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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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Pemanfaatan Augmented Reality untuk Pembelajaran Pengenalan Alat Musik Pianika
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 4 (2023): JELIKU Volume 11 No 4, May 2023
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.2023.v11.i04.p01

Abstract

People use technology as a learning medium to learn musical instruments such as guitar, drums, piano, and other musical instruments. Augmented Reality technology can be used to create an immersive experience for music students. AR unites two-dimensional and three-dimensional virtual objects into a real three- dimensional environment. In music theory, especially the basic theory of piano can actually be learned easily. Now many music learning methods are easy to obtain. However, most of them look boring and difficult to learn music for users. This has triggered the decline in public enthusiasm in learning various things about music. By applying Augmented Reality technology, boring methods can be minimized so that it becomes a more interesting and exciting learning method by using Augmented Reality technology that is able to provide an immersive experience for users.
Sistem Monitoring PKM Berbasis Website Program Studi Informatika FMIPA UNUD
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 4 (2023): JELIKU Volume 11 No 4, May 2023
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.2023.v11.i04.p34

Abstract

From year to year, there are more and more PKM proposals submitted by students in the Informatics Study Program. So far, what has happened is that PKM proposals that enter are sorted manually, namely by students printing their PKM proposals and the proposals will then be distributed to the lecturers in charge of reviewing the proposals. It will take time to evaluate and increase the possibility of repeated errors because the results of the evaluation have no history of recording. Based on these problems, a monitoring system is needed for PKM proposals that enter the Study Program so that later PKM proposals that come in will be more organized and minimize the possibility of errors. The monitoring system is built on a website basis using the laravel framework. Student users can log in and upload PKM proposals, view the results of PKM proposal reviews, revise PKM proposals and update the status of PKM proposals that have been submitted to faculties or universities. Meanwhile, lecturer users can log in and review PKM proposals. After testing with black box testing, the monitoring system has obtained the results as expected.
Implementasi Augmented Reality sebagai Media Pengenalan Alat Musik Tradisional Bali dengan Metode FAST Corner Detection Berbasis Android
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 4 (2023): JELIKU Volume 11 No 4, May 2023
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.2023.v11.i04.p23

Abstract

There are so many traditional Balinese musical instruments that some people don't know about. With technological advances, the introduction of traditional musical instruments can use the Augmented Reality (AR) method. The researcher used ceng-ceng, genggong, gong, gangsa, and rindik 3D objects as 3D models. The algorithm used is FAST Corner Detection to determine the key points on the marker so that it becomes a reference for detecting 3D objects of Balinese musical instruments. Application testing is carried out by blackbox testing and application performance testing which includes testing of scanning markers that are positioned perpendicular to the camera, rotated 90°, 180°, and 270°. In addition, the application response time to markers was tested using three smartphones of different types and specifications. The three devices include Mi 10T, Realme 3 Pro, and Realme C11. The blackbox test results obtained good results. The results of the marker scanning test, namely the angle of rotation of the marker does not affect object detection. As for the response time test, it was found that the Mi 10T has the fastest average response time of 1.35 seconds, then the Realme 3 Pro with an average response time of 1.49 seconds, and the Realme C11 with an average response time of 1.82 seconds.
Prediksi Diabetes Menggunakan Artificial Neural Network Wirapati, Satya; Astuti, Luh Gede
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 4 (2023): JELIKU Volume 11 No 4, May 2023
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.2023.v11.i04.p15

Abstract

Diabetes is one of the non-communicable diseases (NCD) which has now become a serious threat to global health. Quoting from the World Health Organization (WHO) data, 70% of the total deaths in the world are caused by non-communicable diseases. The position of diabetes as one of the silent killers in Indonesia may increase if this disease is not handled properly. In 2016, the percentage of deaths due to diabetes in Indonesia reached 6.7% and was the second highest after Sri Lanka. This figure is quite high because 2 out of 3 diabetics in Indonesia do not know that they have diabetes. Most of them only access health services when they are in a deteriorating condition, and even have complications.This became the basis for our group to create an expert system application using a deep learning/artificial neural network algorithm that aims to predict a patient will have acute diabetes with great accuracy.
Perancangan Sistem Business Intelligence Pada Data Perusahaan FNB X
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 4 (2023): JELIKU Volume 11 No 4, May 2023
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.2023.v11.i04.p06

Abstract

Nowadays, the use of technology as a tool for the success of a business has become very common. Sales and purchase transactions of a business are carried out using the latest technology that can make all transactions recorded on the system. However, in fact, the data is only a small thing in determining the success or decision-making of the leader of a company. By designing a system that can change business information from existing operational data, it can ultimately provide support for business decisions for company leaders.
Rancang Bangun Sistem Prediksi Kebutuhan Bahan Makanan Berbasis Web
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 4 (2023): JELIKU Volume 11 No 4, May 2023
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.2023.v11.i04.p28

Abstract

Abstract Prediction of food supplies is an activity of estimating the stock of foodstuffs that will be sold at a certain time, the supply of foodstuffs is determined by the estimation of future needs so that the seller can make the appropriate provision. When sales are predicted accurately, the fulfillment of consumer needs can be managed on time, the seller's cooperation with the relationship is maintained properly, customer satisfaction is met, the seller can overcome the loss of shortages or out of stock, prevent food ingredients from becoming damaged or stale. On the other hand, the seller can determine policy decisions on production plans, inventory, asset investment and cash flow. In other words, no salesperson can avoid estimating or forecasting sales for the purposes of planning the activities that must be carried out. Based on research conducted through application development in the form of a website displaying the results of sales of raw food ingredients based on time series data, the accuracy results obtained with an accuracy rate of 80% and through a black box evaluation it was found that the application has been running very well with a high level of respondents. shows a true value of 90% in the application that has been made. Keyword : forecasting, time series, web application, sales, raw food ingredients.
Implementasi Algoritma MFCC dan KNN dalam Identifikasi Nada Dasar Alat Musik Kendang
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 4 (2023): JELIKU Volume 11 No 4, May 2023
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.2023.v11.i04.p19

Abstract

Balinese kendang is a Balinese musical instrument that is closely related to the art of karawitan. Usually drums are played in a musical instrument show in Bali. Balinese drums are played in pairs, which consist of lanang drums and wadon drums. The sound features used in this system are extracted from the MFCC algorithm which are then classified using the KNN algorithm. The results of the system show the best classification results with an accuracy of 90% with parameter K = 1 and can correctly recognize 54 tones out of 60 tones.
Klasifikasi Penyakit Jantung Dengan Metode Convolutional Neural Network
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 4 (2023): JELIKU Volume 11 No 4, May 2023
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.2023.v11.i04.p11

Abstract

Penyakit jantung merupakan penyakit yang paling umum terjadi pada manusia. Di Indonesia, penyakit jantung masuk ke dalam salah satu penyakit yang paling banyak menyebabkan kematian. Tingginya angka kematian yang disebabkan penyakit jantung ini terjadi karenakurangnya kesadaran masyarakat terhadap makanan sehat, pengecekan Kesehatan secara berkala, dan kurangnya ahli jantung yang dimiliki. Penyakit jantung terjadi disaat kinerja jantung tidak berjalan seperti seharusnya atau mengalami kelainan. Kelainan ini dapat dideteksi melalui hasil pengolahan citra EKG. Ada beberapa penyebab dari kelainan jantung ini, diantaranya adalah serangan jantung, tekanan darah tinggi, stress, Usia, kolesterol total, kadar trigliserida, hipertensi, dan diabetes melitus. Faktor yang paling berpengaruh terhadap kejadian penyakit jantungadalah kolesterol. Penyakit jantung memilikibeberapa jenis klasifikasi, diantaranya adalah myocardial infarction, dan heart failure. Berdasarkan penyebab dan jenis penyakit jantungyang dapat terjadi pada manusia, maka dibutuhkan sebuah aplikasi yang dapat mengklasifikasi penyakit jantung secara dini dan mandiri.
Membandingkan Analisis Sentimen Review Pelanggan Shopee Dan Tokopedia Menggunakan Google's NLP API
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 4 (2023): JELIKU Volume 11 No 4, May 2023
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.2023.v11.i04.p02

Abstract

Dengan teknologi yang sudah sangat maju di jaman sekarang mempermudah kita manusia dalam berbelanja. Yang dulunnya kita harus berbelanja secara langsung namun sekarang kita bisa berbelanja secara online dengan E-Commerce yang ada. Transaksi e-commerce di Indonesia semakin meningkat, hal tersebut memberikan peluang pada produsen untuk memasarkan produk dan memudahkan konsumen untuk berbagi aktivitas, salah satu faktor yang sangat sering kita jumpai adalah memberikan ulasan produk. Ulasan produk berperan penting untuk membangun kepercayaan konsumen ketika menentukan keputusan dalam pembelian produk. Dengan meningkatnya jumlah ulasan, membuat calon konsumen kesulitan untuk menarik kesimpulan yang tepat. Oleh karena itu, diperlukan analisis sentimen untuk membantu calon konsumen untuk menarik kesimpulan. Analisis sentimen bertujuan untuk menyimpulkan, mengindentifikasi sentimen pada data yang ada. Disini kami akan melakukan Analisis Sentimen menggunakan Google Natural Language Processing dan membandingkan hasil ulasan applikasi Tokopedia dan Shopee pada Google Play Store
Identifikasi Forensik Biometrik Pada Individu Melalui Citra Sidik Bibir Menggunakan Descriptor Features
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 11 No 4 (2023): JELIKU Volume 11 No 4, May 2023
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.2023.v11.i04.p24

Abstract

Identifikasi biometrik menjadi begitu penting dan berkembang cukup pesat. Telah banyak bidang yang menggunakan identifikasi biometrik, salah satunya adalah dalam penyelidikan dan pemecahan kasus forensik seperti tindakan kriminal. Sidik bibir dapat menjadi salah satu metode identifikasi, karena polanya yang unik, stabil dan berbeda untuk setiap individu bahkan pada saudara kembar sekalipun. Identifkasi ini dapat dilakukan dengan bantuan pengolahan citra digital. Terdapat banyak metode yang dapat digunakan untuk melakukan identifikasi, salah satunya Speed Up Robust Features (SURF) dan Fast Approximate Nearest Neighbor (FANN) yang diakan digunakan pada penelitian ini. Data yang akan digunakan berupa data citra sidik bibir sebanyak 105 citra, yang kemudian akan diambil 15 citra sebagai data test dan 90 citra sebegai data refferal. Metode SURF akan mengektraksi fitur citra sidik bibir berupa descriptor yang kemudian akan dicocokkan menggunakan metode FANN. Skenario pengujian yang akan dilakukan dengan mengambil 5 kemungkinan calon yang cocok. Hasil pengujian menunjukkan telah berhasil mengidentifikasi sebanyak 12 individu dari total 15 individu dengan akurasi sebesar 80%.

Page 34 of 49 | Total Record : 488

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