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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 7 Documents
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Search results for , issue "Vol 10 No 3 (2022): JELIKU Volume 10 No 3, February 2022" : 7 Documents clear
VOCAL TONE PRECISION DETECTION USING HARMONIC PRODUCT SPECTRUM (HPS) AND K-NEAREST NEIGHBOR (KNN) CLASSIFICATION Apsari, Made Sri Ayu; Widiartha, I Made; Agung Raharja, Made; Santi Astawa, I Gede; Arta Wibawa, Gede; Made Mahendra, Ida Bagus
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 3 (2022): JELIKU Volume 10 No 3, February 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.v10.i03.p01

Abstract

The progress of the digital era that is happening today, encourages rapid development in technology and science, one of which is in the field of art. Of all performing arts, the art of singing is the most complex, which requires a lot of preparation and practice. Everyone has a different type of voice. Males generally have three types of voice, namely bass, baritone, and tenor, while women generally have three types of voice, namely contralto (alto), mezzo-soprano, and soprano. However, not everyone knows what kind of voice they have. Therefore, this study will focus on classifying the human voice. In this study, the author uses the Harmonic Product Spectrum (HPS) and K-Nearest Neighbor (K-NN) algorithms. The data used is in the form of primary voice recording data obtained from 258 participants (male and female), where each person has 8 sound files, namely do, re, mi, fa, sol, la, si, and do'. saved in .wav format. From the research conducted, the test was carried out using the K-NN and K-NN methods with Hyperparameters. The results obtained in the form of accuracy of 74% and 81%, so that the Harmonic Product Spectrum (HPS) and K-Nearest Neighbor (K-NN) algorithms give good results for determining the type of human voice.
Music Genre Classification Using Modified K-Nearest Neighbor (MK-NN) Giri, I Nyoman Yusha Tresnatama; Rahning Putri, Luh Arida Ayu; Mastrika Giri, Gst Ayu Vida; Anom Cahyadi Putra, I Gusti Ngurah; Widiartha, I Made; Supriana, I Wayan
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 3 (2022): JELIKU Volume 10 No 3, February 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.v10.i03.p02

Abstract

The genre of music is a grouping of music according to their resemblance to one another and commonly used to organize digital music. To classify music into certain genres, one can do it by listening to the music one by one manually, which will take a long time so that automatic genre assignment is needed which can be done by a number of methods, one of which is the Modified K-Nearest Neighbor. Modified K-Nearest Neighbor method is a further development of its former method called KNearest Neighbor method which adds several additional processes such as validity calculations and weight calculations to provide more information in the selection class for the testing data. Research to find the best H value shows that the H = 70% of the training data is able to produce an accuracy of 54.100% with K = 5 and the proportion ratio of test data and training data is 20:80 (fold 5). The best H value is then used for further testing, which is to compare the K-Nearest Neighbor method with the Modified K-Nearest Neighbor method using two different proportions of test data and training data and each proportion of data also tests a different K value. The results of the classification comparison of the two methods show that the Modified K-Nearest Neighbor method, with the highest accuracy of 55.300% is superior to the K-Nearest Neighbor method with the highest accuracy of 53.300%. The two highest accuracies produced in each method were obtained using K = 5 and the proportion ratio of test data and training data is 10:90 (fold 10).
Analisis Forensik Digital pada Aplikasi Twitter di Android sebagai Bukti Digital dalam Penanganan Kasus Prostitusi Online Pratama, Sang Putu Febri Wira; Putra, I Gusti Ngurah Anom Cahyadi; Hamid, Muhammad Akbar; Christian, Calvin; Merdana, I Ketut Kusuma
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 3 (2022): JELIKU Volume 10 No 3, February 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.v10.i03.p03

Abstract

At this time the use of social media from time to time has experienced rapid development, one of which is the social media twitter. Twitter social media has many benefits such as making tweets about daily activities. However, Twitter social media has a negative side in its use, one of which is online prostitution. Prostitution is an act of cyber crime that violates the rules and norms that exist in society. Therefore, to overcome these cyber crimes, the necessary action is to review online prostitution on Twitter social media. In this study, a digital forensic analysis was conducted on Twitter social media on smartphones related to acts of prostitution using the National Institute of Justice (NIJ). Based on the research conducted, digital evidence is obtained that can be accounted for by the perpetrators.
Analisis Keamanan Aplikasi Android Dengan Metode Vulnerability Assessment Ardita, I Kadek Aldy Oka; Anom Cahyadi Putra, I Gusti Ngurah; Kustiadie, Mohammad Rizky; Dika Varuna, Gusti Ngurah Made; Eka Prananda, Made Yayang
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 3 (2022): JELIKU Volume 10 No 3, February 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.v10.i03.p04

Abstract

Seiring berkembangnya beragam aplikasi maka sistem Android haruslah tahan terhadap bebagai serangan malware dengan mengamati izin akses yang diberikan oleh pengguna. Penyerang dapat menggunakan kerentanan dalam aplikasi untuk mencuri berbagai informasi penting. Informasi merupakan aset penting dan berharga berupa rekaman suara, rekaman video, catatan, dll. Oleh karena itu, diperlukan suatu analisis keamanan. dari aplikasi yang digunakan dengan tes / tindakan pada tingkat keamanan aplikasi. Dalam melakukan Vulnerability test atau proses identifikasi celah keamanan pada aplikasi android dilakukan dua teknik yaitu dengan MobSF dan dengan frida. Hasil dari Analisis MobSF sangat terlihat perbedaannya antara mendownload aplikasi melalui pihak ketiga dengan mendownload aplikasi melalui Play Store. Dimana nilai hash yang didapat sangat berbeda baik dari md5, sha1, atau sha256, dari hasil tersebut dapat diketahui bahwa ada perubahan pada file yang disediakan oleh penyedia pihak ketiga. Pada security score didapatkan bahwa aplikasi yang di download melalui pihak ketiga terdapat banyak server dan aktivitas mencurigakan, sedangkan aplikasi yang terdapat di playstore terdapat 2 server yang asli. Pada size, ukuran file yang disediakan oleh pihak ketiga, ukuran file asli hanya 20.37MB sedangkan file yang di sediakan oleh pihak ketiga berukuran 61.33MB. Pada analisis menggunakan frida dilakukan proses penyerangan yaitu bypass login. Dimana pada aplikasi pihak ketiga sudah memiliki email yang telah diinputkan oleh penyedia aplikasi. Dari hasil analisis yang dilakukan maka lebih baik untuk mendownload aplikasi melalui playstore agar lebih aman. Karena sebagai pengguna awam tidak akan tahu perubahan file apa yang dilakukan dan beresiko atau tidaknya perubahan tersebut terhadap perangkat tersebut
Comparison of K-Nearest Neighbor And Modified K-Nearest Neighbor With Feature Selection Mutual Information And Gini Index In Informatics Journal Classsification
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 3 (2022): JELIKU Volume 10 No 3, February 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.v10.i03.p05

Abstract

With the rapid development of informatics where thousands of informatics journals have been made, a new problem has occured where grouping these journals manually has become too difficult and expensive. The writer proposes using text classification for grouping these informatics journals. This research examines the combinations of two machine learning methods, K-Nearest Neighbors (KNN) and Modified K-Nearest Neighbors with two feature selection methods, Gini Index (GI) and Mutual Information (MI) to determine the model that produces the higherst evaluation score. The data are informatics journals stored in pdf files where they are given one of 3 designated labels: Information Retrieval, Database or Others. 252 data were collected from the websites, neliti.com and garuda.ristekbrin.go.id. This research examines and compares which of the two methods, KNN and MKNN at classifying informatics journal as well as determining which combination of parameters and feature selection that produces the best result. This research finds that the combination of method and feature selection that produces the best evaluation score is MKNN with GI as feature selection producing precision score, recall score and f1-score of 97.7%
Rancang Bangun Portal Lowongan Pekerjaan Berbasis Web Dengan Fitur Rekomendasi
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 3 (2022): JELIKU Volume 10 No 3, February 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.v10.i03.p06

Abstract

Tingginya tingkat pengangguran di Indonesia yang disebabkan oleh dampak pertumbuhan penduduk yang padat dan sulitnya mencari pekerjaan yang mengakibatkan pertumbuhan ekonomi tidak stabil menjadi tantangan bagi pemerintah untuk menanggulangi masalah pengangguran. Salah satu faktor yang mempengaruhi tingkat pengangguran yang tinggi adalah penyebaran informasi lowongan kerja yang kurang merata. Pelamar kerja sering kesulitan untuk mendapatkan informasi pekerjaan yang sesuai dengan kemampuan dan keterampilan yang dimiliki. Dengan dibuatnya sistem rekomendasi lowongan kerja, diharapkan dapat menyelesaikan masalah yang dialami seorang pelamar yang ingin melamar pekerjaan yang sesuai dengan kemampuannya. Dengan menggunakan algoritma euclidean distance, sistem diharapkan dapat memberikan hasil rekomendasi berdasarkan beberapa parameter yang sesuai dengan keinginan pelamar. Parameter yang dimaksudkan adalah usia, jenis kelamin, pendidikan, jurusan, gaji, keterampilan, pengalaman kerja, dan kategori pekerjaan yang diinginkan. Penelitian ini menghasilkan kesimpulan yaitu berdasarkan hasil pengujian precision recall sistem rekomendasi lowongan kerja menggunakan metode euclidean distance menghasilkan nilai precision sebesar 0,94 atau 94% dan nilai recall sebesar 0,94 atau 94%.
Cover & Table of Contents Vol. 10 No. 3
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 3 (2022): JELIKU Volume 10 No 3, February 2022
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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