GODELVA, GABRIELLA NATHANIA (2019) APPAREL RETAIL DEMAND FORECASTING TO MANAGE INVENTORY IN CV. PERDANA MANDIRI. S1 thesis, UNIVERSITAS ATMA JAYA YOGYAKARTA.

[thumbnail of JUDUL DAN ABSTRAK]
Preview
 Text (JUDUL DAN ABSTRAK)
TI INT 008147.pdf
Download (517kB) | Preview
[thumbnail of BAB I]
Preview
 Text (BAB I)
TI INT 108147.pdf
Download (72kB) | Preview
[thumbnail of BAB II]
Preview
 Text (BAB II)
TI INT 208147.pdf
Download (207kB) | Preview
[thumbnail of BAB III]
Preview
 Text (BAB III)
TI INT 308147.pdf
Download (123kB) | Preview
[thumbnail of BAB IV]
Preview
 Text (BAB IV)
TI INT 408147.pdf
Download (419kB) | Preview
[thumbnail of BAB V] Text (BAB V)
TI INT 508147.pdf
Restricted to Registered users only
Download (402kB)
[thumbnail of BAB VI] Text (BAB VI)
TI INT 608147.pdf
Restricted to Registered users only
Download (668kB)
[thumbnail of BAB VII]
Preview
 Text (BAB VII)
TI INT 708147.pdf
Download (668kB) | Preview

Abstract

Demand forecasting is important in any part of business including retail. It assists
to determine the order quantity from suppliers, safety stock in inventory, and
inventory management for normal selling condition and for when there would be
promotions (marketing strategy like discounts). CV. Perdana Mandiri has a clothing
store with inventory problems (overstock and understock). As per request from the
company, the name of the clothing store is disguised as X clothing store. A forecast
tool was developed using Microsoft Excel to help X clothing store carries out
demand forecast easily. The methods used in the forecast tool were simple
averages, moving averages, and exponential smoothing (single exponential
smoothing, double exponential smoothing, and triple exponential smoothing).
Forecasting was done by grouping their SKUs to a family code group. Trial and
error were done to achieve the best forecasting method with the minimum forecast
error in every code group. All sixty-six code groups were forecasted, and it resulted
in sixty-one code groups with triple exponential smoothing as their best methods,
three code groups with single exponential smoothing as their best methods, and
two code groups with simple average method as their best forecasting method

Item Type: Thesis (S1)
Uncontrolled Keywords: retail, apparel, time series forecasting, seasonal data forecasting.
Subjects: Industrial Engineering > Production and Inventory Management
Divisions: Fakultas Teknologi Industri > Teknik Industri Internasional
Depositing User: Editor UAJY
Date Deposited: 24 Sep 2021 03:10
Last Modified: 24 Sep 2021 03:10
URI: https://repository.uajy.ac.id/id/eprint/24821

Actions (login required)

View Item
View Item