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INDONESIA
(JELIKU) Jurnal Elektronik Ilmu Komputer Udayana
Published by Universitas Udayana
ISSN : 23015373     EISSN : 26545101     DOI : https://doi.org/10.24843/JLK
Core Subject : Science,
Computer Science & IT
Aim and Scope: JELIKU publishes original papers in the field of computer science, but not limited to, the following scope: Computer Science, Computer Engineering, and Informatics Computer Architecture Parallel and Distributed Computer Computer Network Embedded System Human—Computer Interaction Virtual/Augmented Reality Computer Security Software Engineering (Software: Lifecycle, Management, Engineering Process, Engineering Tools and Methods) Programming (Programming Methodology and Paradigm) Data Engineering (Data and Knowledge level Modeling, Information Management (DB) practices, Knowledge Based Management System, Knowledge Discovery in Data) Network Traffic Modeling Performance Modeling Computer Security IT Governance Networking Technology Robotic Instrumentation Information Search Engine Multimedia Security Information Retrieval Mobile Processing Natural Language Processing Artificial intelligence & soft computing and their applications Neural networks Machine Learning Reasoning and evolution Intelligence applications Computer vision and speech understanding Multimedia and cognitive informatics Data mining and machine learning tools, heuristic and AI planning strategies and tools, computational theories of learning
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 13 Documents
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Search results for , issue "Vol 8 No 2 (2019): Jeliku Volume 8 No 2, November 2019" : 13 Documents clear
Klasifikasi Penyakit Kanker Payudara Menggunakan Jaringan Syaraf Tiruan dan Seleksi Fitur Gorianto, Frisca Olivia; Santi Astawa, I Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 2 (2019): Jeliku Volume 8 No 2, November 2019
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2019.v08.i02.p01

Abstract

Breast cancer is still one of the leading causes of death in the world. Prevention can be done if the cancer can be recognized early on whether the cancer is malignant or benign. In this study, a comparison of malignant and benign cancer classifications was performed using two artificial neural network methods, which are the Feed-Forward Backpropagation method and the Elman Recurrent Neural Network method, before and after the feature selection of the data. The result of the study produced that Feed-Forward Backpropagation method using 2 hidden layers is better after the feature selection was performed on the data with an accuracy value of 99,26%.
Pengembangan Pemodelan Ontologi Semantik dalam Representasi Pengetahuan Instrumen Gamelan Bali Wardana, Made; Pramartha, Cokorda Rai Adi
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 2 (2019): Jeliku Volume 8 No 2, November 2019
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2019.v08.i02.p06

Abstract

Indonesia has many types of cultural and artistic heritage, which one is Balinese gamelan. Knowledge of Balinese gamelan still tends to be less explicitly collected. This result the cultural heritage knowledge, especially the Balinese gamelan challenging to be learned by the young and future Balinese generation. Therefore, the knowledge of Balinese gamelan information should be documented well, especially in the digital form. In this research, we develop an ontology for Balinese cultural heritage, specifically the gamelan Bali. This ontology can be used to capture, document, and represent knowledge surrounds the Balinese gamelan domain. The construction of the ontology model was carried out using the Methontology methodology. The gamelan ontology has 112 classes, 31 datatype properties, 53 object properties, and 289 instances. Further research needs to carry out in order to evaluate and improve the quality of ontology, and follow-up by the implementation into a semantic web-based application.
Segmentation of Certificate With Connected Component Labeling Method Jaya, Cokorda Gde Teresna; Arta Wibawa, I Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 2 (2019): Jeliku Volume 8 No 2, November 2019
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2019.v08.i02.p02

Abstract

Certificate is one of the documents that can be used as evidence of ownership or an event. For example, when certificate used as requirement to participate in an event. If a document is made as a requirement, of course the file verification process will be done. Seeing the time optimization problem when verifying the file, the authors carry out research by segmenting important data contained in a certificate as an initial step in the development of an automatic document verification system. The segmentation process carried out in this study uses the Connected Component Labeling method in determining the area to be segmented and Automatic Cropping to cut the results of the segmentation process. By using these two methods obtained an accuracy of 60% with a total of 15 pieces of test data

Page 2 of 2 | Total Record : 13

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