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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 488 Documents
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Penerapan Metode SAW dan TOPSIS dalam Sistem Rekomendasi Lowongan Kerja Bali
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 2 (2022): JELIKU Volume 11 No 2, November 2022
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.2022.v11.i02.p02

Abstract

Job information is important for humans, because almost every human being needs a job. The more unemployed human resources in an area, the higher the demand for job vacancies. Bali is one of the areas that has increased unemployment since the pandemic, Bali has a workforce of 2.6 million who need work. To help Bali job seekers find jobs that match their criteria. In this study, a Bali job vacancy recommendation system was built based on the preferences of respondents residing in Bali. This system will apply the SAW-TOPSIS method in providing recommendations. For the development method, the Waterfall Model will be used. Job vacancies data will be collected on a secondary basis via the internet. The criteria and weighting in the recommendations are based on the results of the respondent's survey. The results of this study note that the application of the SAW-TOPSIS method in the Bali job vacancy recommendation system is in accordance with manual calculations and for direct testing to users using usability testing with 20 respondents the results are 83.39% which shows the system has a very good usability value.
Analisis Sentimen Ulasan E-Commerce Pakaian Berdasarkan Kategori dengan Algoritma Convolutional Neural Network
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 1 (2022): JELIKU Volume 11 No 1, August 2022
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.2022.v11.i01.p01

Abstract

Almost everyone looks at reviews before deciding to buy an item in e-commerce. Consumers say that online reviews influence their purchasing decisions. Based on these data, consumers need sentiment reviews to make a decision to choose a product/service. However, the results of the sentiment analysis are still less specific, so the review classification process is carried out based on the review category. Sentiment classification process based on clothing category is carried out using the Convolutional neural network method. The amount of data used is 3384 data with 3 categories. The category classification model shows good performance. When evaluated with testing data (unseen data), the accuracy value is 88%, the precision value is 88%, recall is 88% and the f1-score is 88%. For the sentiment classification model with the bottoms category, the resulting accuracy value is 80%, precision is 81%, recall is 80%, and f1-score is 79%. For the sentiment classification model with the dresses category, the accuracy value is 81%, precision is 81%, recall is 81%, and f1-score is 81%. For sentiment classification with the tops category the resulting accuracy value is 77%, precision is 77%, recall is 77%, and f1-score is 77%.
Klasifikasi Tifus dan Demam Berdarah Menggunakan Algoritma Pseudo Nearest Neighbor
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 1 (2022): JELIKU Volume 11 No 1, August 2022
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.2022.v11.i01.p16

Abstract

Typhus and dengue fever are diseases that often occur in Indonesia. The spread of these two diseases is relatively fast with similar symptoms. This could be a fatal thing if there is a misdiagnosis. Therefore, an application was developed to assist in the classification of typhus and dengue fever based on the patient's clinical symptoms using the PNN (Pseudo Nearest Neighbor) algorithm. This application receives input in the form of clinical symptoms experienced by the patient, then a preprocessing process is carried out to convert user input into discrete data, and the results are processed in classification using the PNN method. From the validation process with 5-fold cross validation obtained the best k value is k=6. Then, the accuracy testing process concluded that the accuracy of the classification process for typhoid and dengue fever with the PNN method is 68,97%. Then, from 25 respondents in the user acceptance test obtained that 88.4% of respondents strongly agree with the application design, 87.6% respondents strongly agree with the ease of application, and 86.6% respondents strongly agree with the efficiency provided by the application.
Penerapan Metode Adaptive Neuro Fuzzy Inference System (ANFIS) Dengan Membership function Tipe Gaussian dan Generalized Bell Dalam Prediksi Harga Tertinggi Saham
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 1 (2022): JELIKU Volume 11 No 1, August 2022
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.2022.v11.i01.p12

Abstract

Banyak kalangan yang memiliki modal saat ini beramai-ramai memborong saham di stock market dengan harapan harga saham tersebut akan naik saat pandemi Covid-19 berakhir. Sebagai seseorang yang ingin mencoba berinvestasi di stock market harus mampu memperkirakan untung dan rugi dari pembelian saham. Salah satu cara yang dapat membantu pertimbangan dalam pegambilan keputusan membeli dan menjual saham adalah melakukan prediksi. Terdapat banyak algoritma yang dapat digunakan dalam prediksi salah satunya adalah metode Adaptive Neuro Fuzzy Inference System (ANFIS) yang merupakan penggabungan dari algoritma Logika Fuzzy dan Jaringan Syaraf Tiruan. Pengaplikasian metode ANFIS memerlukan struktur ANFIS yang baik dengan pemilihan jumlah dan tipe membership function yang tepat. Pada penelitian ini membership function tipe gaussian dan gbell digunakan karena memiliki kelebihan yaitu memungkinkan perubahan halus dan dapat mengakomodasi ketidaktepatan dalam pengukuran sehingga cocok dengan pola data histori yang bergerak secara halus di satu waktu. Pada penelitian ini diperoleh bahwa tipe gaussian memiliki akurasi yang lebih baik dibandingkan tipe gbell sebesar 97.87% untuk memprediksi harga tertinggi saham Tencent Holdings Limited dan tipe gbell memiliki akurasi yang lebih baik dibandingkan tipe gaussian sebesar 97,8% untuk memprediksi harga tertinggi saham Take-Two Interactive.
Perancangan Sistem Informasi Pengelolaan Data Penjualan Pada UD Memeri
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 2 (2022): JELIKU Volume 11 No 2, November 2022
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.2022.v11.i02.p24

Abstract

UD Memeri merupakan salah satu UKM yang menjual berbagai jenis bebek. Selama UKM ini berjalan, kualitas bebek yang dijual UD Memes tidak pernah buruk. Saat ini transaksi penjualan UD Memeri per hari bisa mencapai 50 hingga 100 orang. mulai mencatat penjualan itik. Dengan adanya penjualan dan pencatatan secara manual, tidak menutup kemungkinan dapat terjadi kesalahan dalam pencatatan transaksi. Kegiatan transaksi dan pengelolaan data produk masih dilakukan dengan cara konvensional yang membuat proses kerja memakan banyak waktu karena dalam proses transaksi di penjualan, oleh karena itu dibutuhkan sebuah sistem informasi untuk mengelola data transaksi penjualan di UD Memeri. Pembuatan sistem informasi tidak dapat langsung dikembangkan sebelum adanya analisis kebutuhan dan sistem yang dideskripsikan dalam bentuk desain. Hasil analisis kebutuhan pengguna, terdapat tiga pengguna sistem informasi yaitu admin, pemilik, dan staf. Perancangan sistem didasarkan pada analisis kebutuhan pengguna dengan merancang Data Flow Diagram (DFD) dan merancang basis data menggunakan Entity-Relationship Diagram (ERD), serta merancang antarmuka sistem informasi yang akan dibangun berbasis website. Desain antarmuka meliputi desain antarmuka halaman admin, desain antarmuka halaman staf, dan desain antarmuka halaman pemilik. Dengan dibuatnya perancangan ini, UD Memeri memiliki gambaran tentang sistem informasi yang akan dibangun dan disesuaikan dengan kebutuhan
Perbandingan Pengelompokan Metode PSO K-Means Dan Tanpa PSO Dalam Pengelompokan Data Alert
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 2 (2022): JELIKU Volume 11 No 2, November 2022
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.2022.v11.i02.p07

Abstract

With increasing knowledge and increasing internet crime, an Intrusion Detection System (IDS) is needed, one of which is Snort which can detect attacks. An attack notification is needed to let administrators know if an attack has occurred. The grouping of alerts uses the PSO method on K-Means and continues with the calculation of the risk value to label the threat level, namely low, medium, high in each group. The Whatsapp bot will send groups of alerts that have high and medium labels only. A notification will appear on the Whatsapp application. The results obtained in this study by grouping the attack data, namely, the accuracy obtained by the system using the Particle Swarm Optimization method on K-Means obtained better results than only using the K-Means method.
Implementasi Port Knocking Dalam Mengamankan Jaringan VPN Pada Sistem E-learning
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 1 (2022): JELIKU Volume 11 No 1, August 2022
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.2022.v11.i01.p06

Abstract

Many universities have started using e-learning as a medium of learning and teaching. However, the system on e-learning is still vulnerable to attacks such as identity theft and authentication on e-learning systems. One of the way to secure data on a network is implement a Virtual Private Network (VPN) on the network which can make a network private. That way, the security on the port on the E-learning server will be guaranteed. But attacks on servers more often occur on port 23 (telnet) because telnet does not encrypt the connection process. One of the attacks that is often used is a brute force attack. Based on these problems, research has been carried out to secure port 23 (telnet) and port 80 (e-learning website) on the e-learning server from brute force attacks by implementing the port knocking method. Port 23 and port 80 on the e-learning server that uses the port knocking method are always closed so that the client must do port knocking before being able to use port 23 and port 80 on the e-learning server. By implementing port knocking on the e-learning server, brute force attacks can be avoided because the attacked port is closed.
Aplikasi Pencarian Informasi Al-Quran dengan Ontologi Web Semantik
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 1 (2022): JELIKU Volume 11 No 1, August 2022
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.2022.v11.i01.p19

Abstract

Al-Quran is the holy book of Muslims which consists of 30 chapters, 114 surahs, and 6236 verses. Each juz in the Quran can contain one or more surah and each surah consists of a different number of verses. Seeing the many contents of the knowledge of the Quran, then this can help someone to find and determine the theme of the surah to be read manually. In this study, the authors build a system that is expected to facilitate one's work in searching for the contents of the Al-Quran by using ontology as the backbone of the system, Methonology as a method for building an ontology model, and Prototyping as a system development method.
Implementasi Algoritma Gronsfeld Cipher dan Steganografi End Of File Untuk Pengamanan Data
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 1 (2022): JELIKU Volume 11 No 1, August 2022
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.2022.v11.i01.p14

Abstract

Information is a collection of data or facts that are organized or processed in a certain way so that they have meaning for both recipients and users. Data and information are very important things to keep their security or confidentiality so that unauthorized parties cannot find out the data or information. This Data Security Application was developed using the Gronsfeld Cipher algorithm and the End Of File Steganography method. This desktop-based application was created with the aim of increasing data security on confidential information so that unauthorized parties cannot find out the contents of the data. This applicationlis expected to be a solution to prevent the theft of important information by unauthorized parties. From the test results, the developed application can receive input, process input and produce output as expected. Testing the quality of the embedded image gets an average PSNR value of 75,543 dB which can be said to be good because an image can be said to be good if it has a PSNR value above 40 dB, this also shows that the developed application can protect the data embedded in the digital image.
Enkripsi Gambar Berdasarkan Modifikasi Bit Piksel Dengan Menggunakan Perpaduan Logistic Map Dan Henon Map
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 2 (2022): JELIKU Volume 11 No 2, November 2022
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.2022.v11.i02.p10

Abstract

Pencurian data dengan menggunakan serangan malware di era digital ini dapat menyerang smartphone dan cloud server, pada tahun 2018 terjadi pencurian foto milik Aryono Huboyo Djati. Pencurian dapat dicegah dengan menerapkan teknik kriptografi. Tujuan dari penelitian ini adalah untuk mengetahui kemampuan menggabungkan Logistic Map dan Henon Map dalam enkripsi dan dekripsi citra. Kedua teori ini dipilih karena sensitif, dengan perubahan kecil pada nilai input akan memberikan dampak yang sangat signifikan terhadap nilai output. Langkah pertama adalah mengubah citra menjadi matriks dan pengacakan menggunakan algoritma Logistic Map kemudian dilanjutkan dengan proses XOR untuk setiap bit piksel menggunakan algoritma Henon Map. pada penelitian ini citra hasil enkripsi diperoleh nilai MSE rata-rata melebihi 400 dan nilai PSNR rata-rata kurang dari 10dB, hal ini menunjukkan bahwa citra cipher berbeda dengan citra biasa, dan hasil dekripsi menunjukkan nilai MSE rata-rata adalah 0 dan PSNR rata-rata nilai rata-rata adalah 100, ini menunjukkan bahwa tidak ada perbedaan antara gambar deskripsi dan gambar asli

Page 28 of 49 | Total Record : 488

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