Text

KLASIFIKASI MULTI LABEL PADA GENRE NOVEL BERDASARKAN COVER MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK

---

Penilaian

---

Fiction book classification based on its cover become a particularly exciting research topic in recent years. There exists a wide variety of book genres, and the design on its cover as a graphic designs vary in many different ways such as colors, styles, textual information, even for books of the same genre, make it an challenging task to do fiction book genre classification based on its cover. In some related work before, classification system for define genre of fiction book practice still limited with traditional classification, where a fiction book will only be classified into one genre, whereas in real situations a novel can be classified into more than one genre. In addition, another problem lies in the data redundancy in several categories of the dataset. Therefore, in this study will try to solved the two problems, the first by applying multi-label classification practice with a Convolutional Neural Network model in order to classify the fiction book genre information based on the cover and provide the correct genre classification results, then the second we will collect fiction book’s cover image as new dataset using web scraping technique, so the data can be used for multi label classification purpose. The Convolutional Neural Network model used in this study is the VGG16 architecture. The results of experiments conducted in this study indicate that the VGG16 model that has been trained using the dataset that has been collected by the author can perform a multi label classification to determine the novel genre in the testing process properly and obtain a fairly good F1 Score.

---

Availability

Inventory Code	Barcode	Call Number	Location	Status
2207000179	T62726	T627262022	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

-

Call Number

T627262022

Publisher

Inderalaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022

Collation

xx, 94 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

-

Classification

004.650 7

Content Type

-

Media Type

-

Carrier Type

-

Edition

-

Subject(s)

Jurusan Teknik Informatika
Jaringan Komunikasi Komputer

Specific Detail Info

-

Statement of Responsibility

SEPTA

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment