Anditya Arifianto

Anditya Arifianto

Lecturer, Deep Learning Researcher, Ph.D. candidate at Nagoya University

Publications

End-to-End Speech Recognition Models for a Low-Resourced Indonesian Language,

Published in 2020 8th International Conference on Information and Communication Technology (ICoICT), 2021

Recent automatic speech recognition (ASR) is commonly developed using deep learning (DL), instead of the Hidden Markov Model (HMM). Many researchers show that DL is much better than HMM in noisy environments. However, DL needs a huge speech corpus but does not require any dictionary as well as the c …

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EDGAN Disguising Text as Image using Generative Adversarial Network,

Published in 2020 8th International Conference on Information and Communication Technology (ICoICT), 2021

In the concept of data hiding, image is often used as a cover to hide sensitive data inside it. This approach is considered a good addition in securing information to cryptography which only hides the information and not the presence of the message itself. The combination of Deep Learning with Stega …

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Adaptive Attention Generation for Indonesian Image Captioning,

Published in 2020 8th International Conference on Information and Communication Technology (ICoICT), 2021

Image captioning is one of the most widely discussed topic nowadays. However, most research in this area generate English caption while there are thousands of language exist around the world. With their language uniqueness, there's a need of specific research to generate captions in those languages. …

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Pembangunan Aplikasi Mobile Pengenalan Objek Untuk Pendidikan Anak Usia Dini

Published in Jurnal Teknologi Informasi dan Ilmu Komputer (JTIK), Vol. 8, 2021

Mobile phone usage has been very close to early childhood life, so giving rise to some negative impact on early childhood, especially reduced interaction with the surrounding world. One of the technologies that can be developed on the cellphone is computer vision. One of the uses of computer vision …

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Lip Motion Recognition for Indonesian Vowel Phonemes Using 3D Convolutional Neural Networks,

Published in 2020 3rd International Conference on Computer and Informatics Engineering (IC2IE), 2020

Lip motion recognition is a technique for interpreting visual data that focuses on the mouth area and aims to recognize lip movement. The development of lip motion recognition is expected to be used to develop communication tools with deaf people and to automate the speech-to-text process visually. …

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Pneumonia Classification from X-ray Images Using Residual Neural Network

Published in Indonesia Journal on Computing (Indo-JC), Vol. 5, No. 2, 2020

Pneumonia is a virus, bacterium, and fungi infection disease which causes alveoli swelling and gets worse easily if it is not taken care of immediately. There are symptoms that can be recognized through x-ray images, for example the appearance of white mist in the lungs. A pneumonia classification s …

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Recognizing Soft Biometric on Pedestrian Using Convolutional Neural Network,

Published in 2020 International Conference on Data Science and Its Applications (ICoDSA), 2020

Video surveillance is very important in automatic surveillance. It is usually used to monitor any criminal activity and help to find the perpetrator. In the search for individual among pedestrians when the face image can no longer be recognized, then what can be recognized is the soft-biometric or a …

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Hyperparameter Setting of LSTM-based Language Model using Grey Wolf Optimizer,

Published in 2020 International Conference on Data Science and Its Applications (ICoDSA), 2020

Hyperparameters is one of the most essential part of deep learning, because they can give big impact to the performance of the model. Recent works show that if the hyperparameters of a Long Short-Term Memory (LSTM) are carefully adjusted or optimized, its performance can achieve the same performance …

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Firefly Algorithm-based Hyperparameters Setting of DRNN for Weather Prediction,

Published in 2020 International Conference on Data Science and Its Applications (ICoDSA), 2020

A Deep Recurrent Neural Networks (DRNN) is powerful to be used in sequential datasets. Quite hard tasks in DRNN is setting the optimum hyperparameters. There are known to be three types of general methods for searching the optimum DRNN hyperparameters: manual, grid, and random searches. However, the …

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Developing an LSTM-based Classification Model of IndiHome Customer Feedbacks

Published in 2020 International Conference on Data Science and Its Applications (ICoDSA), 2020

The development of companies in the service sector is inseparable from problems with the customer service process. The latest trends show that customers are more comfortable using social media and chat services as feedback delivery media compared to sending emails.In this study, we classify user fee …

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Melanoma Cancer Classification Using ResNet with Data Augmentation,

Published in 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), 2019

Melanoma skin cancer is cancer that difficult to detect. In this study, have been done melanoma cancer classification using Convolutional Neural Network (CNN). CNN is a class of Deep Neural Network (Deep Learning) and commonly used to analyzing images data. A lot of data used on CNN can greatly affe …

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Hierarchical SVM-kNN to Classify Music Emotion,

Published in 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), 2019

The emotional component in a music classification is more powerful than the others. This research addresses a music emotion classification. A hierarchical classification system using a Support Vector Machine (SVM) and a k-Nearest Neighbors (kNN) is proposed. The experiments using 120 pop-rock music …

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Quality Image Enhancement from Low Resolution Camera using Convolutional Neural Network,

Published in 2019 7th International Conference on Information and Communication Technology (ICoICT), 2019

Images captured with various cameras have different qualities especially low-resolution images which generally have deficiencies in terms of quality. The uses of Convolutional Neural Network (CNN) in Super Resolution has been widely applied and has impressive performance results. It encourages the u …

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Generating Image Description on Indonesian Language using Convolutional Neural Network and Gated Recurrent Unit,

Published in 2019 7th International Conference on Information and Communication Technology (ICoICT), 2019

Recently, research on image captioning is to generate the proper description for an image given in English. No previous research has been found on image captioning to generating description in Bahasa Indonesia. In fact, quoted from Wikipedia, Bahasa Indonesia is spoken by 198.7 million people worldw …

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Face Spoofing Detection using Color Distortion Features and Principal Component Analysis,

Published in 2019 7th International Conference on Information and Communication Technology (ICoICT), 2019

Face anti-spoofing is an important topic of face recognition system to protect against security breach. Previous approach for face spoofing detection based on distortion in images have achieved promising results. However, their generalization ability has not been sufficiently addressed. In this work …

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Face Expression Recognition Using Local Gabor Binary Pattern Three Orthogonal Planes (LGBP-TOP) and Support Vector Machine (SVM) Method

Published in Journal of Physics: Conference Series, Vol 1192, 2019

The video expression recognition system has been created before using the Local Gabor Binary Pattern Three Orthogonal Planes (LGBP-TOP) extraction method and the Support Vector Machine (SVM) classifi-cation method. However, the recognizable facial expressions use the entire area of the face image, w …

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Pengenalan Huruf Isyarat Tangan Menggunakan Ekstraksi Ciri Local Binary Pattern,

Published in Indonesia Journal on Computing (Indo-JC), Vol. 3, No. 1,, 2018

Pada penelitian ini dibangun sistem pengenalan huruf isyarat tangan menggunakan metode ekstraksi ciri Local Binary Patterns (LBP). Metode LBP memiliki kehandalan dalam melakukan analisis tekstur, mengatasi penskalaan dan citra yang kabur. Untuk algoritma klasifikasi, digunakan metode k-Nearest Neigh …

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Pengenalan Angka Tulisan Tangan Menggunakan Diagonal Feature Extraction dan Artificial Neural Network Multilayer Perceptron,

Published in Indonesia Journal on Computing (Indo-JC), Vol. 3, No. 1,, 2018

Pada penelitian ini dibangun sistem pengenalan angka tulisan tangan menggunakan metode ekstraksi ciri diagonal dan Artificial Neural Network Multilayer Perceptron. Pada ekstraksi ciri diagonal, citra dibagi menjadi beberapa area yang sama besar. Pada tiap area dihitung rata-rata nilai piksel p …

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Indonesian License Plate Recognition Using Convolutional Neural Network,

Published in 2018 6th International Conference on Information and Communication Technology (ICoICT), 2018

License plate is a part of vehicle's identity. In modern countries, license plate recognition has been developed to collect traffic activity information. The performance of license plate recognition system tend to drop when the input picture contains noises like illumination, dirt, and scratches whi …

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Endorsement Recommendation using Instagram Follower,

Published in 2018 6th International Conference on Information and Communication Technology (ICoICT), 2018

In the fierce competition of product sale, in recent years product owners have used the services of Artists and Celebrities to co-promote the products they sell called endorsements. One way the celebrities promotes the products they endorse is through various online social media like Facebook, Twitt …

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Web crawler utilization for resource search on Indonesian anti-plagiarism detection,

Published in 2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM), 2013

Matching one document with other documents is one of anti-plagiarism tasks. Matching can be performed both intra and extra-corpal. This paper will discuss extra-corpal matching utilize the web crawlers as reference search. The role of web-crawler described in extra-corpal anti-plagiarism architectur …

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Malaria Incidence Forecasting from Incidence Record and Weather Pattern using GMDH Polynomial Neural Network,

Published in International Conference on Future Computer and Communication (ICFCC 2013), 2013

Malaria affects over 100 million persons worldwide with approximately 2,414 deaths a day in average each year. Indonesia is on the third highest position in the number of malaria incident in South East Asia, with 229,819 confirmed cases and 432 deaths only at 2010. Previous work has demonstrated the …

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