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Cover & Table of Contents JELIKU Vol. 9 No. 1 Vida Mastrika Giri, Gst Ayu
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 1 (2020): JELIKU Volume 9 No 1, Agustus 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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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

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Cover & Table of Contents Vol. 9 No. 4 Vida Mastrika Giri, Gst Ayu
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

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Cover & Table of Contents JELIKU Vol. 10 No. 1 Vida Mastrika Giri, Gst Ayu
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

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Peningkatan Fungsi UKS Dalam Memberikan Pendidikan Kesehatan Awal Berbasis IPTEKPada Sekolah Dasar Desa Belatungan Cahyadi Putra, I Gusti Ngurah Anom; Eka Karyawati, A. A. Istri Ngurah; Raharja, Made Agung; Mastrika Giri, Gst. Ayu Vida; Widiartha, I Made
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 1 (2020): JELIKU Volume 9 No 1, Agustus 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.i01.p07

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Usaha Kesehatan Sekolah (UKS) is a basic health business owned by a school. One of the functions of UKS is as a forum to provide early health education to school children. In primary schools the UKS maggot village does not function optimally, because there are no facilities and infrastructure to support UKS activities. Through the Udayana Mengabdi Program, assistance is provided for facilities and infrastructure, such as first aid kits, weighing instruments, temperature measuring instruments and height measuring instruments. Booked the administration of health records for elementary school students. From the programs that have been implemented, a survey is conducted to measure the success rate. After the service program was conducted the average level of knowledge of students about the function of UKS increased. As well as UKS in elementary schools, it should function properly as a place to provide early health education to elementary school children.
Cover & Table of Contents JELIKU Vol. 10 No. 2 Vida Mastrika Giri, Gst Ayu
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 10 No 2 (2021): JELIKU Volume 10 No 2, November 2021
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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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

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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).
Cover, Table of Contents, Editorial Boards of JIK Vol 11 No 1 Gst Ayu Vida Mastrika Giri
Jurnal Ilmu Komputer Vol 11 No 1 (2018): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

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Klasifikasi Musik Berdasarkan Genre Gst Ayu Vida Mastrika Giri
Jurnal Ilmu Komputer Vol 11 No 2 (2018): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (153.171 KB) | DOI: 10.24843/jik.2018.v11.i02.p05

Abstract

Genre musik adalah salah satu cara yang sangat umum digunakan untuk mengatur database musik digital. Dengan bertambahnya jumlah musik, tentunya pemberian genre secara maual akan membutuhkan banyak tenaga ahli dan waktu yang lama. Saat ini, pemberian genre musik secara otomatis dapat membantu menyelesaikan masalah tersebut. Berbagai teknik klasifikasi dan fitur musik telah digunakan untuk klasifikasi musik berdasarkan genre. Penelitian ini membahas tentang klasifikasi musik berdasarkan genre (classical, EDM, hip-hop, metal, pop, punk, R&B, rap, dan rock) dengan metode K-Nearest Neighbor dengan menggunakan 11 fitur musik (speechiness, energy, danceability, loudness, tempo, mode, valence, instrumentalness, acoustic-ness, dan liveliness). Nilai akurasi klasifikasi pada penelitian ini adalah 44,8%. Nilai tertinggi ada pada genre classical, dengan total akurasi 100% dan nilai terendah ada pada genre pop dengan akurasi 25%.
Back Cover of JIK Vol 11 No 1 Gst Ayu Vida Mastrika Giri
Jurnal Ilmu Komputer Vol 11 No 1 (2018): Jurnal Ilmu Komputer
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (78.759 KB)

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