Teddy Surya Gunawan
International Islamic University Malaysia

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Performance Evaluation of Smart Home System using Internet of Things Teddy Surya Gunawan; Intan Rahmithul Husna Yaldi; Mira Kartiwi; Hasmah Mansor
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1117.986 KB) | DOI: 10.11591/ijece.v8i1.pp400-411

Abstract

Nowadays, many researches have been conducted on smart home. Smart home control system (SHCS) can be integrated into an existing home appliances to reduce the need for human intervention, increase security and energy efficiency. We have proposed a smart home system using internet of things and four types of sensors, including PIR, temperature, ultrasonic, and smoke gas sensor for automatic environmental control and intrustion detection. In this paper, the performance of the previously developed prototype of smart home system will be evaluated. First, experiments on various sensors will be conducted. Next, the communicaton channel using wireless and Ethernet modules will be discussed. Moreover, the overall SHCS will be evaluated in terms of hardware and software performance. Additionaly, solar charger enhances the availability of our prototype system. Results showed the effectiveness of our proposed smart home system in the prototype and real life experiments.
Sukuk Rating Prediction using Voting Ensemble Strategy Mira Kartiwi; Teddy Surya Gunawan; Tika Arundina; Mohd Azmi Omar
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (192.942 KB) | DOI: 10.11591/ijece.v8i1.pp299-303

Abstract

Islamic finance development has grown into a focal point in many countries accros the globe. Sukuk, in particular, an Islamic investment product that has received growing attention from sovereigns, multinational and national organizations from both developed and emerging economies. Its uses has been aimed to finance investments in a varieties of economic activities and development projects. Despite the promising look of Sukuk, currently there is lack of studies had been to examine and predict the rating of the Sukuk. As a result, many practitioners adopted the conventional bond hence ignore the fact that these two instruments are different in nature. In order to fill the gap in the literature, it is the aim of this research to develop an ensemble model that can be used to predict Sukuk rating. The effectiveness of the proposed models were evaluated using dataset on Sukuk issuance for domestic from 2006 to 2016. The results indicate that the overall performance of the ensemble model is fall short behind the i duction decision tree (IDT) model. However, the class precision of the ensemble model improved, particularly in predicting the lowest rating of Sukuk.
Design and Implementation of Portable Outdoor Air Quality Measurement System using Arduino Teddy Surya Gunawan; Yasmin Mahira Saiful Munir; Mira Kartiwi; Hasmah Mansor
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (755.272 KB) | DOI: 10.11591/ijece.v8i1.pp280-290

Abstract

Recently, there is increasing public awareness of the real time air quality due to air pollution can cause severe effects to human health and environments. The Air Pollutant Index (API) in Malaysia is measured by Department of Environment (DOE) using stationary and expensive monitoring station called Continuous Air Quality Monitoring stations (CAQMs) that are only placed in areas that have high population densities and high industrial activities. Moreover, Malaysia did not include particulate matter with the size of less than 2.5μm (PM2.5) in the API measurement system. In this paper, we present a cost effective and portable air quality measurement system using Arduino Uno microcontroller and four low cost sensors. This device allows people to measure API in any place they want. It is capable to measure the concentration of carbon monoxide (CO), ground level ozone (O3) and particulate matters (PM10 & PM2.5) in the air and convert the readings to API value. This system has been tested by comparing the API measured from this device to the current API measured by DOE at several locations. Based on the results from the experiment, this air quality measurement system is proved to be reliable and efficient.
Development of Quranic Reciter Identification System using MFCC and GMM Classifier Teddy Surya Gunawan; Nur Atikah Muhamat Saleh; Mira Kartiwi
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 1: February 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (392.361 KB) | DOI: 10.11591/ijece.v8i1.pp372-378

Abstract

Nowadays, there are many beautiful recitation of Al-Quran available. Quranic recitation has its own characteristics, and the problem to identify the reciter is similar to the speaker recognition/identification problem. The objective of this paper is to develop Quran reciter identification system using Mel-frequency Cepstral Coefficient (MFCC) and Gaussian Mixture Model (GMM). In this paper, a database of five Quranic reciters is developed and used in training and testing phases. We carefully randomized the database from various surah in the Quran so that the proposed system will not prone to the recited verses but only to the reciter. Around 15 Quranic audio samples from 5 reciters were collected and randomized, in which 10 samples were used for training the GMM and 5 samples were used for testing. Results showed that our proposed system has 100% recognition rate for the five reciters tested. Even when tested with unknown samples, the proposed system is able to reject it.
Development of control system for quadrotor unmanned aerial vehicle using LoRa wireless and GPS tracking Teddy Surya Gunawan; Wan Athereah Yahya; Erwin Sulaemen; Mira Kartiwi; Zuriati Janin
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.16716

Abstract

In the past decades, there has been a growing interest in unmanned aerial vehicles (UAVs) for educational, research, business, and military purposes. The most critical data for a flight system is the telemetry data from the GPS and wireless transmitter and also from the gyroscope and accelerometer.  The objective of this paper is to develop a control system for UAV using long-range wireless communication and GPS. First, Matlab simulation was conducted to obtain an optimum PID gains controller. Then LoRa wireless was evaluated during clear and rainy days. Static and dynamic points measurement was conducted to validate and optimize GPS accuracy. GeoMapping in Matlab and Google GPS GeoPlanner were then used to analyze the traveled UAV flight path.
Development of video-based emotion recognition using deep learning with Google Colab Teddy Surya Gunawan; Arselan Ashraf; Bob Subhan Riza; Edy Victor Haryanto; Rika Rosnelly; Mira Kartiwi; Zuriati Janin
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 5: October 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i5.16717

Abstract

Emotion recognition using images, videos, or speech as input is considered as a hot topic in the field of research over some years. With the introduction of deep learning techniques, e.g., convolutional neural networks (CNN), applied in emotion recognition, has produced promising results. Human facial expressions are considered as critical components in understanding one's emotions. This paper sheds light on recognizing the emotions using deep learning techniques from the videos. The methodology of the recognition process, along with its description, is provided in this paper. Some of the video-based datasets used in many scholarly works are also examined. Results obtained from different emotion recognition models are presented along with their performance parameters. An experiment was carried out on the fer2013 dataset in Google Colab for depression detection, which came out to be 97% accurate on the training set and 57.4% accurate on the testing set.
On the use of voice activity detection in speech emotion recognition Muhammad Fahreza Alghifari; Teddy Surya Gunawan; Mimi Aminah binti Wan Nordin; Syed Asif Ahmad Qadri; Mira Kartiwi; Zuriati Janin
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (903.469 KB) | DOI: 10.11591/eei.v8i4.1646

Abstract

Emotion recognition through speech has many potential applications, however the challenge comes from achieving a high emotion recognition while using limited resources or interference such as noise. In this paper we have explored the possibility of improving speech emotion recognition by utilizing the voice activity detection (VAD) concept. The emotional voice data from the Berlin Emotion Database (EMO-DB) and a custom-made database LQ Audio Dataset are firstly preprocessed by VAD before feature extraction. The features are then passed to the deep neural network for classification. In this paper, we have chosen MFCC to be the sole determinant feature. From the results obtained using VAD and without, we have found that the VAD improved the recognition rate of 5 emotions (happy, angry, sad, fear, and neutral) by 3.7% when recognizing clean signals, while the effect of using VAD when training a network with both clean and noisy signals improved our previous results by 50%.
The disruptometer: an artificial intelligence algorithm for market insights Mimi Aminah binti Wan Nordin; Dmitry Vedenyapin; Muhammad Fahreza Alghifari; Teddy Surya Gunawan
Bulletin of Electrical Engineering and Informatics Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (550.211 KB) | DOI: 10.11591/eei.v8i2.1494

Abstract

Social media data mining is rapidly developing to be a mainstream tool for marketing insights in today’s world, due to the abundance of data and often freely accessed information. In this paper, we propose a framework for market research purposes called the Disruptometer. The algorithm uses keywords to provide different types of market insights from data crawling. The preliminary algorithm data-mines information from Twitter and outputs 2 parameters-Product-to-Market Fit and Disruption Quotient, which is obtained from a brand’s customer value proposition, problem space, and incumbent space. The algorithm has been tested with a venture capitalist portfolio company and market research firm to show high correlated results. Out of 4 brand use cases, 3 obtained identical results with the analysts ‘studies.
A critical insight into multi-languages speech emotion databases Syed Asif Ahmad Qadri; Teddy Surya Gunawan; Muhammad Fahreza Alghifari; Hasmah Mansor; Mira Kartiwi; Zuriati Janin
Bulletin of Electrical Engineering and Informatics Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (303.859 KB) | DOI: 10.11591/eei.v8i4.1645

Abstract

With increased interest of human-computer/human-human interactions, systems deducing and identifying emotional aspects of a speech signal has emerged as a hot research topic. Recent researches are directed towards the development of automated and intelligent analysis of human utterances. Although numerous researches have been put into place for designing systems, algorithms, classifiers in the related field; however the things are far from standardization yet. There still exists considerable amount of uncertainty with regard to aspects such as determining influencing features, better performing algorithms, number of emotion classification etc. Among the influencing factors, the uniqueness between speech databases such as data collection method is accepted to be significant among the research community. Speech emotion database is essentially a repository of varied human speech samples collected and sampled using a specified method. This paper reviews 34 `speech emotion databases for their characteristics and specifications. Furthermore critical insight into the imitational aspects for the same have also been highlighted.
A novel optimization harmonic elimination technique for cascaded multilevel inverter Ezzidin Hassan Aboadla; Sheroz Khan; Mohamed H. Habaebi; Teddy Surya Gunawan; Belal A. Hamida; Mashkuri Bin Yaacob; Ali Aboadla
Bulletin of Electrical Engineering and Informatics Vol 8, No 2: June 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1385.13 KB) | DOI: 10.11591/eei.v8i2.1500

Abstract

The main goal of utilizing Selective Harmonic Elimination (SHE) techniques in Multilevel Inverters (MLI) is to produce a high-quality output voltage signal with a minimum Total Harmonic Distortion (THD). By calculating N switching angles, SHE technique can eliminate (N-1) low order odd harmonics of the output voltage waveform. To optimized and obtained these switching angles, N of nonlinear equations should be solved using a numerical method. Modulation index (m) and duty cycle play a big role in selective harmonic elimination technique to obtain a minimum harmonic distortion and desired fundamental component voltage. In this paper, a novel Optimization Harmonic Elimination Technique (OHET) based on SHE scheme is proposed to re-mitigate Total Harmonic Distortion. The performance of seven-level H-bridge cascade inverter is evaluated using PSIM and validated experimentally by developing a purposely built microcontroller-based printed circuit board.