: https://wira.co.id/fabrikasi-adalah/

Ginting, R. (2007). Sistem Produksi. Yogyakarta: Graha Ilmu.

Heizer, J., & Render, B. (2011). Manajemen Operasi Edisi Sembilan. Jakarta: Salemba Empat.

Herjanto, E. (2008). Manajemen Operasi Edisi Ketiga. Jakarta: Grasindo.

Hudaningsih, N., Utami, S. F., & Jabbar, W. A. (2020). Perbandingan Peramalan Penjualan Produk AKNIL PT Sunthi Sepuri Menggunakan Metode Single Moving Average dan Single Exponential Smoothing. Jurnal JINTEKS, 15 - 22.

Indah, D. R., & Rahmadani, E. (2018). Sistem Forecasting Perencanaan Produksi. Jurnal Penelitian Ekonomi Akuntansi (JENSI), 10 - 18.

McKinsey & Company. (2019). Otomatisasi dan Masa Depan Pekerjaan di Indonesia. Jakarta: Mckinsey & Company.

Nurlifa, A., & Kusumadewi, S. (2017). Sistem Peramalan Jumlah Penjualan Menggunakan Metode Moving Average pada Rumah Jilbab Zaky. Jurnal INOVTEK Polbeng.

Saiful, M. A. (2021). Perbandingan Single Exponential Smoothing Dan Metode Single Moving. Prosiding SAINTIKS FTIK UNIKOM.

Santiari, N. L., & Rahayuda, I. S. (2021). Analisis Perbandingan Metode Single Exponential Smoothing dan Single. Jurnal Informatika Universitas Pamulang, 312 - 318.

Sitorus, N. S., Siagian, Y., & Aulia, R. (2021). Penerapan Metode SMA untuk Peramalan Tingkat Produksi Tanaman Pangan di Dinas Pertanian. Journal of Computer, 27 - 32.

Sugiyono. (2017). Metode Penelitian Kuantitatif, Kualitatif. Bandung: CV Alfabeta.

Thahirah, F. S., Barus, M. D., & Mustafa. (2021). Single Exponential Smoothing: Analisis Forecasting dalam unyuPerencanaan Produksi (Studi Kasus PT Food Beverages Indonesia). Seminar of Social Sciences Engineering & Humaniora, 199 - 212.