PREDIKSI PERMINTAAN UNTUK MENENTUKAN JUMLAH PRODUKSI PERSEDIAAN PRODUK DI UD. ALFI BERKAH MENGGUNAKAN METODE TRIPLE EXPONENTIAL SMOOTHING

Muazaroh, Aulal Fithroti (2018) PREDIKSI PERMINTAAN UNTUK MENENTUKAN JUMLAH PRODUKSI PERSEDIAAN PRODUK DI UD. ALFI BERKAH MENGGUNAKAN METODE TRIPLE EXPONENTIAL SMOOTHING. Other thesis, STMIK Amikom Purwokerto.

[img] Text
Cover.pdf

Download (937kB)
[img] Text
Daftar Isi.pdf

Download (430kB)
[img] Text
Abstrak.pdf

Download (615kB)
[img] Image
BAB I.pdf
Restricted to Registered users only

Download (537kB)
[img] Image
BAB II.pdf
Restricted to Registered users only

Download (956kB)
[img] Image
BAB III.pdf
Restricted to Registered users only

Download (563kB)
[img] Image
BAB IV.pdf
Restricted to Registered users only

Download (1MB)
[img] Image
BAB V.pdf
Restricted to Registered users only

Download (511kB)
[img] Image
Daftar Pustaka.pdf
Restricted to Registered users only

Download (626kB)
[img] Text
Lampiran.pdf
Restricted to Repository staff only

Download (1MB)

Abstract

UD. Alfi Berkah is a production house engaged in the food industry, which produces typical Maos food namely Jenang. During this time in determining the amount of jenang production, the business owner of the business used intuition experience and prediction to determine the number of products produced, especially during Eid al-Fitr season. Where every day in the season, transactions for direct sales always experience inconsistent increases and decreases which results in many enthusiasts who do not get products. To optimize this product inventory, a method is needed to predict demand to determine the amount of production to be carried out. In predicting requests, the Triple Exponential Smoothing method is used with Additive and Multiplicative models. The calculated data is the Eid Eid season sales data in 2014 to 2018. Of the 5 pairs of constants used, pairs of constants with α = 0.9, β = 0.1, and γ = 0.1 have the best accuracy values for additive models with MAPE = 19.22% and for the multiplicative model with MAPE = 17.26%. Because the accuracy value of the multiplicative model is smaller than the accuracy value of the additive model, the Triple Exponential Smoothing method with the multiplicative model is the best model to predict the next period of demand at UD. Alfi Blessings.

Item Type: Thesis (Other)
Additional Information: Dosen Pembimbing: Riyanto, M.Kom.
Uncontrolled Keywords: Prediction, Triple Exponential Smoothing, Additive Model, Multiplicative Model.
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komputer > Sistem Informasi
Depositing User: UPT Perpustakaan Pusat Universitas Amikom Purwokerto
Date Deposited: 12 Oct 2021 06:54
Last Modified: 12 Oct 2021 06:54
URI: http://eprints.amikompurwokerto.ac.id/id/eprint/1058

Actions (login required)

View Item View Item