Predicting restaurant revenue using machine learning

Nadiah Hanun Ismail

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Type :	article
Subject :	HB Economic Theory
Main Author :	Nadiah Hanun Ismail
Additional Authors :	Chee, Wooi Hooy
Title :	Predicting restaurant revenue using machine learning

Place of Production :	Tanjong Malim
Publisher :	Fakulti Pengurusan dan Ekonomi
Year of Publication :	2023
Corporate Name :	Universiti Pendidikan Sultan Idris

Abstract : Universiti Pendidikan Sultan Idris

This paper studied the restaurant branch’s revenue to determine the best strategic location with period of study from 1996 until 2014. On the other hand, the paper examined multiple linear regression, decision tree regression, random forest regression and support vector regression to forecasting approach that will likely generate the highest accuracy during validation process in predicting the revenue. Analysis have resulted that support vector regression gives the lowest of error. Some recommendation been proposed for successful plans toward revenue growth which applicable to adopt in the company. Keywords: Supervised machine learning; Restaurant revenue prediction; TFI branch

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