(JELIKU) Jurnal Elektronik Ilmu Komputer Udayana
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
Articles
21 Documents
Search results for
, issue
"Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020"
:
21 Documents
clear
<![CDATA[Pengaruh Fitur Terhadap Hasil Diagnosis Gangguan Hati Menggunakan Jaringan Syaraf Tiruan(JST) pada Matlab ]]>
<![CDATA[Prebiana, Kiki Dwi]]>;
<![CDATA[Santi Astawa, I Gede]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020 ]]>
Publisher : <![CDATA[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.v08.i03.p07
<![CDATA[The diagnosis is a classification of a person based on a disease or abnormality . One classification technique that can be used is Artificial Neural Networks. ANN is an information processing system that has characteristics similar to human nerves, in ANN training data is needed in learning. The learning process in Artificial Neural Networks related to the length of time the learning is done. One way to reduce computing time can be done with the selection feature. In this study, an analysis of the results of the diagnosis of liver disorders using Artificial Neural Networks with feature selection and without feature selection. The test results show that the accuracy of the data obtained by performing feature selection tends to be more stable when compared to the value of data accuracy without feature selection. Besides the learning time required by the data that do feature selection tends to be faster than data that does not do the feature selection.]]>
<![CDATA[Kualifikasi Noise Pada Citra Lontar Bali dengan Metode Gaussian Filter ]]>
<![CDATA[Prathama, Wayan Adhitya]]>;
<![CDATA[Arta Wibawa, I Gede]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020 ]]>
Publisher : <![CDATA[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.v08.i03.p12
<![CDATA[In improving the quality of the image basically makes the appearance of an image better than before. One thing that is done in improving the image quality is noise qualification. This noise qualification aims to reduce the level of noise contained in a digital image. In this study, the image used is the image of Bali palm leaf. There are many methods that can be used to qualify for noise. One of them is the Gaussian filter. In this study, Gaussian Filter is used as a method to qualify the noise contained in the palm leaf image. The image quality after the noise qualification process is calculated using PSNR (Peak Signal to Noise Ratio). The higher the PSNR value obtained, the better the image quality. In this study, the PSNR value obtained in the palm leaf image after processing the noise qualification is 54.7625 db. Keywords: Gaussian Filter, Noise, PSNR, Bali Palm Leaf, Image]]>
<![CDATA[Prediksi Loyalitas Pengguna Menggunakan Metode Naive Bayes di Online Printing Marketplace "Goprint" ]]>
<![CDATA[Widiastawan, Gede]]>;
<![CDATA[Arya Kadyanan, I Gusti Agung Gede]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020 ]]>
Publisher : <![CDATA[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.v08.i03.p03
<![CDATA[Goprint is an Online Printing Marketplace that connects printing services with users who want to print documents quickly without the need to queue. In the span of time from April 2019 to September 2019 it was found that the number of Goprint users reached 407 users, 24 partners, and 256 orders. From transactions that have been carried out by users, not a few orders are often canceled due to ineffective Goprint features or poor partner performance. This causes Goprint users to feel dissatisfied with the services provided by the Goprint application. The Naive Bayes algorithm is one of the algorithms used for classification or grouping of data, but can also be used for decision making. With this algorithm and the problems that occur, the authors make a system to predict the loyalty of Goprint users to anticipate users who stop leaving Goprint because they are not satisfied or loyal users. The data used as training data is 20 and testing data is 10. From the test results it is found that the value of precision is 80%, 100% recall, and 90% accuracy.]]>
<![CDATA[Low Filtering Method for Noise Reduction at Text to Speech Application ]]>
<![CDATA[Sutanti, Putu Asri Sri]]>;
<![CDATA[Mastrika Giri, Gst. Ayu Vida]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020 ]]>
Publisher : <![CDATA[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.v08.i03.p17
<![CDATA[Technological developments have greatly encouraged various researchers to develop several studies in the IT field. One branch of research in the IT field is sound synthesis. Some text-to-speech applications, are usually quite difficult to form and are less flexible in replacing existing types of sound. In addition, sometimes accent or how someone speaks is not well represented, so it is quite difficult to form a text-to-speech application by using the desired sound like user voice or other sounds. From the above problems, this research propose an application that can change text into sound or text-to-speech which is more flexible and in accordance with the wishes of the user. From the results of testing that has been done, this system has an accuracy of 70%.]]>
<![CDATA[Voice Classification Based on Gender Using Backpropagation and K-Means Clustering Algorithm ]]>
<![CDATA[Khatami, Maula]]>;
<![CDATA[Gede Suhartana, I Ketut]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020 ]]>
Publisher : <![CDATA[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.v08.i03.p08
<![CDATA[Sound is the identity of all living creature, including Humans. With voice we can do socialize, call people, ask questions, communicate, and even be able to help us to recognize the sex of the person who makes the sound. Nowadays, knowing gender through sound cannot only be done by humans but through a computer. Voice classification using a computer shows increasingly sophisticated technology. Of course this technological advance can also help in terms of security, where the voice can be a key or password in a certain confidentiality. In this study the focus of sound recordings is classified according to the sex of men and women by using the Backpropagation algorithm for training data, then Mel Frequency Cepstral Coefficients (MFCC) will process sound data and get features, and the K-Means Clustering algorithm will classify sound data already processed. The dataset used here is in the form of male and female voice recordings obtained from YouTube videos that have been separated by video sections. There are each 10 male and female voice files for training. As for testing, there are several male and female voice files that are placed in separate folders.]]>
<![CDATA[Design and Development of Poultry Disease Classification with Certainty Factor Method ]]>
<![CDATA[Panji Palguna, I Gusti Agung Ngurah]]>;
<![CDATA[Astuti, Luh Gede]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020 ]]>
Publisher : <![CDATA[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.v08.i03.p13
<![CDATA[Expert systems in organizations aimed at adding value, increasing productivity and managerial areas that can draw conclusions quickly. Like with organizations that conduct livestock business that are very promising but necessary high vigilance against disease as well as highly poultry susceptible to various types of diseases caused by viruses or bacteria. To know the disease quickly made a system that is useful for detecting, so breeders can check their poultry without seeing a veterinarian for early detection. Permanent Veterinarian required for further treatment.]]>
<![CDATA[Lemmatization in Balinese Language ]]>
<![CDATA[Purnajiwa Arimbawa, I Gede Angga]]>;
<![CDATA[Sanjaya ER, Ngurah Agus]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020 ]]>
Publisher : <![CDATA[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.v08.i03.p04
<![CDATA[Lemmatization is a process to extracting root word from an affixed word with the aim of reducing variations of the word into the root word. Previous researches on extraction of root word in Balinese Language has been done with rule- based methods to remove affixes from words. The weakness of the rule-based method is that it must comply with the set of rules provided. However, writings in Balinese often contain typographical errors because speakers tend to write words according to how the word is spoken instead of following the correct rules. In this research, we apply the Levenshtein distance method to overcome the aforementioned shortcoming. After all the rules applied to a given word fail, the Leven- shtein distance method is used to list all words that are ”close”. Next, we select the closest word as the root word of the given input. Based on the experiments, our proposed method achieved an accuracy of 96.01 %.]]>
<![CDATA[Tourism Recommendation System in Bali Using Topsis and Greedy Algorithm Methods ]]>
<![CDATA[Ubaidillah, Muhammad Afif]]>;
<![CDATA[Gede Dwidasmara, Ida Bagus]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020 ]]>
Publisher : <![CDATA[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.v08.i03.p09
<![CDATA[Tourism is the mainstay of the economy of the region of Bali and is an important sector in supporting the level of community welfare. The world of tourism is essentially an important symbol for Bali. Of the many tourists who come to Bali, of course not all tourists know all information about Bali, such as in terms of tourist locations, and tourist attractions closest to other tourist attractions. Therefore, the authors aim to create a recommendation system that can provide planning for the selection of tourist attractions according to the closest distance and the user's budget. This system is designed using the TOPSIS (Technique for Order Preference by Similarity To Ideal Solution) method and the Greedy Algorithm. The TOPSIS method is a SPK (Decision Making System) that will be used for the selection of tourist attractions that will help tourists to arrange vacation planning before going on a tour. While the Greedy Algorithm is used to find the closest or shortest distance between a tourist site and other tourist attractions, this algorithm will be able to determine which path will be taken first or called the local optimal path, so that all the paths are taken at the end of the trip and create a travel route shortest or called the global optimum so that it can also be the expected solution. From this it can be determined the value of the shortest travel route that starts from the location of the user's residence to the tourist attractions and to other nearby tourist attractions. The data used is data obtained from DISPARDA, namely tourist data. Research related to the selection of tourism object decisions based on the type of tourism, prices and facilities, and the results are able to provide recommendations for tourist attractions that meet these criteria. Tourism Selection Using Techniques For Order Preference By Similarity To Ideal Solution (Topsis) With Object Localization Visualization [4], Development of Decision Support System for Hotel Determination in Buleleng District Using Analytic Hierarchy Process (AHP) Method and Technique for Others Reference By Similarity To Ideal Solution (TOPSIS) [3], a Decision Support System for Determining Tourist Locations using the Top-sis Method [6]]]>
<![CDATA[PENERAPAN METODE CERTINTY FACTOR(CF) DALAM PEMBUATAN SISTEM PAKAR DIAGNOSIS PENYAKIT TUMOR OTAK ]]>
<![CDATA[Prebiana, Kiki Dwi]]>;
<![CDATA[Astuti, Luh Gede]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020 ]]>
Publisher : <![CDATA[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.v08.i03.p14
<![CDATA[Diagnosis adalah klasifikasi seseorang berdasarkan suatu penyakit atau abnormalitas yang diidapnya. Salah satu jenis penyakit yang memerlukan diagnosis adalah penyakit tumor otak. Akan tetapi dalam proses pemeriksaannya tentu memerlukan sautu biaya yang cukup mahal. Oleh sebab itu diperlukan suatu sistem yang dapat bertindak layaknya serang pakar untuk mengetahui gejala- gejala yang timbul akibat penyakit tumor otak. Salah satu metode yang dapat diterapkan dalam pembuatan sistem pakar adalah metode Certinty Factor(CF). Metode ini dapat digunakan untuk mengatasi permasalahan berkaitan dengan ketidakpastian dalam menyelesaikan atau menentukan suatu solusi. Hasil dari penelitian ini adalah prosantase kemungkinan pasien terhadap keempat jenis penyakit tumor otak yang ada.]]>
<![CDATA[Implementasi Aplikasi Enkripsi Dan Dekripsi Objek 3 Dimensi Menggunakan Algoritma Blowfish ]]>
<![CDATA[Nuboba, Barneci Henderika]]>;
<![CDATA[Anom Cahyadi Putra, I Gst Ngurah]]>;
<![CDATA[Gede Suhartana, I Ketut]]>
<![CDATA[ JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020 ]]>
Publisher : <![CDATA[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.v08.i03.p21
<![CDATA[Kemajuan Teknologi Digital telah mempengaruhi cara berpikir dalam desain pada Arsitektur. Sekarang banyak Arsitek yang menggunakan software tidak hanya sebagai alat menggambar objek 2 dimensi tetapi telah berkembang menjadi alat untuk menggambar objek 3 dimensi (modeling) dan presentasi multimedia. 3 dimensi modeling telah menjadi bagian yang tak terpisahkan dalam proses desain arsitektur. 3 dimensi semakin sering digunakan karena didapati informasi secara utuh dan akurat sesuai keadaan nyata. Dengan begitu banyaknya perkembangan yang terjadi di dunia arsitektur, keamanan pada objek 3 dimensi sangat dibutuhkan mengingat telah terjadi banyak kasus plagiarisme desain arsitektur. Berdasarkan hasil survey yang dilakukan di 72 Perguruan Tinggi di Indonesia oleh Tim Alumni Reference Group (ARG), disebutkan bahwa masih banyak yang belum mengetahui dan menyadari tentang plagiarisme sehingga mereka sering tidak menyadari jika telah melakukan tindakan plagiarisme, selain itu juga masih adanya mindset atau persepsi yang keliru dan menganggap bahwa mengambil atau mencuri ide, hak cipta dan hak intelektual seseorang bukan merupakan masalah serius atau mungkin sudah lazim (Mochtar, 2014). Dengan latar belakang di atas, penulis memilih judul "Keamanan Objek 3 Dimensi menggunakan Algoritma Blowfish” dimana penulis mengimplementasikan ilmu kriptografi untuk mengamankan data berupa desain arsitektur objek 3 dimensi agar terhindar dari praktek plagiarism menggunakan algoritma blowfish. Kata Kunci: kriptografi, enkripsi, dekripsi, objek 3 dimensi, algoritma blowfish]]>
