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All Journal Jurnal Ilmu Komputer (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana Jurnal Ilmiah Kursor JOIV : International Journal on Informatics Visualization Specta Journal of Technology Jurnal Pengabdian Informatika (JUPITA) Jurnal Nasional Teknologi Informasi dan Aplikasinya
I Made Widiartha
Universitas Udayana
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Other

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Pengembangan Metode Klasterisasi Data Berbasis Hybrid Improved Artificial Bee Colony (IABC) dan K – Harmonic Means Musa, Saiful Bahri; Humaira, Fitrah Maharani; Widiartha, I Made; Herumurti, Darlis; Arifin, Agus Zainal; Fiqar, Tegar Palyus
Specta Journal Vol 2 No 3 (2018): SPECTA Journal of Technology
Publisher : Specta Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (466.517 KB) | DOI: 10.0610/specta.v2i3.3

Abstract

One of data grouping process method is k-harmonic clustering method (KHM) which has a relatively short and simple process. However, it has a weakness at cluster center point. Randomly formed cluster center point causes difficulty to converge solutions. One way to solve the problem at the cluster center point requires a method which has a global solution for KHM. The method is Improved artificial bee colony (IABC), improvement of artificial bee colony (ABC) method based on behavior patterns of honey bee colony in food searching process. Advantage of the IABC method is able to have more optimum global solution. This research proposes a new method of clustering using improved artificial bee colony and K-Harmonic means (IABC-KHM) to optimize the center point in clusters that lead to global solution. In this study, the IABC is functioned for finding the most optimum cluster center point for the data clustering process using KHM. Furthermore, the performance test of the IABC-KHM clustering method is compared with ABC and ABC-KHM methods on three different datasets. The result of mean value of best function of IABC-KHM method of Iris dataset is 152,87, Contraceptive Method Choice dataset is 918,54, and Wine dataset is 31,01. Moreover, the result of the average value of the best F-Measure method IABC-KHM Iris dataset is 0.90, the Contraceptive Method Choice dataset is 0.41, the Wine dataset is 0.95. To conclude, IABC-KHM method has successfully optimized the position of cluster center point that directs the cluster result which has global solution.
Pengembangan Metode Klasterisasi Data Berbasis Hybrid Improved Artificial Bee Colony (IABC) dan K – Harmonic Means Fiqar, Tegar Palyus; Musa, Saiful Bahri; Humaira, Fitrah Maharani; Widiartha, I Made; Herumurti, Darlis; Arifin, Agus Zainal
SPECTA Journal of Technology Vol 2 No 3 (2018): SPECTA Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (466.517 KB) | DOI: 10.35718/specta.v2i3.3

Abstract

One of data grouping process method is k-harmonic clustering method (KHM) which has a relatively short and simple process. However, it has a weakness at cluster center point. Randomly formed cluster center point causes difficulty to converge solutions. One way to solve the problem at the cluster center point requires a method which has a global solution for KHM. The method is Improved artificial bee colony (IABC), improvement of artificial bee colony (ABC) method based on behavior patterns of honey bee colony in food searching process. Advantage of the IABC method is able to have more optimum global solution. This research proposes a new method of clustering using improved artificial bee colony and K-Harmonic means (IABC-KHM) to optimize the center point in clusters that lead to global solution. In this study, the IABC is functioned for finding the most optimum cluster center point for the data clustering process using KHM. Furthermore, the performance test of the IABC-KHM clustering method is compared with ABC and ABC-KHM methods on three different datasets. The result of mean value of best function of IABC-KHM method of Iris dataset is 152,87, Contraceptive Method Choice dataset is 918,54, and Wine dataset is 31,01. Moreover, the result of the average value of the best F-Measure method IABC-KHM Iris dataset is 0.90, the Contraceptive Method Choice dataset is 0.41, the Wine dataset is 0.95. To conclude, IABC-KHM method has successfully optimized the position of cluster center point that directs the cluster result which has global solution.
Mangrove ecosystem Segmentation from Drone Images using Otsu Method Pratiwi, Ni Made Dinda; Widiartha, I Made
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.p10

Abstract

Mangrove ecosystems are found mainly in tropical and subtropical coastal areas. they are playing a very important ecological role in land-ocean interfaces. These ecosystems are protecting the environment and providing a habitat that supports many living organisms. Identification of area images in mangrove ecosystems is very helpful in monitoring and conservation of this ecosystem. In this study, we will present the segmentation of drone image taken from TAHURA Ngurah Rai mangrove area using otsu method. The otsu method giving well accuracy to segmented image to divide mangrove area and non mangrove area. Because Otsu method operates on a grayscale image so that it cannot distinguish the dark green of the tree canopies from the dark shadows of the trees, then the segmentation accuracy will decrease.
Prediction Of The Number Of Tourists To Visit Bali Province Using Backpropagation Artificial Neural Network (Case Study: Data 1990-2016) Panji Palguna, I Gusti Agung Ngurah; Widiartha, I Made
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 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.v08.i03.p05

Abstract

Bali Island is the most popular tourist destination in Indonesia. The total number of foreign tourists visiting Indonesia through the entrance of Ngurah Rai Airport reached 40% as of October 2016, with the value of Bali's foreign exchange receipts for Indonesia from the tourism sector amounting to 70 Trillion Rupiah. Minister of Tourism (Menpar) Arief Yahya always uses the password "Bali" in promoting destinations throughout the world. Because in tourism, Bali is a gate that is passed by 40 percent of foreign tourists (tourists) to Indonesia. In support of more accurate decision making, the author makes a system of forecasting numbers of foreign tourists visiting Bali Province by taking a sample of Japan. Factors that are used as input to make predictions include the number of tourists visiting before, the population of the country of origin of foreign tourists, Gross Domestic Product, and the Relative Consumer Price Index of the countries of origin of foreign tourists. In this research, optimization of the activation function, hidden neuron, and learning rate parameters is performed. Forecasting results using the backpropagation method produce a pretty good accuracy with an accuracy of Mean Square Error = 0.0050558, and test data accuracy of MSE = 0.031695. ANN architecture in the training process is then used to calculate predictions of visits by foreign tourists in the testing process
ANALISIS DESAIN SISTEM PENDUKUNG KEPUTUSAN UNTUK MENENTUKAN PRIORITAS KEBUTUHAN BARANG DAN JASA DI RUMAH SAKIT UMUM DENGAN METODE ANALYTIC HIERARCY PROCESS (Studi Kasus Rumah Sakit Umum Bangli) bratha, dede khausa bayu; Widiartha, I Made
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 7 No 4 (2019): JELIKU Volume 7 No 4, Mei 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.v07.i04.p05

Abstract

Rumah sakit merupakan salah satu fasilitas yang diberikan oleh pemerintah dalam bidangkesehatan. Untuk meningkatkan kualitas peyalanan, Rumah Sakit Umum membutuhkananggaran dana yang cukup besar. Salah satu masalah pada rumah sakit umum bangli adalahbanyaknya anggaran biaya untuk disetiap unit dan bidang perencanaan sulit untuk menentukanprioritas untuk setiap kebutuhan di setiap unit. Oleh karena itu, untuk meningkatkan efektifitasserta efisiensi dari proses penyusunan prioritas tersebut dibuatlah sebuah sistem pendukungkeputusan penentuan prioritas kebutuhan barang dan jasa untuk disetiap ruangan di rumah sakitumum bangli dengan berbasis web.
Perancangan dan Implementasi Sistem Manajemen Proyek Perangkat Lunak Menggunakan Teknologi Single Page Application Wikardiyan, Aditya; Widiartha, I Made; Rahning Putri, Luh Arida Ayu
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 4 (2020): JELIKU Volume 8 No 4, Mei 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.v08.i04.p17

Abstract

Pekerjaan secara berkelompok memerlukan koordinasi yang tepat, sehingga tujuan dari pekerjaan dapat tercapai secara maksimal dan sesuai dengan yang diharapkan oleh setiap anggota. Keterlibatan teknologi informasi dapat memberi kemudahan bagi seluruh anggota dalam sebuah kelompok kerja untuk melakukan koordinasi tim, pengerjaan tugas dan pemantauan pekerjaan dengan lebih efisien dan efektif, tetapi meskipun begitu platform yang tersedia menjadi tersebar dan tidak terpusat pada satu platform saja dikarenakan sistem yang telah ada belum mengandung komunikasi dari sesama user, yang menyebabkan saat user ingin berkomunikasi dengan anggota tim harus menggunakan aplikasi komunikasi lain yang menjadikan hal ini kurang efisien. Menyelesaikan masalah dari hal-hal tersebut maka diperlukan Sistem Manajemen Proyek Perangkat Lunak (SMPPL) yang sifatnya online berbasis website sehingga dapat dengan mudah diakses dari mana saja dan mendukung komunikasi antar user dengan anggota tim secara efisien. Sistem ini menerapkan teknologi Single Page Application (SPA). Single Page Application (SPA) akan meningkatkan kecepatan memuat website karena hanya mengambil bagian-bagian tertentu sesuai kebutuhan dari setiap halaman website tanpa memuat keseluruhan resource saat adanya interaksi berpindah halaman yang dilakukan user.
Implementasi Learning Vector Quantization(LVQ) untuk KLasifikasi Penyakit Ginjal Kronis Pramana, I Gst Bgs Bayu Adi; Widiartha, I Made; Astuti, Luh Gede
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.p11

Abstract

Chronic kidney disease is a disruption in the function of the kidney organs. When the kidneys are no longer fully functioning, the body is filled with water and a waste product called uremia. As a result, the body or legs will experience swelling and feel tired quickly because the body needs clean blood. Therefore, impaired kidney function should not be underestimated because it can be fatal. Researchers have conducted research related to the classification of kidney disease to find out what symptoms can cause kidney disease. One method that can be used for classification is the Learning Vector Quantization (LVQ) method. In this study, the LVQ algorithm was applied to classify chronic kidney disease. From the research results, the highest accuracy is 81.667% with the optimal learning rate is 0.002.
Gaussian Filtering Method to Remove Noise in Images Satya, I Dewa Gede Rama; 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.p07

Abstract

Capturing every moment is not taboo in this era. One way to capture the moment is to use a photo, but the results are often unsatisfactory. Noise, is one of the many causes of unsatisfactory results. Noise is a disturbance caused by digital data storage received by the image data receiver which can interfere with image quality. Noise can be caused by physical (optical) disturbances in the image capturing device, such as dust on the camera lens or due to improper processing. To get rid of this noise, you can use various methods, of which Gaussian Filtering is one of them. In this research, we will implement it using Matlab. The type of file used is a photo that has a jpg format and has noise above 75%. After doing image processing, it shows the results of the image which initially has noise and after the image quality improvement process is carried out, the image quality is clearer and the noise decreases.
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.
Classification of Pop and RnB (Rhythm and Blues) Songs with MFCC Feature Extraction and K-NN Classifier Ramadhan, Zhaqy Hikkammi Gullam; Widiartha, I Made
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.p09

Abstract

Classification is a technique for designing functions based on observations of attributes in a data so that data can be mapped that do not have a class which in this study can be called genres, into data that has been classified according to the given rules. In this research, music classification is conducted to determine whether the class or genre of music is pop or RnB (Rhythm and Blues) by using MFCC as the feature extraction method and K-NN as the classification method. The test results in this study obtained an accuracy of 77.5% with an optimal value of k = 31 as a parameter in K-NN.
Co-Authors A A I N Karyawati Agus Muliantara Agus Zainal Arifin Alit Indrawan, I Gusti Ngurah Alvin Wiraprathama Anak Agung Istri Ngurah Eka Karyawati Anggotra, Puspadevi Anny Yuniarti Apsari, Made Sri Ayu Ari Mogi, I Komang Arsa, Dewa Made Sri Astawa, Ni Wayan Amanda Putri Atmojo, Firman Ali Eka Ayu Nikki Asvikarani bratha, dede khausa bayu Darlis Herumurti Dewa Made Wiharta Firman Ali Eka Atmojo Gede Agung Aji Andar Sakti Gede Wisnu Bhaudhayana Gilang Indrawan, Muhammad Caesar Giri, I Nyoman Yusha Tresnatama Gst. Ayu Vida Mastrika Giri Humaira, Fitrah Maharani Humaira, Fitrah Maharani I Dewa Made Bayu Atmaja Darmawan, I Dewa Made Bayu I Gede Arta Wibawa I Gede Santi Astawa I Gusti Agung Gede Arya Kadyanan I Gusti Ngurah Anom Cahyadi Putra I Kadek Aldy Oka Ardita I Ketut Gede Suhartana I Made Eko Satria Wiguna I Made Nusa Yudiskara I Made Satria Bimantara I Putu Bayu Eka Pratama I Putu Gede Hendra Suputra I WAYAN SANTIYASA I Wayan Sugiana I Wayan Supriana Ida Bagus Gede Dwidasmara Ida Bagus Gede Dwidasmara Ida Bagus Made Mahendra Julianti, Syelvia Kadek Nanda Banyu Permana Ketut Ardha Chandra Kusuma, Putu Agus Dharma Luh Arida Ayu Rahning Putri Luh Gede Astuti Luh Gede Astuti Nathanael Richie Thomas Ngurah Agus Sanjaya ER Ni Made Elvina Aryadhika Putri Nyoman Putra Sastra Octavia, Hana Christine Panji Palguna, I Gusti Agung Ngurah Pijar Candra Mahatagandha Pramana, I Gst Bgs Bayu Adi PRATIWI, NI MADE DINDA Priandana, Bhisma Satwika Ari Purba, Kevin Joel Putra, I Gusti Ngurah Agung Widiaksa Raharja, Made Agung Ramadhan, Zhaqy Hikkammi Gullam Rukmi Sari Hartati Ryan, Ida Bagus Putu Saiful Bahri Musa Satria Wiguna, I Made Eko Satya, I Dewa Gede Rama Sitinjak, Anugrah Ignatius Tegar Palyus Fiqar Widnyana, I Kadek Agus Candra Wijaya, Partha Wikardiyan, Aditya Wiraprathama, Alvin