TOURISM IN YOGYAKARTA RECOMMENDATIONS USING COSINE SIMILARITY ALGORITHM

WIMALA, STEPHANIE NADA (2023) TOURISM IN YOGYAKARTA RECOMMENDATIONS USING COSINE SIMILARITY ALGORITHM. Skripsi thesis, UNIVERSITAS KATOLIK SOEGIJAPRANATA.

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Abstract

Currently, Google Maps is very popularly used to find a location among the public. The google maps feature is also very useful in finding the location of tourist attractions, from the location of tourist attractions that have a medium to high rating and finding these locations easily. Therefore, people who visit tourist sites or new locations can use the google maps application on their mobilephones so that they know the locations they are visiting with moderate to high ratings. However, it is quite wasting time because we also have to consider the ratings and reviews from other visitors, as well as the location of the tourist attractions closest to us. In this paper, the author found ways or programs to make a recommendation program for tourist sites in Yogyakarta, especially based on the use of Google Maps reviews and ratings and their percentage to readers. This research utilizes the Google Maps API to find nearby areas and offer information to tourists. This program will provide recommendations for the closest tourist areas to us and display a medium to high rating. This program uses the TF-IDF method to calculate the weight of the data, the Cosine Similarity algorithm finds recommendations for tourist attractions based on existing datasets, and the Array data structure. Everyone always wants to do every activity effectively and efficiently. Even today, many people still spend their time looking for and choosing tourist attractions when they want to or are traveling to an area. Therefore, the author wants to create a program for recommending tourist sites that can help tourists find tourist sites easily without having to waste time checking one by one ratings and reviews from other visitors, as well as the location of tourist attractions closest to them

Item Type:	Thesis (Skripsi)
Subjects:	000 Computer Science, Information and General Works
Divisions:	Faculty of Computer Science > Department of Informatics Engineering
Depositing User:	Mr Yosua Norman Rumondor
Date Deposited:	16 Apr 2024 02:07
Last Modified:	16 Apr 2024 02:07
URI:	http://repository.unika.ac.id/id/eprint/35168

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