Nurifan, Farza (2019) Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) untuk Mengoptimalkan Pemilihan Restoran berdasarkan Aspek dan Sentimen Menggunakan Modified Double Propagation. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Sekarang ini banyak anak muda yang sering kebingungan dalam menentukan restoran sebagai tempat untuk berkumpul bersama teman. Mereka biasanya mencari informasi tentang suatu restoran melalui aplikasi peta online untuk melihat satu-persatu review dari restoran tersebut apakah harganya bersahabat, makanannya enak, tempatnya nyaman, dan pelayanannya baik atau tidak. Namun hal itu tidak mungkin untuk dilakukan apabila terdapat banyak restoran yang masing-masing memiliki ratusan bahkan ribuan review. Oleh karena itu perlu suatu sistem yang dapat mengoptimalkan pemilihan restoran yang sesuai dengan kriteria pengguna. Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) adalah salah satu algoritma yang berguna untuk membantu mengoptimalkan pengambilan keputusan. Algoritma tersebut memerlukan masukan berupa kriteria dan nilai dari kriteria tersebut. Kriteria yang kami gunakan yaitu: Ambience; Food; Service; dan Prices. Kemudian nilai dari tiap kriteria kami tentukan berdasarkan aspek dan sentimen dari review restoran dengan menggunakan metode Modified Double Propagation (MDP) dan semantic similarity untuk kategorisasi aspek serta opinion lexicon untuk analisis sentimen. Terakhir, nilai kriteria dikalikan dengan bobot kriteria yang ditentukan oleh masukan dari pengguna. Hasil uji coba yang dilakukan menunjukkan bahwa sistem kami mampu mengoptimalkan pemilihan restoran dengan memberikan rekomendasi restoran yang tepat. Selain itu hasil kategorisasi aspek kami mampu meningkatkan F1measure sebesar 15% dari penelitian sebelumnya serta hasil analisis sentimen kami dapat mencapai F1measure sebesar 82%.
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Today many young people are often confused in determining restaurants as a place to gather with friends. They usually look for information about a restaurant through an online map application to see one by one a review of the restaurant whether the price is low, the food is good, the place is comfortable, and the service is good or not. But that is not possible if there are many restaurants, each of which has hundreds or even thousands of reviews. Therefore, we need a system that can optimize the restaurant selection that suitable to the user's criteria. Multi-Objective Optimization on the Base of Ratio Analysis (MOORA) is one algorithm that is useful to help optimize decision making. The algorithm requires input in the form of criteria, values of these criteria, and weighting criteria. The criteria we use are: Ambience; Food; Service; and Prices. Then the values of each of our criteria are determined based on aspects and sentiments of restaurant reviews using the Modified Double Propagation (MDP) method and semantic similarity for aspect categorization and Lexicon Opinion for sentiment analysis. Finally, the criteria weight is determined by the input from the user. The results show that our system is able to optimize the restaurant selection by providing appropriate restaurant recommendations. Besides that, the results of our aspect categorization were able to increase the F1measure by 15% from previous studies and the results of our sentiment analysis could reach F1measure by 82%.
| Item Type: | Thesis (Other) |
|---|---|
| Subjects: | T Technology > T Technology (General) > T11 Technical writing. Scientific Writing T Technology > T Technology (General) > T58.62 Decision support systems |
| Divisions: | Faculty of Information Technology > Informatics Engineering > 55201-(S1) Undergraduate Thesis |
| Depositing User: | Farza Nurifan |
| Date Deposited: | 23 Jul 2026 03:30 |
| Last Modified: | 23 Jul 2026 03:30 |
| URI: | http://repository.its.ac.id/id/eprint/68614 |
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