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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Perfecting a Video Game with Game Metrics Media Teknika Jurnal Ilmiah Matrik Abdimas Altruis: Jurnal Pengabdian Kepada Masyarakat Jurnal Nasional Teknik Elektro dan Teknologi Informasi Prosiding Seminar Nasional Rekayasa Teknologi Industri dan Informasi ReTII
Wiwien Widyastuti
Universitas Sanata Dharma
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Social Sciences Transportation Other

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Kinerja Deep Convolutional Network untuk Pengenalan Aksara Pallawa Wiwien Widyastuti
Media Teknika Vol 12, No 2 (2017)
Publisher : Sanata Dharma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/mt.v12i2.1085

Abstract

This research trained Deep Convolutional Networks(ConvNets) to classify hand-written Pallava alphabet. The Deep ConvNets architecture consists of two convolutional layers, each followed by maxpooling layer, two Fully-Connected layers. It had 442.602 parameters. This model classified 660 imagesof hand-written Pallava alphabet into 33 diferent classes. To make training faster, this research used GPU implementation with 384 CUDA cores. Two different techniques were implemented, Stochastic Gradient Descent (SGD) and Adaptive Gradient, each trained with 10, 20, 30 and 40 epoch. The best accuracy was 67,5%, achieved by the model with SGD technique trained at 30 epoch.Keywords: Deep ConvNets, Pallava, GPU, SGD
Water Pump Mechanical Faults Display at Various Frequency Resolutions Linggo Sumarno; Tjendro Tjendro; Wiwien Widyastuti; R.B. Dwiseno Wihadi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 1: March 2014
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v12i1.29

Abstract

When an electrical machine suffered a mechanical fault, it generally emits certain sounds. These sounds came from the vibration. Therefore, based on the vibration, it could be detected if there was a mechanical fault in an electrical machine. This paper discussed the graphical display of the vibration of electrical machines in the form of household water pumps which were in good condition, faulty bearing, faulty impeller, or faulty foot valve. Vibration could be displayed in the time domain, or in the frequency domain, by using the three axes, i.e. X, Y, and Z. In the frequency domain, the vibration could be displayed at various frequency resolutions. Based on the observations, the higher frequency resolution, the lower detail in the graphical display of frequency domain would be shown. Although there was lower detail in the graphical display of frequency domain, at frequency resolution of 11.7 Hz in the X axis, showed that it could be visually distinguished among water pumps which were in good condition, faulty bearing, faulty impeller, or faulty foot valve.
PENGUKURAN SPEKTRUM PADA SISTEM PEMETAAN DAN PENGAWASAN FREKUENSI RADIO FM BERBASIS SISTEM INFORMASI GEOGRAFIS DI WILAYAH D.I.YOGYAKARTA Sukma Meganova Effendi; A. Bayu Primawan; Wiwien Widyastuti
Seminar Nasional Aplikasi Teknologi Informasi (SNATI) 2011
Publisher : Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia

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Abstract

Banyaknya jumlah stasiun radio FM dan keterbatasan alokasi frekuensi radio FM mengharuskan penggunaan alokasi frekuensi radio tersebut diatur sesuai dengan yang berlaku dari International Telecommunication Union (ITU). Dengan adanya aturan tersebut, spektrum frekuensi radio juga memerlukan pengawasan secara periodik sekaligus untuk penertiban penggunaannya. Penertiban dilakukan secara periodik supaya penggunaan spektrum frekuensi tetap sesuai dengan aturan yang berlaku. Oleh sebab itu, sistem pemetaan dan pengawasan spektrum frekuensi radio FM berbasis Sistem Informasi Geografis (SIG) untukpengukuran spektrum frekuensi radio FM dibuat.Sistem pengukuran spektrum frekuensi radio FM ini terdiri dari dua proses utama yaitu komunikasi spectrum analyzer (SPA) dengan laptop dan pengolahan data dari SPA yang ditampilkan dengan program visual. Komunikasi SPA dengan laptop digunakan untuk memperoleh file *.txt dan file *.bmp atau *.jpg. Pengolahan data digunakan untuk mengonversi file *.txt menjadi file *.xls.Program pengukuran spektrum frekuensi radio FM berhasil direalisasikan. Komunikasi antara SPA GwInstek dengan laptop berhasil dilakukan yang menghasilkan file *.txt dan *.bmp atau *.jpg. Program SPA GwInstek berhasil mengolah file *.txt menjadi file *.xls. Tampilan akhir gambar dari program SPA GwInstek adalah file *.bmp atau *.jpg hasil pengukuran SPA GwInstek.
ALAT DISPENSER HAND SANITIZER OTOMATIS UNTUK MASYARAKAT Linggo Sumarno; Wiwien Widyastuti; A. Bayu Primawan; Martanto Martanto; Iswanjono Iswanjono; Damar Widjaja; Th. Prima Ari Setiyani; B. Djoko Untoro Suwarno; Tjendro Tjendro; Petrus Setyo Prabowo
ABDIMAS ALTRUIS: Jurnal Pengabdian Kepada Masyarakat Vol 4, No 1 (2021): April 2021
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (610.533 KB) | DOI: 10.24071/aa.v4i1.3336

Abstract

The habit of cleaning hands is one of the new habits during the current COVID-19 pandemic. One way to clean hands is with a hand sanitizer. The automatic hand sanitizer dispenser can be used to clean hands, without touching a button or any part of the appliance. Community service in this paper is carried out by making a number of automatic hand sanitizer dispensers, and distributing them in a number of places, around Campus III of Sanata Dharma University, Paingan, Maguwoharjo, Yogyakarta. A number of complaints emerged from the person in charge of the distribution site for the appliance. The most common complaint is that the appliance does not function as it should. This complaint is caused by a problem with the proximity sensor used. This sensor is too affected by light intensity. To overcome this, it is necessary to explore other types of sensors that are better than proximity sensors, which are less affected by light intensity.
PELATIHAN MEDIA BELAJAR BERBASIS ONLINE DI ERA PANDEMI Kartono Pinaryanto; Anastasia Rita Widiarti; Haris Sriwindono; Ridowati Gunawan; Hari Suparwito; Sri Hartati Wijono; Rosalia Arum Kumalasanti; Wiwien Widyastuti
ABDIMAS ALTRUIS: Jurnal Pengabdian Kepada Masyarakat Vol 5, No 1 (2022): April 2022
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/aa.v5i1.3916

Abstract

The education sector is one of the areas that has been most affected by the COVID-19 pandemic. Schools, which normally hold offline meetings, must now take place online. With this pandemic, the teaching process must be "forced" to be done online. The task model which is usually given in physical mode (questions on paper, done and collected) is no longer relevant to be done because of the limitations of physical meetings. On the other hand, students need an explanation from the teacher directly because they are used to the context of offline learning. Judging from the current level of smartphone ownership, whether owned by students themselves or their parents, we can use smartphone devices to help the teaching and learning process. But of course it requires technological literacy from the student side and the teacher side so that this teaching and learning process can be carried out properly. As a form of concern for the academic community of the Informatics Study Program at Sanata Dharma University to the problems that exist in the environment around the campus, we held training activities for making teaching media for State Elementary School of Timbulharjo teachers who ultimately played an important role in improving teachers' technological literacy in carrying out online learning. This activity had been carried out well offline in 2 stages, namely stage 1 on 9 and 10 June 2021 and stage 2 on 22 and 23 November 2021.
Pengenalan Kerusakan Mekanis Pompa Air Berbasis Sinyal Getaran pada Ranah Frekuensi Linggo Sumarno; R.B. Dwiseno Wihadi; Tjendro; Wiwien Widyastuti
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 4 No 2: Mei 2015
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (984.762 KB)

Abstract

One way in recognizing mechanical faults of electrical machines is using the vibration signals. This paper studies the recognition of mechanical faults of electrical machines which have faulty bearing, faulty impeller, and faulty foot valve. Electrical machines studied in this paper are household water pumps. The recognition of mechanical faults is conducted using the vibration signals at the frequency domain at various frequency resolution. The recognition method used is template matching for pattern classes. Euclidean distance function is used in this template matching. Based on the results, the highest recognition rate of 100% is optimally obtained using the vibration signal at frequency resolution of 5,9 Hz, and the number of 5 samples/classes in the water pump database. The 5,9 Hz frequency resolution was obtained using a 256 point FFT, where the number of 128 FFT coefficients are used as the feature extraction.
PELATIHAN GEOGEBRA UNTUK GURU-GURU SMA DI KALIMANTAN BARAT Bernadeta Wuri Harini; Djoko Untoro Suwarno; Martanto Martanto; Wiwien Widyastuti; Theresia Prima Ari Setiyani; Lusia Krismiyati Budiasih
ABDIMAS ALTRUIS: Jurnal Pengabdian Kepada Masyarakat Vol 5, No 2 (2022): Oktober 2022
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/aa.v5i2.4589

Abstract

Mathematics and Physics are subjects that are not only difficult for students but also difficult for teachers. To make it easier to understand the material, Geogebra software is used. In this community service, Geogebra training was provided for high school teachers who are Mathematics and Physics teachers in West Kalimantan. The training was conducted online involving 10 lecturers and 5 assistants. The training consisted of 4 sessions carried out over 2 days which was attended by 31 teachers of Mathematics and Physics. The training is divided into 2 classes to be more effective. From the training results, there was an increase in the ability to use Geogebra by 38.05%. The average level of participant satisfaction with the implementation of the study is 4.15 on (a scale of 5)
Pengenalan Aksara Pallawa dengan Model Hidden Markov Wiwien Widyastuti
Retii Prosiding Seminar Nasional ReTII ke-11 2016
Publisher : Institut Teknologi Nasional Yogyakarta

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Abstract

Aksara Pallawa atau kadangkala ditulis sebagai Pallava adalah sebuah aksara yang berasal dari India bagian selatan. Aksara ini sangat penting untuk sejarah di Indonesia karena aksara ini merupakan aksara dari mana aksara-aksara Nusantara diturunkan [Wikipedia]. Hidden Markov Model (HMM) adalah suatu metode stochastic yang sudah banyak digunakan pada sistem pengenalan suara dan sistem pengenalan pola dan menghasilkan tingkat pengenalan yang cukup tinggi [Intechweb, 2011]. Penelitian ini menerapkan dan mengamati  unjuk kerja Model Hidden Markov untuk mengenali aksara Pallawa. Kegiatan penelitian meliputi pengambilan data baik untuk pelatihan maupun untuk pengujian, preprocessing, ekstraksi ciri, tahap pelatihan untuk mencari model Hidden Markovnya  terakhir adalah tahap pengujian  serta pembahasan hasil  penelitian. Berdasarkan hasil pengamatan  dengan variasi jumlah state sebesar 8, 10, 12, 14, 16, 18, dan 20 diperoleh hasil pengenalan terbaik pada jumlah state 14 yaitu sebesar 35,1515% dengan waktu eksekusi selama 82 detik. Kata Kunci: Aksara Pallawa, Hidden Markov Model.
PREDIKSI SALINITAS AIR LAUT DENGAN DEEP NEURAL NETWORK Wiwien Widyastuti; J. B. Budi Darmawan
Jurnal Ilmiah Matrik Vol 21 No 2 (2019): Jurnal Ilmiah Matrik
Publisher : Direktorat Riset dan Pengabdian Pada Masyarakat (DRPM) Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/jurnalmatrik.v21i2.570

Abstract

Research in the marine field is important to look at the state of the ocean's atmosphere and the biodiversity that can live in it. Based on the CalCOFI data set, seawater salinity correlates with the depth of the sea. Sea water salinity can be predicted based on its depth. The classic method that is often used is the least squares regression. Deep neural network is one of the machine learning methods that has been widely applied to regression problems. This study aims to find better predictive performance by comparing the least squares regression method and the deep neural network method. The research method is done first by making an equation model with the least squares regression method. Second, by training the deep neural network using the same data so that the network model is obtained. Furthermore, the results of both methods are compared by calculating MAE and MSE. The results showed that the network model with superior deep neural network was used to predict data outside the range of trained data compared to the least squares regression method.
Co-Authors Anastasia Rita Widiarti Bernadeta Wuri Harini Damar Widjaja Damar Widjaja Djoko Untoro Suwarno Hari Suparwito Haris Sriwindono Iswanjono Iswanjono Iswanjono Iswanjono J. B. Budi Darmawan Linggo Sumarno Lusia Krismiyati Budiasih Martanto . Martanto Martanto Petrus Setyo Prabowo Pinaryanto, Kartono Primawan, A.Bayu R.B. Dwiseno Wihadi Ridowati Gunawan Rosalia Arum Kumalasanti Setiyani, Th. Prima Ari Sri Hartati Wijono Sukma Meganova Effendi Theresia Prima Ari Setiyani Tjendro Tjendro Tjendro Wihadi, R.B. Dwiseno