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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmu Komputer (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana Jurnal Sains dan Teknologi Jurnal Buana Informatika Jurnal Ilmiah Kursor JUTIK : Jurnal Teknologi Informasi dan Komputer JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal RESISTOR (Rekayasa Sistem Komputer) WIDYA LAKSANA Seminar Nasional Aplikasi Iptek (SINAPTEK) Jurnal Pengabdian Informatika (JUPITA) Paradharma: Jurnal Aplikasi IPTEK Jurnal Nasional Teknologi Informasi dan Aplikasinya
I Wayan Supriana
Universitas Udayana
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Other

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Pengembangan Sistem Informasi Manajemen Tuas Akhir Program Studi Teknik Informatika Universitas Udayana Adiartika, Made Harry Dananjaya; Supriana, I Wayan
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.p02

Abstract

Bagi seorang Mahasiswa sebuah Tugas Akhir merupakan sebuah persyaratan bagi seorang mahasiswa untuk menyelesaikan pendidikannya serta sebelum menyandang gelar sarjana, dalam pembuatannya terdapat berbagai proses administrasi sebelum mendapatkan penilaian terhadap tugas akhir mereka, dalam mengelola atau memanajemen berbagai proses tersebut Program Studi Teknik Informatika Universitas Udayana memiliki sebuah sistem yang digunakan untuk mengelola berbagai proses tersebut, namun dengan berjalannya waktu permintaan akan fitur yang dapat mempermudah berbagai proses tersebut semakin bertambah sehingga diperlukan sebuah sistem baru yang dapat memenuhi berbagai permintaan tersebut, sehingga pada penelitian ini penulis bertujuan untuk merancang serta mengimplementasikan sebuah sistem informasi tugas akhir dimana penulis berfokus pada proses administrasi dokumen tugas akhir mahasiswa, sistem informasi ini dikembangkan berbasis website dengan framework CodeIgniter sebagai backend dari sistem
Segmentasi Baris Aksara Bali Pada Citra Lontar Prashanti, Ni Putu Vidya Vira; Santi Astawa, I Gede; Ngurah Eka Karyawati, Anak Agung Istri; Santiyasa, I Wayan; Gede Dwidasmara, Ida Bagus; Supriana, I Wayan
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2021.v10.i02.p03

Abstract

Indonesia merupakan negara kepulauan yang disetiap pulaunya memiliki kebudayaan yang berbeda-beda, seperti misalnya Pulau Bali yang sangat kaya akan warisan budaya, salah satunya yaitu aksara Bali. Aksara Bali merupakan lambang bahasa masyarakat Bali yang sampai saat ini masih digunakan. Salah satu media yang dimanfaatkan untuk menuliskan aksara Bali yaitu lontar dapat mengalami penurunan kualitas dikarenakan usia yang semakin tua. Hal tersebut tentunya berpengaruh terhadap tulisan aksara Bali yang terdapat pada lontar, sehingga menyulitkan pembaca untuk mengetahui informasi yang terkandung pada lontar tersebut. Upaya yang dapat dilakukan untuk menyelamatkan informasi yang terkandung pada lontar adalah dengan mengubahnya kedalam bentuk digital. Tulisan aksara Bali pada lontar terkadang memiliki jarak yang dekat antar baris aksara sehingga karakter aksara pada baris satu dengan karakter aksara pada baris lainnya bersentuhan. Aksara yang bersentuhan juga dapat menyulitkan pembaca memahami makna dari tulisan tersebut. Aksara yang paling sering bersentuhan adalah gantungan pada kasara baris atas dengan pengangge pada baris aksara dibawahnya. Oleh karena itu, diperlukan segmentasi baris untuk menemukan dan memperjelas baris pemisah antara aksara pada baris satu dengan aksara pada baris lainnya. Proses segmentasi baris aksara Bali dilakukan menggunakan Algoritma Genetika. Algoritma Genetika akan mencari kromosom dengan nilai fitness terbaik. Gen pada kromosom tersebut mewakili baris piksel citra biner yang diambil secara acak sesuai batas area segmentasi. Berdasarkan hasil pengujian yang telah dilakukan terhadap 10 bilah citra lontar, diperoleh hasil akurasi proses segmentasi baris aksara Bali menggunakan Algoritma Genetika adalah sebesar 92.17%.
IDENTIFICATION OF HOAX BASED ON TEXT MINING USING K-NEAREST NEIGHBOR METHOD Santiyasa, I Wayan; Brahmantha, Gede Putra Aditya; Supriana, I Wayan; Kadyanan, I GA Gede Arya; Suhartana, I Ketut Gede; Mahendra, Ida Bagus Made
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2021.v10.i02.p04

Abstract

At this time, information is very easy to obtain, information can spread quickly to all corners of society. However, the information that spreaded are not all true, there is false information or what is commonly called hoax which of course is also easily spread by the public, the public only thinks that all the information circulating on the internet is true. From every news published on the internet, it cannot be known directly that the news is a hoax or valid one. The test uses 740 random contents / issue data that has been verified by an institution, where 370 contents are hoaxes and 370 contents are valid. The test uses the K-Nearest Neighbor algorithm, before the classification process is performed, the preprocessing stage is performed first and uses the TF-IDF equation to get the weight of each feature, then classified using K-Nearest Neighbor and the test results is evaluated using 10-Fold Cross Validation. The test uses the k value with a value of 2 to 10. The optimal use of the k value in the implementation is obtained at a value of k = 4 with precision, recall, and F-Measure results of 0.764856, 0.757583, and 0.751944 respectively and an accuracy of 75.4%
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).
Simulasi Antrian Jaringan Multi Server Menggunakan Metode Open Jackson I Wayan Supriana; Subanar Subanar
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 7, No 2 (2013): July
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.3358

Abstract

AbstrakAntrian paket data pada jaringan komputer memiliki model antrian jaringan, dimana proses transmisi yang rumit sehingga tidak dapat diselesaikan secara analitik. Pemodelan dan simulasi diperlukan untuk menyelesaikan masalah antrian jaringan. Model antrian dalam penelitian ini adalah jaringan terbuka dengan analisis paket data menggunakan model server tunggal. Waktu pelayanan paket memiliki distribusi Eksponensial dan distribusi Erlang yang digunakan sebagai pembanding. Jika waktu pelayanan paket data menggunakan distribusi Eksponensial maka model menjadi M/M/1, sedangkan waktu pelayanan paket data menggunakan distribusi Erlang dengan parameter m dan µ, maka model menjadi M/E[m]/1. Penelitian ini menggunakan metode open Jackson untuk melakukan simulasi antrian jaringan guna menghitung nilai karakteristik jaringan. Pengujian sistem simulasi menggunakan packet switching network pada server jaringan komputer Jurusan Ilmu Komputer Universitas Udayana untuk mengetahui performansi sistem yang menggunakan distribusi waktu pelayanan berbeda. Hasil pengujian menunjukkan bahwa waktu pelayanan distribusi Eksponensial memiliki karakteristik yang lebih baik dari distribusi Erlang pada parameter m-Erlang ≥ 2.  Kata kunci— antrian jaringan, distribusi,sistem performansi, multi server.  AbstractQueue data packet at computer network having a network queueing model, with complicated transmission process so that it can not be solved analytically. Modeling and simulation are needed to resolve the issue queue network. Queueing model in this research is an open network with the analysis of data packet using a single server model. Service time packet has Exponential distribution and Erlang used as comparison. If the service time of data packet using the Exponential distribution, then the model become M/M/1, whereas the service time using the Erlang distribution with parameter m and µ, then the model becomes M/E[m]/1. This research uses an open Jackson method to perform queueing network simulations to calculate the characteristics of network queueing system. Examination of simulation system uses data packets on a computer network server of Department Computer Science University of Udayana to determine system performance using with different service time distribution. The result of examination indicate that service time of Exponential distribution has better characteristic then Erlang distribution at parameter m-Erlang ≥2. Keywords— queueing network, distribution, system performance, multiple server
PERANCANGAN SISTEM PENDUKUNG KEPUTUSAN PENILAIAN PENERIMA BANTUAN BEDAH RUMAH DENGAN METODE PEMOBOBOTAN I Wayan Supriana
Jurnal Ilmu Komputer Vol 9 No 2: September 2016
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (343.428 KB)

Abstract

Dalam Penelitian ini keluaran yang dihasilkan berupa rancangan sistem informasi menjadi salah satu alat pendukung keputusan pada penilaian bantuan bedah rumah. Penilaian bantuan bedah rumah yang dilakukan masih konvensional sehingga perlu adanya sistem yang membantu dalam minilai calon pemohon secara obyektif. Terdapat 14 faktor kelayakan yang digunakan untuk menilai calon pemohon pengajuan bantuan bedah rumah. Adapun foktor tersebut adalah luas alas rumah, jenis alas  rumah, jenis tembok rumah, jenis dan kondisi atap rumah, Kondisi fasilitas WC, sumber pencahayaan rumah, air konsumsi rumah tangga, bahan energi untuk memasak, konsumsi jenis makanan dalam  satu minggu, kemampuan beli pakaian baru untuk setiap rumah tangga dalam setahun, kemampuan berobat ke puskesma dalam sebulan, pekerjaan kepala rumah tangga, tingkat pendidikan kepala rumah tangga, tidak memiliki tabungan. Dalam penelitian ini rancangan sistem penilaian bantuan bedah rumah dengan metode pembobotan dapat di lakukan perancangannya, serta proses uji model rancangan memberikan optimalitas dalam penilaian.
SISTEM PENDUKUNG KEPUTUSAN DALAM PEMILIHAN TEMPAT KOST DENGAN METODE PEMBOBOTAN ( STUDI KASUS : SLEMAN YOGYAKARTA) I Wayan Supriana
Jurnal Ilmu Komputer Vol 5 No 2: September 2012
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (640.665 KB)

Abstract

Penentuan tempat tinggal di daerah yang baru dikenal dipengaruhi oleh banyak factor, diantaranyalokasi, fasilitas, sistem kontrak dan harga. Makalah ini menentukan kriteria-kriteria yang digunakandidalam pemilihan tempat tinggal. kriteria-kriteria tersebut dianalisis menggunakan metodepembobotan. Hasil analisis yang didapat berupa kriteria lokasi untuk menentukan tempat kost yangpaling sesuai.
Optimalisasi Penyelesaian Knapsack Problem Dengan Algoritma Genetika I Wayan Supriana
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol. 7, No. 3 Desember 2016
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (498.783 KB) | DOI: 10.24843/LKJITI.2016.v07.i03.p06

Abstract

Knapsack problems is a problem that often we encounter in everyday life. Knapsack problem itself is a problem where a person faced with the problems of optimization on the selection of objects that can be inserted into the container which has limited space or capacity. Problems knapsack problem can be solved by various optimization algorithms, one of which uses a genetic algorithm. Genetic algorithms in solving problems mimicking the theory of evolution of living creatures. The components of the genetic algorithm is composed of a population consisting of a collection of individuals who are candidates for the solution of problems knapsack. The process of evolution goes dimulasi of the selection process, crossovers and mutations in each individual in order to obtain a new population. The evolutionary process will be repeated until it meets the criteria o f an optimum of the resulting solution. The problems highlighted in this research is how to resolve the problem by applying a genetic algorithm knapsack. The results obtained by the testing of the system is built, that the knapsack problem can optimize the placement of goods in containers or capacity available. Optimizing the knapsack problem can be maximized with the appropriate input parameters.
METODE PENALARAN BERBASIS KASUS (CASE BASE REASONING) DALAM PENENTUAN KELAYAKAN SEKOLAH PERAWATAN I Wayan Supriana; Kiki Dwi Prebiana
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 3 No. 1 (2020): Jurnal RESISTOR Edisi April 2020
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v3i1.554

Abstract

Nurse is a job that has many roles in everyday life. Obtained from the ability to become a nurse. In 1980, there was an explosion in the number of registrants at the Ljubljana nursing school, Slovenia. The data is then collected in a data collected data that is a nursery dataset. There are several things related to health conditions, family status, financial conditions and other things that are considered feasible or not to enter the nursing school. A system that can be used for this problem needs to be created. In this study, a system will be made by applying the method of punishment based on cases and classifying domains to increase computational time. Each new case will be calculated the similarity value to the old case using the Bayes naive algorithm. The system built will produce a decision about whether or not the applicant is suitable in nursing school. Of the 100 data tested, 96 data were obtained that produced true values. With a computing time between 0.253 seconds - 0.607 seconds.
SISTEM REKOMENDASI MUSIK BERDASARKAN DATA KONTEKS PADA LISTENING HISTORY MUSIK DAN KETERKAITAN ARTIS INDONESIA Gst Ayu Vida Mastrika Giri; Made Leo Radhitya; Made Agung Raharja; I Wayan Supriana
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 5 No. 1 (2022): Jurnal RESISTOR Edisi April 2022
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v5i1.1044

Abstract

A large number of digital music circulates online today. It makes music listeners confused to choose which music is suitable to listen to in certain circumstances or contexts, for example certain time, weather, activity, and desired mood. Playlist creation can make it easy for music listeners to collect their favorite music for a particular context, but creating playlists is time consuming and of course a lot of playlists will have to be created to accommodate all combinations of contexts. In this study, an automated music recommendation system was built using context data consisting of time, weather, activities, and desired mood which were also adjusted for the listener's age, gender, and favorite artist. The method used is Case-Based Reasoning (CBR), using listeners' listening history data as a knowledge base and the artist relatedness of Indonesian artists to improve solutions at the revision stage. Output of this system is in the form of music playlist presented in a website. The overall precision average for music recommendations is 0.78.
Co-Authors Adiartika, Made Harry Dananjaya Agus Muliantara Aisyah Putri, Sandrina Ferani Anak Agung Istri Dewi Lestari Anak Agung Istri Ngurah Eka Karyawati Anak Agung Istri Ngurah Eka Karyawati Ananta, I Gede Ngurah Wahyu Brahmantha, Gede Putra Aditya Cokorda Pramartha Cokorda Rai Adi Pramartha Devan Bramantya Dharmawangsa, I Gusti Ngurah Agung Eka Putra, I Gede Ariawan Gerson Feoh Giri, Gst. Ayu Vida Mastrika Giri, I Nyoman Yusha Tresnatama Gst. Ayu Vida Mastrika Giri I Dewa Agung Cahya Putra I Gede Ariawan Eka Putra I Gede Santi Astawa I Gede Wilantara Jaya I Gusti Agung Gede Arya Kadyanan I Gusti Bagus Ngurah Agung Brian Wijaya I Gusti Ngurah Anom Cahyadi Putra I Ketut Agus Pranata Muliawan I Ketut Gede Suhartana I Ketut Gede Suhartana I Komang Ari Mogi I Komang Arya Ganda Wiguna I Made Arya Dwisada I Made Satria Bimantara I Made Satria Bimantara I Made Wahyu Purnama Putra I Made Widiartha I Nyoman Adiputra I Putu Gede Adiatmika I Putu Gede Hendra Suputra I Putu Gede Maysa Putra I WAYAN SANTIYASA I Wayan Wikananda Adikara Ida Ayu Gede Suwiprabayanti Ida Bagus Gede Dwidasmara Ida Bagus Gede Sarasvananda Ida Bagus Made Mahendra IWK Teja Sukmana Jeremi Herodian Abednigo Jhordi, Rafif Karlina Surya Witanto Kiki Dwi Prebiana Komang Dhiyo Yonatha Wijaya Krisphino Saputra Nurbidin Liana, Laurensia Luh Arida Ayu Rahning Putri Luh Gede Astuti Luh Gede Astuti Mahardika, I Gede Teguh Maheswara, Pande Putu Devo Punda Marissa Audina Mrs Megawati Muhammad Firdaus Zulkarnain Muliawan, I Ketut Agus Pranata Ni Komang Santi Cahyani Ni Made Putri Wahyuni Ni Putu Dian Kartika Sari Ni Wayan Anti Andari Nyoman Putra Prasetya Wardhana Partamayasa, I Wayan Gede Prashanti, Ni Putu Vidya Vira Prebiana, Kiki Dwi Putra, I Made Wahyu Purnama Putra, I Putu Krisnawan Putra, IGN Anom Cahyadi Putu Wida Gunawan Radhitya, Made Leo Raharja, Made Agung Saifulloh Rahman Sandrina Ferani Aisyah Putri Sang Putu Febri Wira Pratama Santiani, Ida Ayu Made Putri Saputra, I Made Widi Arsa Ari Saputra, I Made Widi Arsa Ari Saputra Simarmata, Ivan Luis subanar subanar Sudarmawan, I Komang Roni Surya Gemilang, I Wayan Adhi Susy Purnawati Tpoy, Getzbie Alfredo Utama, I Putu Yasa Utari, Ni Nyoman Grisyana Valentin Gea Affila Pradika Wahyu Ananta, I Gede Ngurah Wardhana, Nyoman Putra Prasetya Wati, Zulfazazalia Putri Candra Wiantari, Ni Wayan Zulfazazalia Putri Candra Wati