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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 23 Documents
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Search results for , issue "Vol 11 No 1 (2022): JELIKU Volume 11 No 1, August 2022" : 23 Documents clear
Aplikasi Website Pengamanan File Dokumen Menggunakan Kriptografi RSA
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.p04

Abstract

Data security is something that needs to be considered in maintaining the confidentiality of information, especially those that only contain information that can be known by the authorized party. There are still many cases of data leakage that occur in Indonesia, especially in documents. Documents can be secured using cryptographic techniques. One of the well-known cryptography is RSA Cryptography. The security of RSA cryptography lies in the difficulty of factoring large numbers into prime factors. The implementation of RSA cryptography will be made using the python programming language based on the website. The system created has a success rate of 100% in encrypting documents for each document, and in decrypting it has a success rate of 85% to 96%.
Klasifikasi Jurnal menggunakan Metode KNN dengan Mengimplementasikan Perbandingan Seleksi Fitur
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.p18

Abstract

Classification is a process that automatically places text documents into a text based on the content of the text. Classification can help us classify many text documents that have been published, with the classification, these text documents can be reached easily and quickly. Feature selection can be used to improve the performance of text classification in terms of learning speed and effectiveness. In the Chi-Square feature selection experiment, a 1% threshold combination with a parameter value of k=6 is the combination chosen to be the best model. In testing the new data, the K-Nearest Neighbor model by selecting the Chi-Square feature produces precision performance, recall, F1-Score, and accuracy respectively, namely 85%, 83.3%, 88.2%, and 92.3%. In the Gini Index feature selection experiment,1% threshold combination with a parameter value of k=4 is the combination chosen to be the best model. This threshold selects about 31 features with the highest Gini Index value. In testing the new data, the K-Nearest Neighbor model by selecting the Gini Index feature produces precision performance, recall, F1-Score, and accuracy respectively, namely 81.2%, 80.3%, 81.6%, and 86.6%.
Implementasi Metode K-Nearest Neighbor Dalam Mengklasifikasikan Jenis Suara Berdasarkan Jangkauan Vokal
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.p20

Abstract

Humans have voice characteristics with different vocal ranges, namely the male voice consists of Tenor, Baritone, and Bass, while the female voice consists of Soprano, Mezzosoprano, and Alto. Determining the voice range, especially for a singer, requires a vocal trainer or musical instrument that is quite difficult to access. Therefore, a sound classification system created based on vocal range using the Harmonic Product Spectrum (HPS) feature extraction method and the K-Nearest Neighbors (KNN) classification method uses k parameters from 1 to 40. The test gets the highest accuracy on parameter k=8, which is 88.88%, so that from the resulting accuracy to prove the K-Nearest Neighbor (KNN) method gives good results in classifying the type of voice. Keywords: Classification, Vocal range, Harmonic Product Spectrum, K-Nearest Neighbors
Cover & Table of Contents JELIKU Vol. 11 No. 1
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

Abstract

Video Steganography Encryption on Cloud Storage for Securing Digital Image
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.p05

Abstract

Cloud storage is a data storage service in cloud computing that allows stored data to be shared and accessed via the internet. Cloud storage is usually used to store personal data such as files, photos, or videos with so that these data can be accessed anywhere via the internet without the need to use physical storage media. However, cases of data leaks in cloud storage still occur which causes personal data stored in cloud storage to be accessed by other people who do not have access. The Client-Side Steganography Encryption on Cloud Storage Application was developed using the Modified Least Significant Bit (LSB) method and the Standard Advanced Encryption (AES) algorithm. This desktop-based application was developed to protect personal data of digital images embedded in a video so that unauthorized parties cannot view the data. This application is expected to be a data security solution on cloud storage to prevent theft of personal data by non-existent parties. From the test results, the developed application can receive input, process input, and produce the desired output. The image from the extraction process from video also does not change at all in terms of visual or visible. The results obtained from this test is the PSNR value with an average of 36,395 dB. A good PSNR value is above 30 dB and indicates that the quality of the extracted image is good and also indicates that the developed application can protect data of digital images into video.
Implementasi Double Frequency Modulation dan FFT dalam Sintesis Suara Rindik
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.p10

Abstract

The modern era has changed a lot of people's lives, for example traditional culture is slowly being abandoned which is being replaced by the ease of technology which is growing to affect people's lifestyles. One of them is gamelan culture in the Bali area, namely gamelan rindik. In the past, the rindik gamelan was usually used as an entertainment musical instrument played by village farmers, then for the joged roof performance and later adapted as a welcome musical instrument in hotels. However, along with the development of technology, making this gamelan less desirable because people, especially the younger generation, are more interested in modern musical instruments which are more attractive than traditional gamelan such as the rindik. Because of this, the author is interested in making a digital form of gamelan rindik by synthesizing the sound of gamelan rindik and then presenting it through a media website that can be accessed on any platform. This can be an introduction to the younger generation about gamelan rindik with a more attractive visual. Synthesizing requires a sound processing technique with a certain method commonly used, namely Double Frequency Modulation. However, before doing the synthesis, another method is needed to obtain the features that will be used during the synthesis, one of which is the frequency feature of the sound produced by the rindik gamelan. To get the frequency using the Fast Fourier Transform method. The research was conducted by analyzing 11 blades on the rindik and then the synthesis process was carried out. From the test results, it was found that the method used was successful in synthesizing using three datasets with each accuracy for dataset 1 having an accuracy of 36%, for dataset 2 having an accuracy of 100% and dataset 3 having an accuracy of 45%. This result was obtained by recording the sound of the rindik gamelan on its 11 blades
Sistem Media Pembelajaran Matematika Dasar SMP Berbasis Semantik Web
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.p21

Abstract

Mathematics is a very important science because it is related to human life. Therefore, mastery of mathematics is absolutely necessary and mathematical concepts must be understood correctly. In Indonesia, students' ability to understand mathematics is still relatively low. From this, understanding of mathematical concepts needs to be improved again so that students clearly understand mathematical concepts. In order to improve understanding of mathematical concepts, various efforts were made. One of the efforts carried out by the author is a semantic web-based learning media system using concept maps in basic mathematical ontologies. This system will use ontology to build a system that will represent a mathematical concept as a domain of knowledge explicitly about other concepts related to previous concepts by giving meaning, properties, and relations so as to form a knowledge base. In this research, the writer uses methodological method to build the basic mathematical ontology and the system development will be done by prototyping method. The system built has 2 features, namely exploration and semantic search, with the aim that the existing knowledge in the system can be accessed systematically and according to user needs. To ensure that the system built can run as expected, system testing with black box testing has shown which features in the program run according to their functions and ontology evaluation using OntoQA on Schema Metrics carried out by measuring Relationship Richness (RR), Attribute Richness (AR), and Inheritance Richness (IR). In the evaluation of this ontology, it shows that the Relationship Richness (RR) value is 0.06; Attribute Richness (AR) value is 0.5; and the value of Inheritance Richness (IR) is 14.5.
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.

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