ASBHI, AGUNG DIO (2023) PERANCANGAN SISTEM REKOMENDASI PENCARIAN KEDAI KOPI DI BOGOR MENGGUNAKAN CONTENT BASED FILLTERING. S1 thesis, Universitas Mercu Buana.
|
Text (COVER)
01 COVER.pdf Download (426kB) | Preview |
|
|
Text (ABSTRAK)
02 ABSTRAK.pdf Download (158kB) | Preview |
|
![[img]](https://repository.mercubuana.ac.id/style/images/fileicons/text.png) |
Text (BAB I)
03 BAB 1.pdf Restricted to Registered users only Download (153kB) |
|
|
Text (BAB II)
04 BAB 2.pdf Restricted to Registered users only Download (220kB) |
|
|
Text (BAB III)
05 BAB 3.pdf Restricted to Registered users only Download (149kB) |
|
|
Text (BAB IV)
06 BAB 4.pdf Restricted to Registered users only Download (546kB) |
|
|
Text (BAB V)
07 BAB 5.pdf Restricted to Registered users only Download (126kB) |
|
|
Text (DAFTAR PUSTAKA)
08 DAFTAR PUSTAKA.pdf Restricted to Registered users only Download (146kB) |
|
|
Text (LAMPIRAN)
09 LAMPIRAN.pdf Restricted to Registered users only Download (1MB) |
Abstract
The atmosphere is very comfortable and the prices are affordable for all groups, of course coffee places or coffee shops are often used as places to work, hang out, meet, hold events and so on. With so many coffee shops in Bogor, people rarely know about coffee shops that are more interesting in terms of the name of the coffee shop, place, prices, hours and menu. So in solving this problem, analysis can be carried out on coffee shop data in Bogor using the Content Based Filtering method by utilizing TF-IDF weighting and the cosine similarity method to determine the similarity between features entered by the user. The application of this algorithm is expected to provide information regarding recommendations for coffee shops in Bogor based on the name of the coffee shop, place, price, hours and menu. These recommendations can later be used as a reference for the public in deciding which coffee shop to visit. The results of this research show that the Content Based Filtering Algorithm can provide new information by processing coffee shop data in Bogor using the Python programming language with a precision value of 88%. The results of this research provide new information that can help people in finding the best coffee shop. Keywords: Coffee Shop, Bogor, Recommendation System, TF-IDF, Cosine Similarity Suasana yang sangat nyaman dan harga yang affordable untuk semua kalangan tentunya tempat kopi atau kedai kopi sering kali dijadikan tempat bekerja, nongkrong, rapat, pelaksanaan acara dan lain sebagainya. Dengan banyak nya kedai kopi yang ada di Bogor jarang masyarakat yang tahu akan kedai kopi yang lebih menarik baik dari nama kedai kopi,tempat, harga, jam dan menu. Maka dalam penyelesaian masalah tersebut dapat dilakukan analisis terhadap data kedai kopi di Bogor menggunakan metode Content Based Filtering dengan memanfaatkan pembobotan TF-IDF dan metode cosine similarity untuk menentukan kemiripan antar fitur yang dimasukkan user. Penerapan Algoritma tersebut diharapkan dapat memberikan informasi mengenai rekomendasi kedai kopi di Bogor berdasarkan nama kedai kopi,tempat, harga, jam dan menu. Rekomendasi tersebut nantinya dapat digunakan sebagai acuan masyarakat dalam memutuskan keputusan kedai kopi yang akan dikunjungi. Hasil dari penelitian ini menunjukkan bahwa Algoritma Content Based Filtering dapat memberikan informasi baru dengan melakukan pengolahan data kedai kopi di Bogor menggunakan bahasa pemrograman Python dengan nilai precision 88%. Hasil dari penelitian ini memberikan informasi baru yang dapat membantu masyarakat dalam mencari kedai kopi terbaik. Kata Kunci : Kedai Kopi, Bogor, Sistem Rekomendasi, TF-IDF, Cosine Similarity
Actions (login required)
 |
View Item |
