EZ Forecast 2.0: a system of Univariate Models / Noreha Mohamed Yusof … [et al.]

Mohamed Yusof, Noreha and Mahad, Nor Faradilah and Mohd Yusop, Noorezatty and Amit, Norani (2021) EZ Forecast 2.0: a system of Univariate Models / Noreha Mohamed Yusof … [et al.]. In: International Jasin Multimedia & Computer Science Invention and Innovation Exhibition (i-JaMCSIIX 2021). UiTM Cawangan Melaka Kampus Jasin, pp. 47-50.

Abstract

The process of analysis that is performed using past and present data is known as forecasting. It involves the analysis of trends for future predictions. Forecasting helps an organization to cope with future uncertainties. However, forecasting techniques involve complex tasks. In EZ FORECAST 2.0, data forecasting is made easy as the system is developed to be user friendly where the user only needs to key in the data set and the analysis will be done automatically by the system. An upgraded version of EZ FORECAST 1.0, a system of univariate modelling techniques is introduced to forecast and evaluate the best techniques identified by the time series model. This new system is proposed to recommend the best model of the data. This system assists the decision-maker in forecasting the time series data accurately and systematically. The objectives of this system are: (1) to monitor the performance of the time series data set using a univariate model, (2) to forecast the time series data set one step ahead, and (3) to propose the best model based on minimum error measures. There are five methods used in this system which are Naive Forecast, Naive with Trend Forecast, Single Exponential Smoothing, Double Exponential Smoothing, and Holt’s Method. Real-life data from a Food and Beverages (F&B) company is used to demonstrate the effectiveness of the system. The findings show that the system is able to recommend the best model with forecasting values which has minimum error measures. This system benefits an organization by providing valuable information that helps the top management to make decisions on the future direction of the company.

Metadata

Item Type: Book Section
Creators:
Creators
Email / ID Num.
Mohamed Yusof, Noreha
noreh144@uitm.edu.my
Mahad, Nor Faradilah
UNSPECIFIED
Mohd Yusop, Noorezatty
UNSPECIFIED
Amit, Norani
UNSPECIFIED
Contributors:
Contribution
Name
Email / ID Num.
Patron
Md Badarudin, Ismadi
UNSPECIFIED
Advisor
Tahar @ Yusoff, Nor Fadilah
UNSPECIFIED
Advisor
Jono, Mohd Nor Hajar Hasrol
UNSPECIFIED
Advisor
Abdul Rahid @ Abdul Rashid, Nurul Najwa
UNSPECIFIED
Advisor
Sharip, Anis Afiqah
UNSPECIFIED
Subjects: H Social Sciences > HA Statistics > Theory and method of social science statistics > Data envelopment analysis
Q Science > QA Mathematics > Time-series analysis
Q Science > QA Mathematics > Analysis
Divisions: Universiti Teknologi MARA, Melaka > Jasin Campus > Faculty of Computer and Mathematical Sciences
Event Title: International Jasin Multimedia & Computer Science Invention and Innovation Exhibition (i-JaMCSIIX 2021)
Event Dates: 15 February 2021 - 31 March 2021
Page Range: pp. 47-50
Keywords: Forecasting; Time series; Univariate model
Date: 2021
URI: https://ir.uitm.edu.my/id/eprint/50620
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