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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics CommIT (Communication & Information Technology) ComTech: Computer, Mathematics and Engineering Applications Progresif: Jurnal Ilmiah Komputer
Andry Chowanda
Bina Nusantara University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mathematics

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Multi-modal Asian Conversation Mobile Video Dataset for Recognition Task Dewi Suryani; Valentino Ekaputra; Andry Chowanda
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (679.362 KB) | DOI: 10.11591/ijece.v8i5.pp4042-4046

Abstract

Images, audio, and videos have been used by researchers for a long time to develop several tasks regarding human facial recognition and emotion detection. Most of the available datasets usually focus on either static expression, a short video of changing emotion from neutral to peak emotion, or difference in sounds to detect the current emotion of a person. Moreover, the common datasets were collected and processed in the United States (US) or Europe, and only several datasets were originated from Asia. In this paper, we present our effort to create a unique dataset that can fill in the gap by currently available datasets. At the time of writing, our datasets contain 10 full HD (1920 1080) video clips with annotated JSON file, which is in total 100 minutes of duration and the total size of 13 GB. We believe this dataset will be useful as a training and benchmark data for a variety of research topics regarding human facial and emotion recognition.
Tap For Battle: Perancangan Casual Game Pada Smartphone Android Andry Chowanda; Benard H. Prabowo; Glen Iglesias; Marsella Diansari
ComTech: Computer, Mathematics and Engineering Applications Vol. 5 No. 2 (2014): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v5i2.2187

Abstract

Smartphones have become a necessity. Almost everyone uses a smartphone in a variety of activities. Both young and old are sure to utilize this technology, for a wide range of activities such as doing the work, doing school work or enjoying entertainment. The purpose of this research is to build a casual-action game with war theme. The game is built for Android smartphone that has multi touch screen capability. The research methods used in this research are data collection and analysis method including user analysis with questionnaire. Furthermore, IMSDD method is implemented for game design and development phase including system requirement analysis, system design, system implementation, finally system evaluation. In this research, we conclude that 83.9% participants enjoyed the game with touch-screen as the game control.
Gamification of Learning: Can Games Motivate Me to Learn History? Andry Chowanda; Alan Darmasaputra Chowanda
ComTech: Computer, Mathematics and Engineering Applications Vol. 7 No. 3 (2016): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v7i3.2503

Abstract

This article presented empirical finding of the effect of gamification for learning. Evidence in the findings of the empirical study that explores two education games that were developed earlier with a total of 64 participants was presented. The first game was a computer game with historical themes of Ken Arok and Ken Dedes of Singhasari Kingdom. The second game was an Android-based mobile game with Historicity of the Bible themes of Moses. Prior research showed that more than 50 percent of junior and senior high school students in Jakarta demonstrated their apathy to several subjects in their school. They also disclosed that they were having difficulty in following their class in particular with a difficult subject such as History subject. With the popularity of games, the gamification of learning was investigatd to enhance the interest of the students to master a particular subject. The results show that there is a statistical significance increase of the students score and interest in history subject in a group that was using the games to help them in the subject compared to a group that reading books about the particular subject alone 0.001. Furthermore, the participants also reported that playing games was helping them to remember difficult names and event timeline in the historical events   
Emowars: Interactive Game Input Menggunakan Ekspresi Wajah Andry Chowanda
ComTech: Computer, Mathematics and Engineering Applications Vol. 4 No. 2 (2013): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v4i2.2542

Abstract

Research in the affective game has received attention from the research communities over this lustrum. As a crucial aspect of a game, emotions play an important role in user experience as well as to emphasize the user’s emotions state on game design. This will improve the user’s interactivity while they playing the game. This research aims to discuss and analyze whether emotions can replace traditional user game inputs (keyboard, mouse, and others). The methodology used in this research is divided into two main phases: game design and facial expression recognition. The results of this research indicate that users preferred to use a traditional input such as mouse. Moreover, user’s interactivities with game are still slightly low. However, this is a great opportunity for researchers in affective game with a more interactive game play as well as rich and complex story. Hopefully this will improve the user affective state and emotions in game. The results of this research imply that happy emotion obtains 78% of detection, meanwhile the anger emotion has the lowest detection of 44.4%. Moreover, users prefer mouse and FER (face expression recognition) as the best input for this game.
Analisis dan Perancangan Sistem Basis Data Pembelian, Penjualan, dan Persediaan Pada PT Interjaya Surya Megah Andry Chowanda
ComTech: Computer, Mathematics and Engineering Applications Vol. 1 No. 2 (2010): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v1i2.2570

Abstract

The purpose of this paper is to analyze the system of sales, purchases, and inventory of goods at PT Surya Megah Interjaya and designing the database of sales, purchases, and inventories of goods in accordance with the needs of the company, and to design a prototype application. The methodology used to collect information is by fact-finding technique, which conducted a survey, conducting interviews on related parties, and performed an analysis of procedures and corporate documents. As for database design using the methodology of database-life-cycle, which consists of 3 stages, namely: conceptual, logical, and physical database design. Research conducted, resulting conceptual database design, logical, and physical for business processes of sales, purchases, and inventories of goods. A prototype application is developed to build a working model of a database application that allows the designer or user to ensure the final system will be visible and functioning. With the database design and application development, information needs are met quickly and accurately. 
Perancangan Game Kartu Interaktif Berbasis Android Menggunakan Augmented Reality Andry Chowanda
ComTech: Computer, Mathematics and Engineering Applications Vol. 2 No. 2 (2011): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v2i2.2820

Abstract

By utilizing the augmented reality technology which now develops well, a card game system design and the game prototype are created on through this study Android-based Smartphone. This study is expected to increase the children’s interest to play cards in a modern way, to be utilized as a reference material for business actors in the world, and to be an alternative facility for marketing officers to market their products. The scope of this study is limited only to the system design and the prototype making of the game. The combination of waterfall methodology and a game design by Jesse is used in this study. From the results of the study it is concluded that the augmented reality technology is able to make the game more interesting. 
The Development of Indoor Object Recognition Tool for People with Low Vision and Blindness Rhio Sutoyo; Andry Chowanda
ComTech: Computer, Mathematics and Engineering Applications Vol. 8 No. 2 (2017): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v8i2.3763

Abstract

The purpose of this research was to develop methods and algorithms that could be applied as the underlying base for developing an object recognition tools. The method implemented in this research was initial problem identification, methods and algorithms testing and development, image database modeling, system development, and training and testing. As a result, the system can perform with 93,46% of accuracy for indoor object recognition. Even though the system achieves relatively high accuracy in recognizing objects, it is still limited to a single object detection and not able to recognize the object in real time.
Exploring the Best Parameters of Deep Learning for Breast Cancer Classification System Andry Chowanda
CommIT (Communication and Information Technology) Journal Vol. 16 No. 2 (2022): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v16i2.8174

Abstract

Breast cancer is one of the deadliest cancers in the world. It is essential to detect the signs of cancer as early as possible, to make the survival rate higher. However, detecting the signs of breast cancer using the machine or deep learning algorithms from the diagnostic imaging results is not trivial. Slight changes in the illumination of the scanned area can significantly affect the automatic breast cancer classification process. Hence, the research aims to propose an automatic classifier for breast cancer from digital medical imaging (e.g., Positron Emission Tomography or PET, X-Ray of Mammogram, and Magnetic Resonance Imaging (MRI) images). The research proposes modified deep learning architecture with five different settings to model automatic breast cancer classifiers. In addition, five machine learning algorithms are also explored to model the classifiers. The dataset used in the research is the Curated Breast Imaging Subset of Digital Database for Screening Mammography (CBIS-DDSM). A total of 2,676 mammogram images are used in the research and are split into 80%:20% (2,141:535) for training and testing datasets. The results demonstrate that the model trained with eight layers of Convolutional Neural Networks (CNN) (SET-8) achieves the best accuracy score of 94.89% and 93.75% in the training and validation dataset, respectively.
Identifying clickbait in online news using deep learning Andry Chowanda; Nadia Nadia; Lie Maximilianus Maria Kolbe
Bulletin of Electrical Engineering and Informatics Vol 12, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i3.4444

Abstract

Several industries use clickbait techniques as their strategy to increase the number of readers for their news. Some news companies implement catchy headlines and images in their news article links, with the expectation that the readers will be interested in reading the news and click the provided link. The majority of the news is not hoax news. However, the content might not be as grand as the catchy headlines and images provided to the readers. This research aims to explore the classification model using machine learning to identify if the headlines are classified as clickbait in online news. This research explores several machine learning techniques to classify clickbait in online news and comprehensively explain the results. Several popular machine learning techniques were implemented and explored in this research. The results demonstrate that the model trained with fast large margin provides the best accuracy and classification error (90% and 10%, respectively). Moreover, to improve the performance, bidirectional encoder representations from transformers architecture was used to model clickbait in online news. The best BERT model achieved 98.86% in the test accuracy. BERT model requires more time to train (0.9 hour) compared to machine learning (0.4 hour).
Emotion Intensity Value Prediction with Machine Learning Approach on Twitter Rindy Claudia Setiawan; Andry Chowanda
CommIT (Communication and Information Technology) Journal Vol. 17 No. 2 (2023): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v17i2.8503

Abstract

Recognizing the intensity of the emotions is a paramount task for an affective system. By recognizing the intensity of the emotions, the system can have better human-computer interaction. The research explores several machine learning approaches with several different feature extraction method combinations to solve the emotion intensity prediction task while also analyzing and comparing it with several previous related papers. The research uses the dataset provided through theWASSA 2017 and SemEval 2018 competition. The dataset utilizes four of the eight basic emotions that Plutchik defines (anger, fear, joy, and sadness). The total data result in 19,736 rows of entry, with a total of 10,715 (54.3%) for training, 1,811 (9.17%) for validation, and 7,210 (36.53%) for testing. Three feature extraction methods are used and compared: N-gram, TFIDF, and Bag-of-Words. Meanwhile, machine learning algorithms are Linear Regression, Ridge Regression, KNearest Neighbor for Regression, Regression Tree, and Support Vector Regression (SVR). The results show that SVR with TF-IDF features has the best result of all attempted experiments, with a Pearson correlation score of 0.755 for all data and 0.647 for gold labels data. The final model also accepts newly seen data and displays the corresponding emotion label and intensity.
Co-Authors Alan Darmasaputra Chowanda Benard H. Prabowo Dewi Suryani Glen Iglesias Lie Maximilianus Maria Kolbe Marsella Diansari Nadia Nadia Rhio Sutoyo Rindy Claudia Setiawan Valentino Ekaputra Widiya Nurfitri