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Timothy, Vincentius,Prihatmanto, Ary Setijadi,Rhee, Kyung-Hyune Korea Multimedia Society 2016 The journal of multimedia information system Vol.3 No.2
In this paper, we propose a method to automatically diagnose various diseases. The input data consists of electrocardiograph (ECG) recordings. We extract R-to-R interval (RRI) signals from ECG recordings, which are preprocessed to remove trends and ectopic beats, and to keep the signal stationary. After that, we perform some prospective analysis to extract time-domain parameters, frequency-domain parameters, and nonlinear parameters of the signal. Those parameters are unique for each disease and can be used as the statistical symptoms for each disease. Then, we perform feature selection to improve the performance of the diagnosis classifier. We utilize the selected features to diagnose various diseases using machine learning. We subsequently measure the performance of the machine learning classifier to make sure that it will not misdiagnose the diseases. The first two steps, which are R-to-R extraction and preprocessing, have been successfully implemented with satisfactory results.
Finger -Pointing Gestur e Analysis for Slide Presentation
Maisevli Harika,Ary Setijadi Prihatmanto,Hilwadi Hindersah,Bong-Kee Sin 한국멀티미디어학회 2016 멀티미디어학회논문지 Vol.19 No.8
This paper presents a method for computer-assisted slide presentation using vision-based gesture recognition. The proposed method consists of a sequence of steps, first detecting a hand in the scene of projector beam, then estimating the smooth trajectory of a hand or a pointing finger using Kalman Filter, and finally interfacing to an application system. Additional slide navigation control includes moving back and forth the pages of the presentation. The proposed method is to help speakers for an effective presentation with natural improved interaction with the computer. In particular, the proposed method of using finger pointing is believed to be more effective than using a laser pointer since the hand, the pointing or finger are more visible and thus can better grab the attention of the audience.
Vidyanusa Mathematic Learning Systems Based on Digital Game by Balanced Design Approach
Ramdania, Diena Rauda,Prihatmanto, Ary Setijadi,Kim, Myong Hee,Park, Man-Gon Korea Multimedia Society 2016 멀티미디어학회논문지 Vol.19 No.3
Educational games offer an opportunity to engage and inspire students to take an interest in every subject material in school. The "fun" obtain when playing games become a trigger for the use of games in learning. However, there are doubts whether the players actually learn while they are having fun. Vidyanusa is an Online Mathematics Education Game being developed by Crayonpedia Education Ecosystem in Indonesia. The learning goal of Vidyanusa is to engage junior high school students in learning mathematics. In this paper, we design the Vidyanusa game material Functions and Relations by using Balanced Design Approach. This approach has three models in succession; the Content Model outlines the purpose of the game, the Task Model maps out the mission, and the Evidence Model outlines student measurement. This paper will then discusses the quality of games produced in term of Usability factor for effective results and objective. The measurement of the game was carried out based on International Standard ISO/IEC 9126-1 FDIS about Software Quality Product.
Finger-Pointing Gesture Analysis for Slide Presentation
Maisevli Harika,Ary Setijadi Prihatmanto,Hilwadi Hindersah,신봉기 한국멀티미디어학회 2016 멀티미디어학회논문지 Vol.19 No.8
This paper presents a method for computer-assisted slide presentation using vision-based gesture recognition. The proposed method consists of a sequence of steps, first detecting a hand in the scene of projector beam, then estimating the smooth trajectory of a hand or a pointing finger using Kalman Filter, and finally interfacing to an application system. Additional slide navigation control includes moving back and forth the pages of the presentation. The proposed method is to help speakers for an effective presentation with natural improved interaction with the computer. In particular, the proposed method of using finger pointing is believed to be more effective than using a laser pointer since the hand, the pointing or finger are more visible and thus can better grab the attention of the audience.
Design of Music Learning Assistant Based on Audio Music and Music Score Recognition
Mulyadi, Ahmad Wisnu,Machbub, Carmadi,Prihatmanto, Ary S.,Sin, Bong-Kee Korea Multimedia Society 2016 멀티미디어학회논문지 Vol.19 No.5
Mastering a musical instrument for an unskilled beginning learner is not an easy task. It requires playing every note correctly and maintaining the tempo accurately. Any music comes in two forms, a music score and it rendition into an audio music. The proposed method of assisting beginning music players in both aspects employs two popular pattern recognition methods for audio-visual analysis; they are support vector machine (SVM) for music score recognition and hidden Markov model (HMM) for audio music performance tracking. With proper synchronization of the two results, the proposed music learning assistant system can give useful feedback to self-training beginners.
Komariah, Kokoy Siti,Machbub, Carmadi,Prihatmanto, Ary S.,Sin, Bong-Kee Korea Multimedia Society 2016 멀티미디어학회논문지 Vol.19 No.7
Efficient Market Hypothesis (EMH), states that at any point in time in a liquid market security prices fully reflect all available information. This paper presents a study of proving the hypothesis through daily Twitter sentiments using the hybrid approach of the lexicon-based approach and the naïve Bayes classifier. In this research we analyze the currency exchange rate movement of Indonesia Rupiah vs US dollar as a way of testing the Efficient Market Hypothesis. In order to find a correlation between the prediction sentiments from Twitter data and the actual currency exchange rate trends we collect Twitter data every day and compute the overall sentiment to label them as positive or negative. Experimental results have shown 69% correct prediction of sentiment analysis and 65.7% correlation with positive sentiments. This implies that EMH is semi-strong Efficient Market Hypothesis, and that public information provide by Twitter sentiment correlate with changes in the exchange market trends.