CUSTOMER SENTIMENT ANALYSIS FOR HOTEL RATING ASSESSMENT BASED ON SENTISTRENGTH CLASSIFICATION METHOD USING SUPPORT VECTOR MACHINE ALGORITHM (CASE STUDY PEGIPEGI.COM)

In looking for hotels is greatly facilitated by the rise of travel agents that already exist in Indonesia. Wherever and wherever the user comes from, can ensure a scheduled departure quickly and efficiently. However, this will be achieved quickly if the user already has the experience of staying...

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Main Author:	Hadikusuma, Aristyo
Format:	Theses
Language:	Indonesia
Online Access:	https://digilib.itb.ac.id/gdl/view/68348
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Institution:	Institut Teknologi Bandung
Language:	Indonesia

id	id-itb.:68348
spelling	id-itb.:683482022-09-14T08:54:58ZCUSTOMER SENTIMENT ANALYSIS FOR HOTEL RATING ASSESSMENT BASED ON SENTISTRENGTH CLASSIFICATION METHOD USING SUPPORT VECTOR MACHINE ALGORITHM (CASE STUDY PEGIPEGI.COM) Hadikusuma, Aristyo Indonesia Theses Machine learning, Review, Information Technology. natural language programming, sentistrength, word weight INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/68348 In looking for hotels is greatly facilitated by the rise of travel agents that already exist in Indonesia. Wherever and wherever the user comes from, can ensure a scheduled departure quickly and efficiently. However, this will be achieved quickly if the user already has the experience of staying at a hotel of interest. Problems occur if the reference you are interested in does not meet your expectations. Even though users tend to spend their time figuring out the experiences of others who have stayed by reading reviews or comments. Based on the need for so many hotel bookings and the assessment of hotel quality has not been maximized, it offers a solution for making rating indicators based on reviews commented by visitors. With the SentiStrength method the weighting of words is based on words that often appear. Then it can be done to categorize review sentiment to determine the condition of the hotel based on the reviews provided. And recommendations will be given based on positive, negatif and neutral ratings in commenting on the condition of the hotel in the form of a reviewer for each customer who visits. This is very helpful for customers in determining the condition of the hotel based on a good sentiment rating. text
institution	Institut Teknologi Bandung
building	Institut Teknologi Bandung Library
continent	Asia
country	Indonesia Indonesia
content_provider	Institut Teknologi Bandung
collection	Digital ITB
language	Indonesia
description	In looking for hotels is greatly facilitated by the rise of travel agents that already exist in Indonesia. Wherever and wherever the user comes from, can ensure a scheduled departure quickly and efficiently. However, this will be achieved quickly if the user already has the experience of staying at a hotel of interest. Problems occur if the reference you are interested in does not meet your expectations. Even though users tend to spend their time figuring out the experiences of others who have stayed by reading reviews or comments. Based on the need for so many hotel bookings and the assessment of hotel quality has not been maximized, it offers a solution for making rating indicators based on reviews commented by visitors. With the SentiStrength method the weighting of words is based on words that often appear. Then it can be done to categorize review sentiment to determine the condition of the hotel based on the reviews provided. And recommendations will be given based on positive, negatif and neutral ratings in commenting on the condition of the hotel in the form of a reviewer for each customer who visits. This is very helpful for customers in determining the condition of the hotel based on a good sentiment rating.
format	Theses
author	Hadikusuma, Aristyo
spellingShingle	Hadikusuma, Aristyo CUSTOMER SENTIMENT ANALYSIS FOR HOTEL RATING ASSESSMENT BASED ON SENTISTRENGTH CLASSIFICATION METHOD USING SUPPORT VECTOR MACHINE ALGORITHM (CASE STUDY PEGIPEGI.COM)
author_facet	Hadikusuma, Aristyo
author_sort	Hadikusuma, Aristyo
title	CUSTOMER SENTIMENT ANALYSIS FOR HOTEL RATING ASSESSMENT BASED ON SENTISTRENGTH CLASSIFICATION METHOD USING SUPPORT VECTOR MACHINE ALGORITHM (CASE STUDY PEGIPEGI.COM)
title_short	CUSTOMER SENTIMENT ANALYSIS FOR HOTEL RATING ASSESSMENT BASED ON SENTISTRENGTH CLASSIFICATION METHOD USING SUPPORT VECTOR MACHINE ALGORITHM (CASE STUDY PEGIPEGI.COM)
title_full	CUSTOMER SENTIMENT ANALYSIS FOR HOTEL RATING ASSESSMENT BASED ON SENTISTRENGTH CLASSIFICATION METHOD USING SUPPORT VECTOR MACHINE ALGORITHM (CASE STUDY PEGIPEGI.COM)
title_fullStr	CUSTOMER SENTIMENT ANALYSIS FOR HOTEL RATING ASSESSMENT BASED ON SENTISTRENGTH CLASSIFICATION METHOD USING SUPPORT VECTOR MACHINE ALGORITHM (CASE STUDY PEGIPEGI.COM)
title_full_unstemmed	CUSTOMER SENTIMENT ANALYSIS FOR HOTEL RATING ASSESSMENT BASED ON SENTISTRENGTH CLASSIFICATION METHOD USING SUPPORT VECTOR MACHINE ALGORITHM (CASE STUDY PEGIPEGI.COM)
title_sort	customer sentiment analysis for hotel rating assessment based on sentistrength classification method using support vector machine algorithm (case study pegipegi.com)
url	https://digilib.itb.ac.id/gdl/view/68348
_version_	1822933617842585600

CUSTOMER SENTIMENT ANALYSIS FOR HOTEL RATING ASSESSMENT BASED ON SENTISTRENGTH CLASSIFICATION METHOD USING SUPPORT VECTOR MACHINE ALGORITHM (CASE STUDY PEGIPEGI.COM)

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