Application of Data Mining Techniques on Tourist Expenses in Malaysia
Tourism plays an important role in Malaysia’s economic development as it can boost business opportunity in its surrounding economic. By apply data mining on tourism data for predicting the area of business opportunity is a good choice. Data mining is the process that takes data as input and produces...
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| Format: | Article |
| Language: | English |
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University of Baghdad, College of Science for Women
2021-03-01
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| Series: | مجلة بغداد للعلوم |
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| Online Access: | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/5928 |
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| author | Miao Cai Tan Shi An |
| author_facet | Miao Cai Tan Shi An |
| author_sort | Miao Cai |
| collection | DOAJ |
| description | Tourism plays an important role in Malaysia’s economic development as it can boost business opportunity in its surrounding economic. By apply data mining on tourism data for predicting the area of business opportunity is a good choice. Data mining is the process that takes data as input and produces outputs knowledge. Due to the population of travelling in Asia country has increased in these few years. Many entrepreneurs start their owns business but there are some problems such as wrongly invest in the business fields and bad services quality which affected their business income. The objective of this paper is to use data mining technology to meet the business needs and customer needs of tourism enterprises and find the most effective data mining technology. Besides that, this paper implementation of 4 data mining classification techniques was experimented for extracting important insights from the tourism data set. The aims were to find out the best performing algorithm among the compared on the results to improve the business opportunities in the fields related to tourism. The results of the 4 classifiers correctly classifier the attributes were JRIP (84.09%), Random Tree (83.66%), J48 (85.50%), and REP Tree (82.47%). All the results will be analyzed and discussed in this paper. |
| format | Article |
| id | doaj-art-e9481ab3f8fd4d14a11ac915027059c9 |
| institution | DOAJ |
| issn | 2078-8665 2411-7986 |
| language | English |
| publishDate | 2021-03-01 |
| publisher | University of Baghdad, College of Science for Women |
| record_format | Article |
| series | مجلة بغداد للعلوم |
| spelling | doaj-art-e9481ab3f8fd4d14a11ac915027059c92025-08-20T03:19:10ZengUniversity of Baghdad, College of Science for Womenمجلة بغداد للعلوم2078-86652411-79862021-03-01181(Suppl.)10.21123/bsj.2021.18.1(Suppl.).0737Application of Data Mining Techniques on Tourist Expenses in MalaysiaMiao Cai0Tan Shi An1University Sains Malaysia, China.University Sains Malaysia, Malaysia. Tourism plays an important role in Malaysia’s economic development as it can boost business opportunity in its surrounding economic. By apply data mining on tourism data for predicting the area of business opportunity is a good choice. Data mining is the process that takes data as input and produces outputs knowledge. Due to the population of travelling in Asia country has increased in these few years. Many entrepreneurs start their owns business but there are some problems such as wrongly invest in the business fields and bad services quality which affected their business income. The objective of this paper is to use data mining technology to meet the business needs and customer needs of tourism enterprises and find the most effective data mining technology. Besides that, this paper implementation of 4 data mining classification techniques was experimented for extracting important insights from the tourism data set. The aims were to find out the best performing algorithm among the compared on the results to improve the business opportunities in the fields related to tourism. The results of the 4 classifiers correctly classifier the attributes were JRIP (84.09%), Random Tree (83.66%), J48 (85.50%), and REP Tree (82.47%). All the results will be analyzed and discussed in this paper.https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/5928Tourism, Data mining, Classification, JRIP, Random Tree, J48, REP Tree |
| spellingShingle | Miao Cai Tan Shi An Application of Data Mining Techniques on Tourist Expenses in Malaysia مجلة بغداد للعلوم Tourism, Data mining, Classification, JRIP, Random Tree, J48, REP Tree |
| title | Application of Data Mining Techniques on Tourist Expenses in Malaysia |
| title_full | Application of Data Mining Techniques on Tourist Expenses in Malaysia |
| title_fullStr | Application of Data Mining Techniques on Tourist Expenses in Malaysia |
| title_full_unstemmed | Application of Data Mining Techniques on Tourist Expenses in Malaysia |
| title_short | Application of Data Mining Techniques on Tourist Expenses in Malaysia |
| title_sort | application of data mining techniques on tourist expenses in malaysia |
| topic | Tourism, Data mining, Classification, JRIP, Random Tree, J48, REP Tree |
| url | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/5928 |
| work_keys_str_mv | AT miaocai applicationofdataminingtechniquesontouristexpensesinmalaysia AT tanshian applicationofdataminingtechniquesontouristexpensesinmalaysia |