Website Katalog Promosi Makanan dan Minuman Dengan Sistem Rekomendasi Menggunakan User-Based Collaborative Filtering
Abstract
At this time, most people, when they hear or see the word "promo," will generally look for more in-depth information about it. This cannot be separated from the rapid development of information technology, which has penetrated social media. However, the development of social media has also resulted in difficulties in finding information on food and beverage promos that are still valid. Based on these problems, this research aims to help people find more efficient information about food and beverage promos from various vendors. Preliminary data were obtained by web scraping on similar websites, which have determined as many as 6215 data and tested on 50 respondents as rating users. Another advantage is providing alternative promo vendors that users may not have thought of before by using a user-based collaborative filtering algorithm so that the recommendations obtained are expected to be by customer behavior. This research can provide convenience in finding promos that are trending and valid. It was proven by 69.6% of the 50 respondents who answered strongly agreed in finding trending and valid promos. The recommendation feature can help provide options for users to find promo vendors that they may not have searched for before. This is evidenced by 50 respondents, where 72.3% of respondents strongly agree that the "promoku" website can find promos that have never been searched for.
Keywords: Web Scrapping, User Based, Collaborative Filtering, Recommendation
ABSTRAK
Pada saat ini, kebanyakan bila mendengar atau melihat kata “promo” umumnya akan mencari informasi lebih dalam mengenai hal tersebut. Ini tak lepas dari pesatnya perkembangan teknologi informasi, yang merambah ke media sosial. Namun perkembangan sosial media juga mengakibatkan kesulitan pencarian informasi promo makanan dan minuman yang masih berlaku. Berdasarkan masalah tersebut, maka penelitian ini bertujuan untuk membantu masyarakat dalam mencari informasi tentang promo makanan dan minuman dari berbagai vendor dengan lebih mudah. Data awal didapatkan dengan melakukan web scraping pada website sejenis yang sudah ditentukan sebanyak 6215 data dan diujicobakan pada 50 responden sebagai user pemberi rating. Kelebihan lainnya adalah bisa memberikan alternatif vendor promo yang mungkin sebelumnya tidak pernah terpikirkan oleh pengguna dengan menggunakan algoritma user-based collaborative filtering sehingga rekomendasi yang didapatkan diharapkan dapat sesuai dengan perilaku customer. Penelitian ini dapat memberikan kemudahan dalam mencari promo yang sedang tren dan valid. Terbukti dari 69,6% dari 50 responden yang menjawab sangat setuju dalam mencari promo yang sedang tren dan valid. Fitur rekomendasi dapat membantu memberikan opsi kepada pengguna menemukan vendor promo yang mungkin sebelumnya tidak pernah dicari. Hal ini dibuktikan dari 50 responden, dimana 72,3% responden menyatakan sangat setuju bahwa website promoku dapat menemukan promo yang belum pernah dicari sebelumnya.
Kata Kunci: Web Scrapping, User Based, Collaborative Filtering, Rekomendasi
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References
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