Personalisasi Adaptif Informasi POI Menarik Menggunakan Collaborative Filtering pada Ponsel dengan NFC

EMANUEL RISTIAN H, Selo, S.T., M.T., M. Sc., Ph.D.; Ir. P. Insap Santosa, M. Sc., Ph.D.

2019 | Tesis | MAGISTER TEKNOLOGI INFORMASI

Upaya merekomendasikan POI melalui aplikasi panduan wisata mobile saat ini lebih populer dilakukan dengan mengadaptasi pengalaman kunjungan wisata saja daripada pengalaman mereka sebelum berkunjung ataupun setelahnya. Sementara itu, implementasi seperti ini tidak selalu mampu memicu rekomendasi Point-Of-Interest (POI) menarik, sehingga setiap saat seorang wisatawan harus siap beralih menggunakan aplikasi panduan wisata mobile lain atau bertahan terus meminta rekomendasi menarik dari satu aplikasi panduan wisata mobile yang digunakan saat itu. Adapun untuk mengatasi hal tersebut berbagai pengembangan telah dilakukan dengan baik, terutama dalam meningkatkan adaptasi terhadap wisatawan. Didasari implementasi teknik rekomendasi bernama Collaborative Filtering (CF) dalam hal pengumpulan data menurut siklus wisata, beragam aplikasi panduan wisata mobile telah diluncurkan bagi wisatawan yang didukung implementasi sensor ponsel terutama sensor bernama Near Field Communication (NFC) yang saat ini mulai populer digunakan sebagai salah satu cara intuitif untuk mendapatkan data lokasi wisatawan saat itu, disamping konfirmasi terhadap minat wisatawan yang juga dapat diketahui secara nyata. Demikian pula, penelitian ini sebagai upaya pengembangan dalam penelitian serupa ingin membuktikan bahwa terdapat perbedaan jumlah aktifitas wisata pada saat metode rekomendasi dengan personalisasi adaptif diimplementasikan pada aplikasi panduan wisata mobile yang mampu mudah digunakan wisatawan, daripada yang diimplementasikan tanpa personalisasi adaptif.

The effort to recommend POIs through mobile travel guide applications is now more popular by adapting the tourist visit experience rather than their experience before visiting or afterwards. Meanwhile, this kind of implementation is not always able to trigger attractive Point-Of-Interest (POI) recommendations, so that every time a tourist has to be ready to switch to using another mobile travel guide application or persist in asking for interesting recommendations from one mobile travel guide application that was used at that time. As for overcoming this, various developments have been carried out well, especially in increasing adaptation to tourists. Based on the implementation of a recommendation technique called Collaborative Filtering (CF) in terms of data collection according to the tourism cycle, a variety of mobile travel guide applications have been launched for tourists supported by the implementation of mobile sensors, especially sensors called Near Field Communication (NFC) which is currently becoming popular as an intuitive way to get the location data of tourists at that time, in addition to confirmation of the interest of tourists who can also be known in real time. Likewise, this research as a development effort in similar studies wants to prove that there are differences in the number of tourism activities when the method of adaptive personalization recommendations is implemented in mobile travel guide applications that can be easily used by tourists, rather than those implemented without adaptive personalization.

Kata Kunci : collaborative filtering, personalisasi, adaptif, mobile, near field communication