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All Journal International Journal of Electrical and Computer Engineering Jurnal Media Infotama International Journal of Advances in Intelligent Informatics JOIV : International Journal on Informatics Visualization Communications in Science and Technology Conference SENATIK STT Adisutjipto Yogyakarta Jurnal Informatika IJITEE (International Journal of Information Technology and Electrical Engineering) Indonesian Journal of Electrical Engineering and Computer Science Journal of Computer System and Informatics (JoSYC) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal INFOTEL JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)
Hanung Adi Nugroho
Department Of Electrical And Information Engineering, Universitas Gadjah Mada
Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Pengaruh Load Balancing Pada Pemrosesan Paralel untuk Kompresi Video Sudaryanto .; Teguh Bharata Adji; Hanung Adi Nugroho
SENATIK STT Adisutjipto Vol 2 (2016): Peran Teknologi dan Kedirgantaraan Untuk Meningkatkan Daya Saing Bangsa
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/senatik.v2i0.85

Abstract

Communication and multimedia, especially video data processing require very high resource both computing resources and communication traffic. This requires high-end machines such as servers with high specifications are of course very expensive. This results builds a web based application that implements the concept of parallel processing with load balancing process based CPU Usage to compress video files with FFmpeg software.The results are conditioned compression has half the resolution of the original video data. Based on the test results indicate with load balancing process parallel concepts used, the compression process showed an average speed up value of 8.07% faster than paralle Non load balancing process with 2 compressors, 37.57% with 3 compressors, and 41.24% with 4 compressors. The level of processor efficiency by 28.76% more efficient than paralle Non load balancing process with 2 compressors, 37.57% with 3 compressor, and 41.24%  with 4 compressors. Keywords: pemrosesan paralel, kompresi video, Load Balancing, CPU Usage
Analisis Pengaruh Kompresi Citra Fundus terhadap Kinerja Sistem Automated Microanerysm Detections Anugerah Galang Persada; Ahmad Nasikun; Igi Ardiyanto; Hanung Adi Nugroho
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 1: Februari 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1011.955 KB)

Abstract

Diabetes is one of the most serious diseases that commonly suffered by people around the world, including Indonesia. Early symptoms of diabetes could be observed from various indicators, one of which is through the retina. Retina conditions is affected by diabetics and when remain unproperly threated could lead to blindness. This retinal disorders due to diabetes is normally called Diabetic Retinopathy (DR). One method that able to distinguish and detect DR is microaneurysm detection. This method requires good quality of retinal images. However, in certain areas such as rural areas, this requirement may difficult to meet due to lack of adequate infrastructure. One solution that may overcome this problem is to compress the images. In this paper, image compression algorithms were applied to the retinal image, and then used to detect microaneuryms through Deep Learning-based systems. The result shows that the most stable and appropriate algorithm is PNG, which is able to correctly classify around 83% in accuracy with 5,5% variance.
Analisis Penerapan Sistem Informasi Manajemen Rumah Sakit Menggunakan Metode UTAUT dan TTF Novianti Puspitasari; Adhistya Erna Permanasari; Hanung Adi Nugroho
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 2 No 4: November 2013
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (338.009 KB)

Abstract

Ministry of Health RI has issued a policy to guide the implementation of health development undertaken by the government and private sector in order to improve the quality of health services at the hospital. This quality improvement is formed by the implementation of Hospital Management Information System (HMIS) in every hospital. The implementation of HMIS is still having problems and obstacles in the level of user acceptance. There are still many operational and managerial things that, makes the implementation of HMIS not properly running.This research study analyses the results of the implementation of HMIS from the user acceptance levels, using the integration model of the Task Technology Fit (TTF) and the Unified Theory of Acceptance and Usage of Technology (UTAUT).
Penerapan Metode Certainty Factor Dalam Diagnosis Gangguan Depresi Septian Rico Hernawan; Hanung Adi Nugroho; Indriana Hidayah
Journal of Computer System and Informatics (JoSYC) Vol 3 No 2 (2022): Februari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v3i2.643

Abstract

Globalization can cause several problems and pressures of mind for both individuals and groups. Various kinds of problems can certainly lead to psychological disorders, one of which is depression. Indonesia itself is one of the countries with a high number of people with depressive disorders. Depressive disorder itself can have many consequences ranging from lack of enthusiasm to even death. Facing these serious problems, the government should be able to address the mental disorder that is currently happening. However, the reality is still far from this. Inadequate infrastructure, equality problems for each region, and shortages of experts are the main problems at this time. The expert system is considered to be a solution in solving these problems. Web-based expert systems can replace the role of experts in the process of initial diagnosis of depressive disorders, patients can also access them easily. The calculation method implemented is the Certainty Factor method. This method is considered suitable in the diagnosis of depression. The implementation of the CF method in the diagnosis of depression can provide a confidence level of up to 94.9%. The expert system is expected to be able to eliminate human errors, speed up the diagnostic process, make it easier for health workers, and provide standards for related parties in handling mental disorders
Peranan Kontur dan Slope dalam Pengenalan Keaslian Tanda Tangan Menggunakan Dynamic Time Warping dan Polar Fourier Transform Ignatia Dhian Estu Karisma Ratri; Hanung Adi Nugroho; Teguh Bharata Adji
Jurnal Informatika Vol 12, No 2 (2016): Jurnal Teknologi Komputer dan Informatika
Publisher : Universitas Kristen Duta Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (476.563 KB) | DOI: 10.21460/inf.2016.122.495

Abstract

The writer has seen that so far signatures are just validated manually, so there is possibility to create a system for hand signature recognition.  The objective of this research is to improve the method for hand signature recognition using combination method with different characteristic. Contour and slope used for special feature in this research. Contour and slope from image will be applied using Dynamic Time Warping (DTW). Another extraction feature that been used was Polar Fourier Transform (PFT).   The method employed for classification are Support Vector Machine (SVM).From the research results, the writer obtains the fact that the combination between the DTW and PFT using SVM classification, provide the better results in verification of an authentic hand signature with the accuracy of 93.23%.  it is expected that from this research, the results can be utilized in the process of verification of an authentic hand signature in near future dailylife.
Improving Phoneme to Viseme Mapping for Indonesian Language Anung Rachman; Risanuri Hidayat; Hanung Adi Nugroho
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 4, No 1 (2020): March 2020
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.47577

Abstract

The lip synchronization technology of animation can run automatically through the phoneme-to-viseme map. Since the complexity of facial muscles causes the shape of the mouth to vary greatly, phoneme-to-viseme mapping always has challenging problems. One of them is the allophone vowel problem. The resemblance makes many researchers clustering them into one class. This paper discusses the certainty of allophone vowels as a variable of the phoneme-to-viseme map. Vowel allophones pre-processing as a proposed method is carried out through formant frequency feature extraction methods and then compared by t-test to find out the significance of the difference. The results of pre-processing are then used to reference the initial data when building phoneme-to-viseme maps. This research was conducted on maps and allophones of the Indonesian language. Maps that have been built are then compared with other maps using the HMM method in the value of word correctness and accuracy. The results show that viseme mapping preceded by allophonic pre-processing makes map performance more accurate when compared to other maps.
A Review of Feature Selection and Classification Approaches for Heart Disease Prediction Fathania Firwan Firdaus; Hanung Adi Nugroho; Indah Soesanti
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 4, No 3 (2020): September 2020 (in progress)
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.59193

Abstract

Cardiovascular disease has been the number one illness to cause death in the world for years. As information technology develops, many researchers have conducted studies on a computer-assisted diagnosis for heart disease. Predicting heart disease using a computer-assisted system can reduce time and costs. Feature selection can be used to choose the most relevant variables for heart disease. It includes filter, wrapper, embedded, and hybrid. The filter method excels in computation speed. The wrapper and embedded methods consider feature dependencies and interact with classifiers. The hybrid method takes advantage of several methods. Classification is a data mining technique to predict heart disease. It includes traditional machine learning, ensemble learning, hybrid, and deep learning. Traditional machine learning uses a specific algorithm. The ensemble learning combines the predictions of multiple classifiers to improve the performance of a single classifier. The hybrid approach combines some techniques and takes advantage of each method. Deep learning does not require a predetermined feature engineering. This research provides an overview of feature selection and classification methods for the prediction of heart disease in the last ten years. Thus, it can be used as a reference in choosing a method for heart disease prediction for future research.
ECG Signal Classification Review Muhammad Rausan Fikri; Indah Soesanti; Hanung Adi Nugroho
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 1 (2021): March 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.60295

Abstract

The heart is an important part of the human body, functioning to pump blood through the circulatory system. Heartbeats generate a signal called an ECG signal. ECG signals or electrocardiogram signals are basic raw signals to identify and classify heart function based on heart rate. Its main task is to analyze each signal in the heart, whether normal or abnormal. This paper discusses some of the classification methods which most frequently used to classify ECG signals. These methods include pre-processing, feature extraction, and classification methods such as MLP, K-NN, SVM, CNN, and RNN. There were two stages of ECG classification, the feature extraction stage and the classification stage. Before ECG features were extracted, raw ECG signal data first processed in the pre-processing stage because ECG signals were not necessarily free of noise. Noise will cause a decrease in accuracy during the classification process. After features were extracted, ECG signals were then classified with the classification method. Neural Network methods such as CNN and RNN are best to use since they can give better accuracy. For further research, the machine learning method needs to be improved to get high accuracy and high precision in the ECG signals classification.
A Review on Face Anti-Spoofing Rizky Naufal Perdana; Igi Ardiyanto; Hanung Adi Nugroho
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 1 (2021): March 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.61827

Abstract

The biometric system is a security technology that uses information based on a living person's characteristics to verify or recognize the identity, such as facial recognition. Face recognition has numerous applications in the real world, such as access control and surveillance. But face recognition has a security issue of spoofing. A face anti-spoofing, a task to prevent fake authorization by breaching the face recognition systems using a photo, video, mask, or a different substitute for an authorized person's face, is used to overcome this challenge. There is also increasing research of new datasets by providing new types of attack or diversity to reach a better generalization. This paper review of the recent development includes a general understanding of face spoofing, anti-spoofing methods, and the latest development to solve the problem against various spoof types.
Image Analysis for MRI-Based Brain Tumor Classification Using Deep Learning Krisna Nuresa Qodri; Indah Soesanti; Hanung Adi Nugroho
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 1 (2021): March 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.62663

Abstract

Tumors are cells that grow abnormally and uncontrollably, whereas brain tumors are abnormally growing cells growing in or near the brain. It is estimated that 23,890 adults (13,590 males and 10,300 females) in the United States and 3,540 children under the age of 15 would be diagnosed with a brain tumor. Meanwhile, there are over 250 cases in Indonesia of patients afflicted with brain tumors, both adults and infants. The doctor or medical personnel usually conducted a radiological test that commonly performed using magnetic resonance image (MRI) to identify the brain tumor. From several studies, each researcher claims that the results of their proposed method can detect brain tumors with high accuracy; however, there are still flaws in their methods. This paper will discuss the classification of MRI-based brain tumors using deep learning and transfer learning. Transfer learning allows for various domains, functions, and distributions used in training and research. This research used a public dataset. The dataset comprises 253 images, divided into 98 tumor-free brain images and 155 tumor images. Residual Network (ResNet), Neural Architecture Search Network (NASNet), Xception, DenseNet, and Visual Geometry Group (VGG) are the techniques that will use in this paper. The results got to show that the ResNet50 model gets 96% for the accuracy, and VGG16 gets 96% for the accuracy. The results obtained indicate that transfer learning can handle medical images.
Co-Authors - Nurfadilah, - A.A. Ketut Agung Cahyawan W Achmad Rizal Ade Sofa Adhistya Erna Permanasari Agus Eko Minarno Ahmad Nasikun Al-Fahsi, Resha Dwika Hefni Albert Ch. Soewongsono, Albert Ch. Alfarisi, Ikhsan Anondho Wijanarko Aqil Aqthobirrobbany Aqthobirrobbany, Aqil Aras, Rezty Amalia Arham, Aulia Arif Masthori Atmaja Perdana, Chandra Ramadhan Azof Ghazali Sujono Bhisma Murti Cahyani Windarto Chitra Octavina Cindy Claudia Febiola, Cindy Claudia Citra Prasetyawati Cokro Mandiri, Mochammad Hazmi Danny Kurnianto Dewanta, Wika Dewi Kartika Sari Dian Nova Kusuma Hardani Dianursanti Dimas, Dimas Dindin Hidayat Dwi Haryono E. Elsa Herdiana Murhandarwati Elisabeth Deta Lustiyati Erwin Setyo Nugroho Eva Yuliana Fitri Faisal Najamuddin Fathania Firwan Firdaus Faza Maula Azif Fitri Bimantoro Ganesha L Putra Guyub Nuryanto Handani, Deni Hasdani, Hasdani Hasnely, Hasnely Hastuti, Uki Retno Budi Heri Hermansyah Heru Supriyono Hesti Khuzaimah Nurul Yusufiyah Hotama, Christianus Frederick Hutami, Augustine Herini Tita I Md. Dendi Maysanjaya Ibnu Taufan, Ibnu Ibrahim, Zaidah Ichsan Setiawan Igi Ardiyanto Ignatia Dhian Estu Karisma Ratri Imelda Imelda Indah Soesanti Indriana Hidayah Ismail Setiawan Jafaruddin Jafaruddin, Jafaruddin Kartika Firdausy Kirana, Thea Koko Ondara Krisna Nuresa Qodri KZ Widhia Oktoeberza Lina Choridah Listyalina, Latifah M. Khairun Iffat Made Satria Wibawa Maemonah, Maemonah Mahdi Abdullah Syihab Marshell Tendean Momoji Kubo Muhammad Bayu Sasongko Muhammad Rausan Fikri Naomi Shibasaki-Kitakawa Nasikun, Ahmad Ndii, Meksianis Z Nenden Siti Aminah Noor Abdul Haris Noor Akhmad Setiawan Nora Anisa Br. Sinulingga Novianti Puspitasari Nugroho, Anan Nur Fadhilah Nurcahyani Wulandari Nurfauzi, Rizki Oktoeberza, Widhia KZ Oyas Wahyunggoro Perdana, Adli Waliul Persada, Anugerah Galang Pranowo, Vicko Prasojo, Sasmito Praswasti P. D.K Wulan Puspitasari, Novianti Putri Bungsu Rachman, Anung Ratna Lestari Budiani Buana Rima Fitria Adiati Rina Sri Widayati Riri Ferdiana Risanuri Hidayat Rita Arbianti Rizky Naufal Perdana Robert Silas Kabanga Rochim, Febry Putra Roekmijati W. Soemantojo Saftirta Gatra Dewantara Sandy Anwar Mursito Sarjana Sarjana Sasongko Yoni Bagas Septian Rico Hernawan Setiyo Kantomo, Ilham Sudaryanto . Sukiyo Sukiyo Sumadi, Fauzi Dwi Setiawan Sunu Wibirama Suzanna Ndraha Syahrul Purnawan Syahwami, Syahwami Tania Surya Utami TATI NURHAYATI Teguh Bharata Adji Toshiy Yonemoto Tri Lestari Ulung Jantama Widhia K.Z Oktoeberza Widhia K.Z Oktoeberza Widya Sari Wika Dewanta Willy Anugrah Cahyadi Windarta, Budi Woraratpanya, Kuntpong Yenny Rahmawati Yuda Munarko Yufis Azhar Yulaikha Istiqomah Yulyanti, Vesi Zaidah Ibrahim Zubri, Aldino