PEMFILTERAN DAN PERANKINGAN INFORMASI MENGGUNAKAN PENDEKATAN MULTI CRITERIA DECISION MAKING UNTUK SISTEM REKOMENDASI OBJEK WISATA
| Main Authors: | , KARINA AULIASARI, , Ir. P. Insap Santosa, M.Sc., Ph.D. |
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| Format: | Thesis NonPeerReviewed |
| Terbitan: |
[Yogyakarta] : Universitas Gadjah Mada
, 2012
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| Subjects: | |
| Online Access: |
https://repository.ugm.ac.id/99455/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=55948 |
Daftar Isi:
- The increase upon internet use by the global community contributes a significant effect in improving the number of tourists� visits. Today, the transmission of information on tourism through internet has been implemented through several systems, among of them are e-Tourism, tourism virtual reality mapping, tourism reservation system, location-based tourism services and tourism recommender system. Of all those varied systems, tourism recommender system plays awfully vital roles because the system is able to provide any tourism information according to the interest and capability of the tourist �to be�. However, the development of the tourism recommender system, in fact, faces some problems, among of them are the complexity of the information contained in the tourism objects, and the difficult information extraction related to the existence of the tourism objects themselves. The information upon tourism objects holds many various aspects in relation to the services which the tourists to be will receive, such as completeness facilities of the tourism objects, easy access to the tourism objects, security guarantee, and so on and so forth. Therefore, we need the right method to accommodate those aspects mentioned above. In this study, the methods of weighted sum model (WSM) weighted product model (WPM) are implemented to develop the system of tourism object recommendation to be able to handle many alternatives and aspects in relation to tourism objects� judgments. From analysis result of WSM and WPM algorithm obtained main characteristic of two algorithms to generate tourism object recommendations. The experiment result of tourism object recommendations accuracy show that WSM algorithm is capable to ensure the accuracy result is higher than WPM algorithm. While the experiment result of time consumption to generate tourism object recommendations show that WPM algorithm take less time than WSM algorithm. The prototype of tourism object recommender system able to accommodate various criteria that is used in tourism object assessment process from various dataset.