Aplikasi Rekomendasi Tempat Makan Menggunakan Algoritma Slope One pada Platform Android

https://doi.org/10.22146/ijccs.15558

Dharma Pratama(1), Seng Hansun(2*)

(1) Universitas Multimedia Nusantara
(2) Universitas Multimedia Nusantara
(*) Corresponding Author

Abstract


 Food is one of the basic needs for human being. The needs of food will always increase unanimous with the number of people, so that many restaurants appear. Because of there are so many restaurants, it can arise a confusion when we want to choose a restaurant to eat. Therefore, an application which can give a restaurant recommendation will be built in this research. The recommendation given by the system is calculated using Slope One algorithm and the restaurants database is gathered from Google Places API. Slope One algorithm make the recommendation by summing the rating of a restaurants with the difference average to other restaurants. The application also had been tested to the user by using J.R.Lewis questionnaire with questions categories of application usefulness, information quality, and user interface quality. The results from the testing are user find the application useful to give the proper restaurant recommendation, the information quality is good, and the user interface quality is also good.

Keywords


Android, Google Places API, Recommendation System, Slope One algorithm, Restaurants

Full Text:

PDF


References

Shodiqin, A, 2015, Jenis-Jenis dan Contoh Kebutuhan Manusia Primer, Skunder dan Tersier, http://www.ilmuekonomi.net/2015/12/jenis-jenis-dan-contoh-kebutuhan-manusia-primer-skunder-dan-tersier.html, diakses tgl 8 Maret 2016.

Kim, B. M., Li, Q., Park, C. S., Kim, S. G., dan Kim, J.Y., 2006 , A New Approach for Combining Content-Based and Collaborative Filters, Journal of Intelligent Information Systems, Vol.27, Issue 1, hal.79-91.

Sarwar, B., Karypis, G., Konstan, J., dan Riedl, J., 2001, Item-Based Collaborative Filtering Recommendation Algorithms, Proceeding of WWW10, Hong Kong, May 1-5.

Wirawan, V., Hansun, S., dan Nugroho, H. T., 2014, Implementasi Algoritma Squeezer dan Term Frequency Ranking dalam Pembangunan Sistem Rekomendasi Tempat Makan, ULTIMA Computing, Vol.VI, No.1, hal.25-32.

Melville, P. dan Sindhwani, V., 2010, Recommender Systems, Sammut, C. dan Webb, G. I. (ed.): Encyclopedia of Machine Learning, Springer, USA.

Jiang, T. dan Lu, W., 2013, Improved Slope One Algorithm Based on Time Weight, Applied Mechanics and Materials, Vols.347-350, hal.2365-2368.

Clevesy, L., 2010, Slope-one Recommender - Exclusive Article from Mahout in Action, https://dzone.com/articles/slope-one-recommender, diakses tgl 15 Maret 2015.

Masruri, F. dan Mahmudy, W. F., 2007, Personalisasi Web E-Commerce Menggunakan Recommender System dengan Metode Item-based Collaborative Filtering, Kursor, Vol.3, No.1, hal.1-12.

Hendryadi, 2012, Menentukan Ukuran Sampel Sederhana, http://teorionline.net/menentukan-ukuran-sampel-menurut-para-ahli/, diakses tgl 7 Juli 2015.

Lewis, J. R., 1995, IBM Computer Usability Satisfaction Questionnaires: Psychometric Evaluation and Instructions for Use, International Journal of Human-Computer Interaction, Vol.7, Issue 1, hal.57-78.

Jainuri, M., 2015, Skala Pengukuran, http://www.academia.edu/5077784/Skala_Pengukuran, diakses tgl 13 Agustus 2015.



DOI: https://doi.org/10.22146/ijccs.15558

Article Metrics

Abstract views : 7484 | views : 8752

Refbacks

  • There are currently no refbacks.




Copyright (c) 2017 IJCCS - Indonesian Journal of Computing and Cybernetics Systems

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.



Copyright of :
IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
ISSN 1978-1520 (print); ISSN 2460-7258 (online)
is a scientific journal the results of Computing
and Cybernetics Systems
A publication of IndoCEISS.
Gedung S1 Ruang 416 FMIPA UGM, Sekip Utara, Yogyakarta 55281
Fax: +62274 555133
email:ijccs.mipa@ugm.ac.id | http://jurnal.ugm.ac.id/ijccs



View My Stats1
View My Stats2