cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Gst. Ayu Vida Mastrika Giri
Contact Email
vida@unud.ac.id
Phone
+6285737241069
Journal Mail Official
jeliku@cs.unud.ac.id
Editorial Address
-
Location
Kota denpasar,
Bali
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 488 Documents
 45   46   47   48   49 
Klasifikasi Serangan Application Layer Denial of Service Menggunakan Support Vector Machine (SVM) dan Chi Square Putu Agus Prawira Dharma Yuda; Cokorda Pramartha; I Komang Ari Mogi
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 3 (2024): JELIKU Volume 12 No 3, February 2024
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.2023.v12.i03.p21

Abstract

In an era marked by widespread computer usage, security emerges as a critical focal point demanding meticulous attention. The spectrum of potential threats encompasses various methods of attacking computer systems, with Denial of Service (DoS) attacks being a prominent concern. This study delves into the enhancement of cybersecurity by implementing a system capable of discerning between DoS attack data and normal data, employing the Support Vector Machine (SVM) algorithm. To optimize the efficacy of the classification system, a strategic feature selection process is imperative. This research advocates for the utilization of the Chi-square method for this purpose, aiming to eliminate irrelevant features and thereby enhance system performance. The Support Vector Machine algorithm, hinging on hyperplanes for classification, gains efficiency through judicious feature selection. The empirical findings of this research unveil that employing Chi-square feature selection significantly elevates the performance of the classification system when dealing with application layer attacks. Remarkably, this enhancement is achieved without compromising the accuracy of the system. Specifically, the classification of DoS application layer attacks using SVM in tandem with Chi-square yielded identical accuracy results compared to using SVM alone. The average accuracy reached an impressive 99.9995%, with a processing time of 6.08 minutes. In contrast, the classification system without feature selection consumed a comparatively longer processing time of 6.85 minutes. This underscores the efficacy of Chi-square feature selection in optimizing the performance of cybersecurity systems, demonstrating a streamlined approach to safeguarding computer networks from malicious threats.
Analisis Serangan Cross Site Scripting (XSS) Pada Website OASE Menggunakan Metode OWASP Muhammad Arrysatrya Yusuf Putranda; I Komang Ari Mogi; I Gusti Ngurah Anom Cahyadi Putra; I Made Widiartha
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 13 No 1 (2024): JELIKU Volume 13 No 1, August 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Berkembangnya internet membuat majunya era teknologi digitalisasi, dimana hampir seluruh sektor kini dapat diakses secara digital, termasuk pendidikan. Salah satunya adalah Universitas Udayana yang memiliki LMS bernama Online Academic Service for Elearning (OASE) yang digunakan dalam proses pembelajaran di lingkungan Universitas Udayana. Namun perkembangan ini diikuti oleh potensi ancaman, dengan terwujudnya digitalisasi yang berarti hal tersebut dapat diakses oleh siapa saja, termasuk orang yang merusak suatu sistem. Salah satu jenis serangan yang banyak ditemukan adalah Cross Site Scripting (XSS). Untuk memastikan keamanan LMS OASE milik Universitas Udayana, perlu dilakukan Analisis Kerentanan terutama pada serangan XSS yang dilakukan dengan uji penetrasi menggunakan metode OWASP. Dari hasil pengujian ditemukan bahwa meskipun OASE memiliki beberapa potensi celah kerentanan, namun hanya satu fitur saja yang dikonfirmasi memiliki kerentanan, sedangkan fitur lainnya berhasil diproteksi dengan adanya fungsi filtering serta kontrol pada eksekusi script dari pengguna.
Load Time Optimization on React Website using Incremental Static Regeneration with NextJS Gede Sudimahendra; Luh Arida Ayu Rahning Putri
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 2 (2023): JELIKU Volume 12 No 2, November 2023
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.2023.v12.i02.p20

Abstract

There’s a lot of tools that can be used to build or develop a website. Starting from basic HTML CSS and JavaScript to the use of UI Framework such as React, Angular, Vue JS or Svelte But, the use of UI Framework doesn’t come with no cons. UI Framework like React, use virtual DOM, instead of modifying the DOM directly, so when the first time application load, the framework needs to load library to modify the virtual DOM, before the page can load. This can leads to slow first loading time. This paper research performance improvement when using ISR ( Incremental Static Regeneration ) in NextJS
Implementasi CI/CD Pada Microservices Untuk Meningkatkan Availability Pada Pemrosesan Big Data Kompiang Gede Sukadharma; I Putu Gede Hendra Suputra
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 3 (2024): JELIKU Volume 12 No 3, February 2024
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.2023.v12.i03.p12

Abstract

Big Data Processing needed a reliable system that not let the data loss. But sometimes we need to make the system down for a while because we need to push the newest changes of the system. The automation will help us achieve that. Continuous Integration and Continuous Deployment help us to reduce the downtime and increase the availability of the system. Thus, the implication will be led to reduce of data loss. This research focusses on the implementation of CI/CD Pipeline on single-point-of-failure service on Microservices Architecture. This research use Load-Testing to measure data loss on certain amount of time. The result on this research show that implementing CI/CD Pipeline on the Microservices that we made, make the down time will be less than 45 Second with 20 Virtual user who send the data.
Implementasi Metode Fuzzy Logic untuk Mendeteksi Asap Dupa di Pasar Tradisional Bali Berbasis IoT Ira Arituddiniyah; Cokorda Pramartha; I Dewa Made Bayu Atmaja Darmawan; I Gede Surya Rahayuda
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 13 No 1 (2024): JELIKU Volume 13 No 1, August 2024
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research employs Fuzzy Logic for incense smoke detection in Bali's traditional markets, supported by IoT. It aims to develop a system for automatic identification, user reminders, and online monitoring. By using Fuzzy Logic, the system assesses smoke concentration, enabling appropriate responses. IoT integration facilitates object connectivity and communication. The outcome is a web platform for smoke monitoring, notifications, and remote device control. This study innovatively merges IoT with local wisdom, offering a valuable contribution.
Identifikasi Plat Nomor Kendaraan Di Indonesia Menggunakan Metode Convolutional Neural Network (CNN) I Nyoman Restu Muliarta; I Gede Santi Astawa
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 2 (2023): JELIKU Volume 12 No 2, November 2023
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.2023.v12.i02.p11

Abstract

Seiring dengan perkembangan zaman, teknologi juga semakin berkembang. Contohnya dengan menggunakan suatu system yang mampu mengidentifikasi plat nomor kendaraan secara efisien dan akurat. Contoh metode yang digunakan adalah metode CNN. CNN atau Convolutional Neural Network merupakan salah satu metode deep learning yang sering digunakan untuk pengenalan citra. Hal ini disebabkan karena metode CNN berkonsep system pengenalan citra pada visual cortex manusia sehingga memiliki kemampuan mengolah citra informasi. Dengan menggunakan metode ini, dapat mengenali simbol pada plat nomor kendaraan. Penelitian ini menggunakan beberapa sampel gambar plat kendaraan yang diambil dari berbagai media. Berdasarkan hasil penelitian yang telah dilakukan maka diperoleh hasil, yaitu tingkat keakuratan dalam mendeteksi setiap karakter pada plat kendaraan.
Perbandingan Kinerja Algoritma C4.5 dan Naive Bayes Untuk Klasifikasi Penerima Beasiswa Studi Kasus di SMKS 2 Adi Luhur Lia Susanti; Khoirunnisa .
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 4 (2024): JELIKU Volume 12 No 4, May 2024
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.2024.v12.i04.p16

Abstract

In advancing the Nation and State, a smart generation is needed. One of the most important factors is education, but many students who have great abilities and potential cannot continue school because they are not financially capable but there are also many able-bodied students who get scholarships. In the educational environment, especially schools, there should be some rules or classification in determining students who receive scholarships Therefore, in this study, a comparison of the C4.5 and Naïve Bayes algorithms was applied to the data of students who received scholarships. This study aims to find a pattern that can determine the award of scholarships with predetermined criteria, in the selection of prospective scholarship recipients at SMKS 2 Adi Luhur using the Naive Bayes Algorithm and the C 4.5 Algorithm. The data will be tested using k-fold cross validation (k=10). From the comparison results, the results of the Naïve Bayes accuracy are higher than the C 4.5 Algorithm. The results obtained from the comparison of the two algorithms are the Naïve Bayes algorithm has an accuracy rate of 94.52% and the C4.5 algorithm has an accuracy rate of 92.52%. Keywords: Scholarship, C4.5 Algorithm, Naïve Bayes, K-Fold Cross Validation, Classification
Bahasa Inggris Ngakan Putu Widyasprana; Ida Bagus Made Mahendra
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 2 (2023): JELIKU Volume 12 No 2, November 2023
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.2023.v12.i02.p02

Abstract

Literacy is the ability of Indonesian language competence on the basis of reading and writing. Literacy skills in Indonesia are quite lagging behind other nations in the world. To improve literacy skills, we use the SAC (All Smart Children) approach with TaRL (Teaching at Right Level) learning. This approach can be realized by using one of the clustering methods, namely the K-Means Algorithm. The grouping will use data from the implementation of the literacy program at SMP Santi Yasa Petak in the span of 3 months and the modeling using the Rapid Miner application. The results obtained divided students into 2 clusters, namely a cluster of students who were able to carry out a literacy program of 8 people and a cluster of students who had not been able to carry out a literacy program of 5 people.
Perbandingan Metode Ensemble Learning Random Forest Dan Adaboost Pada Pengenalan Chord Instrumen Piano Dan Gitar I Dewa Agung Adwitya Prawangsa; Dr. Anak Agung Istri Ngurah Eka Karyawati
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 4 (2024): JELIKU Volume 12 No 4, May 2024
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.2024.v12.i04.p07

Abstract

Artikel ini menyajikan analisis komprehensif tentang algoritma Random Forest dan Adaboost untuk mengklasifikasikan akord musik, dengan fokus pada ekstraksi fitur dan optimasi model. Distribusi data asli, termasuk panjang sinyal audio dan distribusi kelas, diperiksa, mengungkapkan karakteristik yang konsisten di seluruh dataset mayor dan minor. Koefisien Cepstral Frekuensi Mel (MFCC) diekstraksi dengan parameter yang telah ditentukan sebelumnya, memastikan konsistensi ekstraksi fitur. Normalisasi fitur dan oversampling menggunakan SMOTE dilakukan untuk menangani ketidakseimbangan kelas. Metrik evaluasi, termasuk akurasi, presisi, recall, dan F1-score, digunakan untuk menilai kinerja model. Hasilnya menunjukkan keunggulan Random Forest dalam akurasi, presisi, dan recall dibandingkan Adaboost. Selanjutnya, penerapan optimasi RandomizedSearchCV meningkatkan kinerja kedua model, dengan Random Forest mencapai akurasi 0.84 dan Adaboost mencapai 0.80. Matriks kebingungan mengilustrasikan akurasi prediksi yang lebih tinggi dari Random Forest untuk kelas positif dan negatif dibandingkan Adaboost. Temuan ini menegaskan efektivitas Random Forest dalam mengklasifikasikan akord musik dengan akurasi tinggi dan menyoroti pentingnya optimasi hiperparameter dalam meningkatkan kinerja model klasifikasi.
Implementasi Long-Short Term Memory (LSTM) pada Klasifikasi Kategori Berita Anak Agung Ngurah Andhika Satrya Nugraha; Ida Bagus Made Mahendra
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 12 No 3 (2024): JELIKU Volume 12 No 3, February 2024
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.2023.v12.i03.p07

Abstract

Karena banyaknya berita yang ada saat ini, diperlukan sebuah cara untuk memilah berita yang ingin dilihat. Salah satu cara untuk memilah berita adalah dengan membagi berita ke dalam beberapa kategori. Saat ini pembagian kategori pada berita masih dilakukan secara manual. Penelitian ini membahas tentang implementasi metode Long-Short Term Memory (LSTM) untuk mengklasifikasikan berita ke dalam 7 kategori. Terdapat dua model yang diimplementasikan pada penelitian ini, yaitu model LSTM dan model Bidirectional LSTM. Model LSTM yang dibuat berhasil mengklasifikasikan berita dengan akurasi sebesar 85.36%, model Bidirectional LSTM juga berhasil mengklasifikasikan berita dengan akurasi sebesar 84.15%.

Page 48 of 49 | Total Record : 488

 45   46   47   48   49 

Filter by Year

2012 2024


Reset
Filter By Issues
All Issue Vol 13 No 1 (2024): JELIKU Volume 13 No 1, August 2024 Vol 12 No 4 (2024): JELIKU Volume 12 No 4, May 2024 Vol 12 No 3 (2024): JELIKU Volume 12 No 3, February 2024 Vol 12 No 2 (2023): JELIKU Volume 12 No 2, November 2023 Vol 12 No 1 (2023): JELIKU Volume 12 No 1, August 2023 Vol 11 No 4 (2023): JELIKU Volume 11 No 4, May 2023 Vol 11 No 3 (2023): JELIKU Volume 11 No 3, February 2023 Vol 11 No 2 (2022): JELIKU Volume 11 No 2, November 2022 Vol 11 No 1 (2022): JELIKU Volume 11 No 1, August 2022 Vol 10 No 4 (2022): JELIKU Volume 10 No 4, May 2022 Vol 10 No 3 (2022): JELIKU Volume 10 No 3, February 2022 Vol 10 No 2 (2021): JELIKU Volume 10 No 2, November 2021 Vol 10 No 1 (2021): JELIKU Volume 10 No 1, Agustus 2021 Vol 9 No 4 (2021): JELIKU Volume 9 No 4, Mei 2021 Vol 9 No 3 (2021): JELIKU Volume 9 No 3, Februari 2021 Vol 9 No 2 (2020): JELIKU Volume 9 No 2, November 2020 Vol 9 No 1 (2020): JELIKU Volume 9 No 1, Agustus 2020 Vol 8 No 4 (2020): JELIKU Volume 8 No 4, Mei 2020 Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020 Vol 8 No 2 (2019): Jeliku Volume 8 No 2, November 2019 Vol 8 No 1 (2019): JELIKU Volume 8 No 1, Agustus 2019 Vol 7 No 4 (2019): JELIKU Volume 7 No 4, Mei 2019 Vol 7 No 3 (2019): JELIKU Volume 7 No 3, Februari 2019 Vol 7 No 2 (2018): JELIKU Volume 7 No 2, 2018 Volume 1 No 2 - Nopember 2012 Volume 1 No 1 - Agustus 2012 More Issue