OPTIMASI MESIN PENCARI BUKU FIKSI BERDASARKAN PADA SEMANTIK IMPRESI

Main Article Content

Rengga Asmara
Nur Rasyid Mubtada’i
Varidh Bimantara

Abstract




Fiction books are one of the most popular types of books in Indonesia. There are five most popular genres in fiction books, namely fantasy, mystery, romance, sci-fi, and thriller. Each genre gives a different impression and special interest for readers. It has become a common habit when people choose a fiction book based on the title, author, or publisher of the book. However, it does not provide precise search results. In this final project, an application system was developed to find out fiction books based on semantic impressions on the cover of the fiction book. The impression on each book cover is obtained through a survey of fiction book lovers in Indonesia. To get the results of the closeness between the user search and the impression survey data obtained through text mining, as well as the cosine similarity algorithm to calculate the most precise proximity value to the impression the user expects. The results of this system display a fiction book that has a closeness value with an error rate of 3.93% based on the impression expected by the user.




Article Details

Section
METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi