000			02677ntm a2200337 i 4500
999			_c100868 _d100874
003			MY-KuUP
005			20251125110901.0
006			t||||fr|||| 000 0
007			ta
008			240530t20232023my a|||| |||| 00| 0 eng d
020			_aTHE0009862 (Local) _qHardback
040			_aUMPSA _beng _cUMP _erda
090			_aPSM .F38 2023 r Bc
100	1		_aFatin Farhanah Binti Abd Rahim, _eauthor.
245	1	0	_aSentiment analysis on food reviews in kuantan, pahang using machine learning / _bFatin Farhanah Binti Abd Rahim
264		1	_aKuantan, Pahang: _bUMPSA, _c2023
264		4	_c2023
300			_axiii, 77 pages : _bIllustration (some colour) ; _e1 CD-ROM.
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
347			_2rda _atext file _bPDF
500			_aCenter for Mathematical Sciences
502			_aBachelor of Applied Science in Data Analytics with Honours--Universiti Malaysia Pahang – 2023
504			_aIncludes bibliographical reference
520	3		_aCustomer sentiment analysis is an automated way detecting sentiments in online interactions in order to assess customer opinions about a product, brand or service. It assists companies in gaining insights and efficiently responding to their customers. Social media, blogs and websites have become channels for people to voice their opinions openly on a variety discussion topics making it ideal domain to utilise customers sentiment analysis. This study presents a machine learning approach to analyse how sentiment analysis detects positive and negative feedback about food reviews in Kuantan, Pahang. Customer feedback data will be taken from the suitable social media. All of these data processes will use Python via Jupyter Notebook. These data will be go through a pre-processing stage and the data will be fed to two supervised learning algorithms consisting of Support Vector Machine (SVM) and Logistic Regression. The performance of each model will be compared to select the most accurate model. At the end, the objectives of the project can be achieved because the sentiment analysis is necessary to collect and analyse the large amount of data to give benefit to the customers and producer to discover a psotive or negative reviews. Among the benefits is that the restaurant can make such improvements such as can upgrade existing menu based on customers feedback and customers can choose which is the best food that suits their tastes
610	2	0	_aCenter for Mathematical Sciences _xDissertations
650		0	_aUniversities and colleges _xDissertations
650		0	_aFinal Year Project _xDissertations
942			_2lcc _cPSM