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(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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Disain Sistem Informasi Rekomendasi Tanaman Pangan Daerah Bali Berbasis Mobile suastika, i made; Kadyanan, I Gusti Agung Gede Arya
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 4 (2021): JELIKU Volume 9 No 4, Mei 2021
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.2021.v09.i04.p06

Abstract

Abstract Plant food is a necessary staple of each human being, in the process of cultivation is often the case things are not in want as failed harvests. These problems are caused by various factors such as weather that is not suitable for the needs of the plant or environmental conditions that are not suitable for its growth. Based on the problem that it takes a system of information that can provide information about the needs of that required by a plant food from the weather and environment of his life. The article will discuss the design of the application system of information on food crops to the area of Bali -based applications mobile. Keywords: Applications, Mobile, Information Systems, Food Crops, Weather, Environmental Conditions.
Optimization of K Parameters on KNN in Gamelan Jegog Title Classification Using Time Domain Features Artayani, Adis Luh Sankhya; Putri, Luh Arida Ayu Rahning
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 1 (2021): JELIKU Volume 10 No 1, Agustus 2021
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.2021.v10.i01.p12

Abstract

Bali is one of the provinces in Indonesia which has a lot of culture and arts, one of which is the Gamelan Jegog Bali. The technology nowadays can make it easier for humans to search for the title of a song that was previously unknown. This technology can be applied to the unknown title of Gamelan Jegog. The features used in this system are Short Time Energy and Zero Crossing Rate. The feature is extracted from Gamelan Jegog and then used to find the best k parameter from the K-Nearest Neighbor classifier. The results showed that the highest accuracy was 45% when the k parameter is 9. The amount of data used and the classification method used has an effect on the accuracy of this system when compared to similar studies.
The Effects of Different Kernels in SVM Sentiment Analysis on Mass Social Distancing Yonatha Wijaya, Komang Dhiyo; Karyawati, Anak Agung Istri Ngurah Eka
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 2 (2020): JELIKU Volume 9 No 2, November 2020
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.2020.v09.i02.p01

Abstract

During this pandemic, social media has become a major need as a means of communication. One of the social medias used is Twitter by using messages referred to as tweets. Indonesia currently undergoing mass social distancing. During this time most people use social media in order to spend their idle time However, sometimes, this result in negative sentiment that used to insult and aimed at an individual or group. To filter that kind of tweets, a sentiment analysis was performed with SVM and 3 different kernel method. Tweets are labelled into 3 classes of positive, neutral, and negative. The experiments are conducted to determine which kernel is better. From the sentiment analysis that has been performed, SVM linear kernel yield the best score Some experiments show that the precision of linear kernel is 57%, recall is 50%, and f-measure is 44%
The Influence of Changes in ANN Hidden Layer Unit and Feature Selection on Classification Wijana, Sawendo Eko; Astawa, I Gede Santi; Karyawati, AAIN Eka
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 3 (2021): JELIKU Volume 9 No 3, Februari 2021
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.2021.v09.i03.p05

Abstract

Abstract Classification is the process of differentiating a set of models into several data classes. There are many methods that can be used for the classification process, one of which is the Artificial Neural Network method. Neural networks are a computational method that mimics biological syafar networks. Artificial condition networks can be used to model complex relationships between input and output to recognize patterns in data [1]. In this study, testing was conducted to determine the effect of uncorrelated or low-correlation features in the data classification process and the effect of changing the number of units in the hidden layer on the classification results. The data used in this study were liver disease dataobtained from the Kaggle Dataset.Where in comparing the results of using feature selection, it is divided into 4 predetermined scenarios through the search for significance values ??with the SPSS correlation test.In the results of the implementation of the Multilayer Perceptron which aims to determine the effect of feature selection on the classification results, the results are that feature selection does not really affect the computation time obtained, and correlated data has more influence on the accuracy obtained when compared to uncorrelated data. In the results of the implementation of the Multilayer Perceptron which aims to determine the effect of changing the number of hidden layer units on the classification results, the results show that changes in the number of units in the hidden layer in Artificial Neural Networks have increased significantly in accuracy in several scenarios, but the computation time increases if the number of units in the hidden layer increases. Keywords: Classification, Artificial Neural Network, Liver Disease, Accuracy, Time.
Implementation of K-Means Clustering Algorithm in Determining Classification of the Spread of the COVID-19 Virus in Bali Putra, Putu Mas Anggita; Kadyanan, I Gusti Agung Gede Arya
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 1 (2021): JELIKU Volume 10 No 1, Agustus 2021
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.2021.v10.i01.p03

Abstract

The COVID-19 virus or also known as SARS-Cov-2 is an infectious disease caused by the Coronavirus which attacks the human respiratory system. The COVID-19 case has affected all provinces in Indonesia, including Bali. There is a total of 7481 cases in Bali and this is due to the lack of understanding of the community towards the COVID-19 prone areas in Bali. Therefore, it is necessary to group the areas prone to COVID-19 in Bali. One of the clustering algorithms is K-Means, this algorithm uses several groups for the placement of some data with a partition system. The grouping will be carried out using data from the Bali COVID-19 Task Force website on September 18, 2020, using RapidMiner application. The results obtained divided Bali into 3 clusters with Denpasar as the center of the highest spread of COVID-19 in Bali as the red zone, then Badung, Buleleng, Bangli, Gianyar, and Karangasem in the yellow zone, and other districts in the green zone.
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
Implementasi Business Intelligence Untuk Menentukan Tingkat Kasus Covid-19 di Indonesia Putri, Ni Made Elvina Aryadhika; Ryan Paramaditya, I Putu; Made Swarbawa, Ida Bagus; Aldi Arsa, Gede Lucky; Made Mahendra, Ida Bagus
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 1 (2021): JELIKU Volume 10 No 1, Agustus 2021
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.2021.v10.i01.p17

Abstract

Covid 19 atau SARS-CoV-2 merupakan sebuah penyakit yang menyerang sistem pernapasan yang dikenal pertama kali terjadi di Wuhan China pada akhir Desember 2019, penyebaran dari Covid-19 yang masif mengimflansi seluruh dunia sehingga WHO memutuskan bahwa Covid-19 merupakan pandemi global melalui keputusan tersebut pandemi Covid-19 hingga kini terus menjadi ancaman bagi banyak negara termasuk Indonesia. Teknologi informasi adalah teknologi yang membantu manusia membuat, memodifikasi, menyimpan, mengomunikasikan, dan/atau menyebarkan informasi. Business Intelligence (BI) adalah kumpulan aktivitas dan strategi yang digunakan untuk memahami situasi bisnis dengan melakukan berbagai jenis analisis pada data yang dimiliki oleh organisasi dan data eksternal dari pihak ketiga untuk membantu membuat keputusan bisnis yang strategis, taktis, dan operasional serta mengambil tindakan untuk meningkatkan bisnis. Penggunaan Business Intelligence (BI) sebagai sebuah sarana dalam melakukan peningkatan sistem pencegahan Covid-19 melalui sistem BI diharapkan penyebaran Covid-19 dapat diredam, diprediksi, dan dapat ditekan sehingga jumlah penderita Covid-19 dapat berkurang atau bahkan mencapai angka 0.
Balinese Kulkul Semantic Ontology: REST API Mobile Application Development Widiatmika, I Putu Agus Wahyu; Adi Pramartha, Cokorda Rai
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 4 (2021): JELIKU Volume 9 No 4, Mei 2021
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.2021.v09.i04.p02

Abstract

Kulkul is one of Bali's cultural heritage. Kulkul is used in Balinese society for communication when there is a danger, death, a ritual, and so on. The current phenomenon is that many Balinese people are only able to know and without knowing much knowledge about kulkul. It is because this knowledge is the only word of mouth, making it difficult for it to be collected, stored, retrieved, shared, and renewed. Current technological developments, especially mobile technology, allow the development of mobile applications on cultural knowledge with an ontology approach that will help provide an explicit explanation of this knowledge. In this study, the authors propose the application of a web service with a REST API architecture to help mobile applications integrate Balinese Kulkul Semantic Ontology. This study uses the prototyping method in developing the REST API. From the tests that have been done, it is found that the REST API has successfully received requests and responses which prove that the mobile application is well integrated.
Classification of Women's Voices Using Fast Fourier Transform (FFT) Method Apsari, Made Sri Ayu; Widiartha, I Made
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 1 (2021): JELIKU Volume 10 No 1, Agustus 2021
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.2021.v10.i01.p08

Abstract

Everyone has a different kind of voice. Based on gender, voice type is divided into six parts, namely soprano, mezzo soprano, and alto for women; and tenor, baritone, and bass in men. Each type of sound has a different range and with different frequencies. This study classified the type of voice in women using the Fast Fourier Transform (FFT) method by recording the voices of each user which would then be processed using the FFT method to obtain the appropriate sound range. This research got results with an accuracy of up to 80%.The results obtained from this study are quite appropriate and it is proven that the FFT method can be used in digital signal processing.
Cover & Table of Contents Vol. 9 No. 3 Vida Mastrika Giri, Gst Ayu
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 3 (2021): JELIKU Volume 9 No 3, Februari 2021
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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

Abstract

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