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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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Sistem Monitoring Tanaman Hidroponik Berbasis Internet of Things menggunakan Restful API
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.p11

Abstract

Agricultural technology is one of the important things in today's era. one of the Indonesian government programs made is a roadmap with the name Making Indonesia 4.0. in the agricultural roadmap program one of the important technology applications is hydroponic agriculture, in the implementation of hydroponic plants a good form of data communication is needed, therefore in this study the author uses a form of data communication with Restful Architecture API as communication in the hydroponic agriculture monitoring system. In this study, two tests were carried out, namely the test was carried out by testing the system in sending sensor data and the second. System testing in reading and controlling the pH sensor value with parameter intervals of 1 second, 5 seconds, 10 seconds, 20 seconds, and 30 seconds. The results obtained in this study are 30 seconds is the best time in the process of sending data one interval from the microcontroller to the system.
PERANCANGAN SISTEM KEAMANAN LINGKUNGAN PENGENAL SUARA KULKUL DENGAN MENGGUNAKAN METODE DEEP LEARNING
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.p22

Abstract

Advances in information technology provide benefits for people's lives today. Before the existence of information technology, people still use traditional communication media called kulkul. Kulkul is a communication tool that is used by hitting. Over time, people began to leave this culture because of the many other information systems used as communication media. However, nowadays people in their teens still do not know what the sound of the kulkul means. This is due to the absence of a kulkul voice recognition website. The method of data collection in this study was the observation method of a kulkul worker located in Denjalan Subvillage, Batubulan, Sukawati, Gianyar. To build a kulkul voice recognition system, the author uses a deep learning method. In this system there are 2 processes, namely training and classification. The training is used for the system to learn to recognize the sound of the kulkul and the classification to determine the category of the kulkul sound. Based on the classification carried out, the results obtained is testing accuracy 85%.
Pengembangan Sistem Manajemen Informasi Lagu Tradisional Bali Menggunakan Pendekatan Semantik Ontologi
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.p04

Abstract

Indonesia memiliki budaya yang beragam di setiap daerahnya. Salah satu contoh di Bali, terdapat budaya yang disebut tembang atau lagu tradisional Bali. Generasi muda saat ini kurang memahami informasi lagu tradisional Bali, hal tersebut disebabkan karena kurangnya informasi lagu tradisional Bali yang terkumpul secara eksplisit. Pada penelitian ini, dilakukan pengembangan ontologi untuk mendokumentasikan informasi lagu tradisional Bali dengan menggunakan metode Methontology. Ontologi kemudian diimplementasikan ke dalam sistem manajemen informasi lagu tradisional Bali yang dibangun menggunakan metode Prototyping. Sistem yang dibangun memiliki fitur pencarian semantik dan penjelajahan semantik yang bertujuan agar informasi mengenai lagu tradisional Bali dapat dikumpulkan dan diakses secara sistematis dan relevan. Dalam memastikan fungsionalitas dan pemahaman pengguna terhadap sistem, dilakukan pengujian Black-Box yang melibatkan 30 orang peserta dengan memberikan tugas penjelajahan dan tugas pencarian. Hasil yang didapatkan adalah sistem yang memiliki fungsionalitas baik, serta rata-rata partisipan dapat menjawab semua tugas dengan benar. Dari segi persepsi kegunaan dan kemudahan penggunaan sistem didapatkan hasil analisis data kuesioner menunjukkan rata-rata peserta setuju bahwa sistem yang dibangun sangat berguna dan mudah untuk digunakan.
Pengelompokan Pelanggan Toko Kerajinan Menggunakan K-Means dengan Model RFM dan LRFM
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.p03

Abstract

Customer groups within a company or shop are important to identify for determine the right sales strategy in a competitive market. This research was conducted at one of the online handicraft shops in Bali which was affected by the intense competition in the market. The handicraft industry in Bali is considered to provide a large contribution to the community's economy. One solution that can be done is to identify the customer groups in the store using the clustering technique. This research aims to get the best customer data cluster and model. The stages in this research start from preprocessing data on historical data and customer orders to generate data model Recency, Frequency, Monetary (RFM) and Length, Recency, Frequency, Monetary (LRFM), then the clustering process with K-Means and evaluation of cluster quality with Silhouette Coefficient (SC). Results Based on the research, the RFM model becomes a data model that produces the best clustering results with an SC value of 0.545 when k = 2 which is included in the medium structure. LRFM model only produces the largest SC value when k = 3 with a value of 0.415. The SC value calculated from each data model tends to increase when the percentage of data is added. Cluster 1 has 817 members with the last transaction taking a long time, but has a below average ordering and monetary frequency. Cluster 2 has 158 members, making the last transaction at the most recent time, and has an average order and monetary frequency. Keywords: Clustering, Customer, Craft, K-Means, RFM, LRFM, Silhouette Coefficient
Rancangan dan Analisis Model Algoritma Genetika Untuk Menyelesaikan Permasalahan Knapsack 2 Dimensi
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.p18

Abstract

The knapsack problem is problem that is still often found in everyday life, one of which is the problem of selecting goods to be transported into containers for delivery of goods. This knapsack problem can be solved by using various optimization algorithms, one of which is the genetic algorithm. This study aims to design a genetic algorithm model to solve the 2-dimensional knapsack problem. 2-dimensional knapsack problem is a knapsack problem that has 2 constraints and in this study, the constraints used were weight and volume.. The evaluation results of the genetic algorithm will be compared with dynamic programming. From the evaluation results that have been carried out, it can be concluded that genetic algorithms can produce near-optimal results with faster computational times than dynamic programming.
Analisis Sentimen Ulasan Aplikasi Transportasi Online Menggunakan Multinomial Naïve Bayes dan Query Expansion Ranking
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.p13

Abstract

The rapid development of the transportation industry in recent years has led to a new innovation in the field of transportation, namely the application of online transportation services. To facilitate the translation of user satisfaction, in addition to users being able to provide reviews, the Google Play Store uses a rating system consisting of a rating of 1 to 5. However, users often do not provide a rating that is in accordance with the review so that this is not enough to determine the sentiment of the review. This research is focused on evaluating the performance of the features selection using Query Expanison Ranking on the Multinomial Naïve Bayes method in the problem of sentiment analysis on the two of most popular online transportation service applications in Indonesia, namely Gojek and Grab. From the results of the performance evaluation using k-fold cross validation, it was found that the best feature selection ratio was 20% with the best performance in terms of precision.
Pengembangan Perangkat Lunak Pembelajaran Penulisan Aksara Bali Menggunakan SDLC Untuk Anak-Anak
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.p09

Abstract

Balinese script is a traditional script originating from Bali. To maintain sustainability, formal education in schools through Balinese language subjects is one if many ways to maintain it. Apart from studying at school, it would be even better if Balinese script learning could be done outside of school by appealing to the concept of learning. One way to create interesting learning is through application games. Making a Balinese script writing application aims to help students learn Balinese script by implementing the Software Development Life Cycle (SDLC) and Black Box testing of making Balinese script writing applications. Making the application is expected to be one of the media that can assist students in learning Balinese script.
Penerapan Metode MFCC dan Naive Bayes untuk Deteksi Suara Paru-Paru
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.p08

Abstract

Lung disease is an unpleasant illness that can be dangerous if not treated properly. This is because lung disease can infect others. The lungs are an important part of the human organ that distributes oxygen throughout the body, so this lung disease needs to be treated with proper procedures. Lung disease problems can be solved using an expert system. Expert systems can help doctors work to provide an early diagnosis of ear diseases. The method used in this study is the MFCC method, which provides compelling information about lung disease and provides treatment solutions based on the symptoms of each existing disease. This system is performed by calculating the symptom weights of the disease, which is obtained from expert experience, and produces the optimum value in the form of the maximum value. The highest value data provides the results of the disease diagnosis at the level of confidence in the form of percentage values. Based on the test results, the goodness of fit between the system diagnostics using the system validation test method and the expert diagnostic results is 90%. The results of the tests performed show that the system is operating normally according to its capabilities.
Optimasi Deployment Wsn Menggunakan Algoritma Pso Untuk Pendeteksi Kebakaran Hutan
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.p21

Abstract

Abstract Forest fires are disasters that have often occurred in recent years. This has a huge impact on both the environment and society itself. Delayed handling of fires is one of the triggering factors for the large losses caused by the disaster. The use of a Wireless Sensor Network is one solution so that information related to fires is conveyed to the authorities quickly so that the handling can be done more quickly. In this study, a simulation was made to determine the optimal position of a node to detect fires optimally. This simulation is run on NS3 Software on Ubuntu 18.04 Linux Operating System. In the optimization process, the PSO algorithm is run with Google Colab. The results of each iteration on the PSO will be simulated in NS3 and the communication between nodes will be seen. There are 12 iterations of the maximum 30 iterations specified, and there are 12 simulations according to the number of iterations. From 12 simulations that have been carried out, it is known that in the last iteration of the 10 nodes installed, all nodes communicate. Communication between nodes can be seen through .pcap files and graphs on NetAnim, the communication is characterized by sending fire messages to each installed node. In the last iteration, 10 nodes received a fire message. Keywords: Wireless Sensor Network, Forest fires, Particle swarm optimization
Aplikasi Identifikasi Nada Darbuka Dengan Onset Detection, MFCC, Dan KNN
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.p15

Abstract

Darbuka is one of the hadrah musical instruments that acts as a marker when the vocals raise or lower the rhythm of the sound. In learning the Darbuka, the trainer needs to check whether the sound produced is correct or not. With the Darbuka tone recognition system, it will be easier for someone to learn hadrah without a coach. The system developed in this study uses onset detection to break the tone pattern. Then each note goes through a feature extraction process using MFCC with parameters of frame length, overlap length, and the number of coefficients. Then the results of feature extraction through a classification process using KNN. Thexresultsxof the system test showxthat the best combination of parameters in the identification of Darbuka tones with a frame length of 20 ms, overlap length of 40%, the number of MFCC coefficients as much as 13 and a value of K = 1 produces a basic tone identification accuracy of 100%, a tone pattern identification accuracy of 30%, and the accuracy of basic tone identification in the tone pattern is 72.67%.

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