"SISTEM PREDIKSI PERSEDIAAN STOK SPAREPART DI PT. TOTOISAN"

Suci, Nuzulul Wulan (2021) "SISTEM PREDIKSI PERSEDIAAN STOK SPAREPART DI PT. TOTOISAN". undergraduate thesis, Universitas Muhammadiyah Gresik.

[img]
Preview
Text
Halaman Pernyataan Orisinalitas.pdf

Download (121kB) | Preview
[img]
Preview
Text
Halaman Pengesahan.pdf

Download (123kB) | Preview
[img]
Preview
Text
Halaman Persetujuan Publikasi.pdf

Download (187kB) | Preview
[img]
Preview
Text
Halaman Judul.pdf

Download (1MB) | Preview
[img]
Preview
Text
BAB I .pdf

Download (833kB) | Preview
[img]
Preview
Text
BAB II.pdf

Download (1MB) | Preview
[img]
Preview
Text
BAB III.pdf

Download (2MB) | Preview
[img] Text
BAB IV.pdf
Restricted to Repository staff only

Download (5MB)
[img]
Preview
Text
BAB V.pdf

Download (807kB) | Preview
[img]
Preview
Text
Daftar Pustaka.pdf

Download (803kB) | Preview
[img]
Preview
Text
Lampiran.pdf

Download (904kB) | Preview

Abstract

Pf. Totoisan is a trade company ofgoods and seNices, with business activities in selling motorbikes al1d spare pal.ts. In carrying ou1 its actjvities cefiain]y requires accurate, lelevant and tirnely information. One impoftant information is information about inventory. Problems that occur at PT. Totoisan companies are not able to control the inventory of spare parts properly. This is due to several :actors, such as incomplete rccording of infonnation on stock itens as \r/ell as lales and purchase transactions of goods carried out. l'hese facton cause the aompany not to Lnow clearly when to order goods so that the company often runs .1ut of stock and rltimately is unable to meet customer needs. ln addition, records -.i incomplete sales and purchase transactions also cause customers to wait a lotB :ime because of the inefficient sales process to customers. Stock inventoly of :.are parts is one ofthe important factors in slLppofiing operational sustainability ii PT. Totoisan For that we need a system to forecast the stock of goods for the ::\I period with the method of Single Moving Average. The Moving Average r:ethod is obtained through addition and search for the average value of a cerlain ::nber of periods. The shorter the period, the moving average will be more -=rsitive and can identify new trends faster. While a longer period is trusted but :,s responsive to trend cltanges, therefore a longer period can only take on a rr!,sea trend. The results ofthis system can reconmend the compadson ofactual --,a liom January 2016 to September 2018 using l2-month data calculations with : ilfferent types of supplies with an eror percentage of 84.19042% \a,ith the :::ulrs ofthe test data apprcach.

Item Type: Thesis (undergraduate)
Uncontrolled Keywords: Data Mining, forecasting, Single Moving Average ...
Subjects: Engineering > Informatics Engineering
Engineering
Divisions: Faculty of Engineering > Informatics Engineering Study Program
Depositing User: Nuzulul Wulan Suci
Date Deposited: 07 Jun 2021 06:26
Last Modified: 07 Jun 2021 06:26
URI: http://eprints.umg.ac.id/id/eprint/4875

Actions (login required)

View Item View Item