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myBas driving cycle for Kuala Terengganu city

10.11591/ijece.v11i3.pp2054-2061
J. S. Norbakyah , M. I. Nordiyana , I. N. Anida , A. F. Ayob , A. R. Salisa
Driving cycles are series of data points that represent vehicle speed versus time sequenced profile developed for specific road, route, city or certain location. It is widely utilized in the application of vehicle manufacturers, environmentalists and traffic engineers. Since the vehicles are one of the higher air pollution sources, driving cycle is needed to evaluate the fuel consumption and exhaust emissions. The main objectives in this study are to develop and characterize the driving cycle for myBAS in Kuala Terengganu city using established k-means clustering method and to analyse the fuel consumption and emissions using advanced vehicle simulator (ADVISOR). Operation of myBAS offers 7 trunk routes and one feeder route. The research covered on two operation routes of myBAS which is Kuala Terengganu city-feeder and from Kuala Terengganu to Jeti Merang where the speed-time data is collected using on-board measurement method. In general, driving cycle is made up of a few micro-trips, defined as the trip made between two idling periods. These micro-trips cluster by using the k-means clustering method and matrix laboratory software (MATLAB) is used in developing myBAS driving cycle. Typically, developing the driving cycle based on the real-world in resulting improved the fuel economy and emissions of myBAS.
Volume: 11
Issue: 3
Page: 2054-2061
Publish at: 2021-06-01

Application of Tamarindus indica seed extract as bio-coagulant to removal suspended solids and colors

10.11591/ijphs.v10i2.20686
Agustin Dewi , Iva Rustanti Eri , Hermiyanti Pratiwi , Nerawati Diana A.T , Narwati Narwati
The batik traditional industries in East Java, Indonesia generally not have a proper wastewater treatment plant yet, so liquid waste directly discharge into the river. Batik wastewater generally have a dark color, which derived from the coloring of naphthol with number of suspended solids greater than 100 mg/L and color concentration more than 250 Pt.Co. Tamarind seed extract is known to contain natural polyelectrolytes active group, which had function as bio-coagulant. The research objective was to analyze the application of tamarind seed extract as bio-coagulant in wastewater treatment of the Batik traditional industries, by reducing suspended solids levels and color of wastewater. The research design used pretest and posttest control group design with variations of bio-coagulant doses of 10ml/L, 30ml/L, and 50ml/L, and analyzed using the Two Way Anova Test. The results showed that the level of suspended solids in wastewater before treatment averaged 291mg/L, and the average color content was 593 Pt-Co, so it did not meet the quality standards of the Governor of East Java No 72/2013. For the highest reduction in suspended solids levels at a dose of 10ml/L reduced up to 95.1% and the highest decrease in color levels at a dose of 50ml/L, reduced up to 87.8%. Traditional batik wastewater treatment, which used a coagulation-flocculation process with bio-coagulant extract of tamarind seeds could reduce levels of suspended solids and colors, in order to meet the specified quality standards.
Volume: 10
Issue: 2
Page: 324-329
Publish at: 2021-06-01

Measure the effectiveness of information systems with the naïve bayes classifier method

10.11591/ijai.v10.i2.pp414-420
Agung Triayudi , Sumiati Sumiati , Saleh Dwiyatno , Dentik Karyaningsih , Susilawati Susilawati
Technological advances at this time are developing very fast, information systems became the frontline in technological advancements, the need for information systems to support jobs is increasingly high. However, its implementation for users does not have a significant impact, so that it needs to be reviewed and re-evaluated in the use of the information system built. The naive bayes classifier method can provide "effective" and "ineffective" conclusions and is used as material for evaluation and improvement. The purpose of this study is to contribute to measuring the effectiveness of the information system, to solve problems with the naïve bayes classifier method approach which has advantages in the process of classifying data and predicting data. From the test results three times, training has been conducted using 100 data, accuracy value of 84.82% and error 15.18%.
Volume: 10
Issue: 2
Page: 414-420
Publish at: 2021-06-01

Pedestrian age estimation based on deep learning

10.11591/ijeecs.v22.i3.pp1548-1555
Nawal Younis Abdullah , Mohammed Talal Ghazal , Najwan Waisi
The large-scale distribution of camera networks in the traffic area resulted in the increasing popularity of video surveillance systems. As pedestrian detection and tracking are the critical monitoring targets in traffic surveillance, many studies focus on pedestrian detection algorithms across cameras. This paper addressed the effect of using the age estimation based on deep convolution neural network (CNN) as a convenience for pedestrian monitoring who is crossing at intersections. Two popular deep convolutional neural networks (DCNNs) pre-trained models have been used in this work, which have recently achieved the best performance in facial features extraction tasks: VGG-Face and ResNet-50. We combined these two models to increase the efficiency of the proposed system. We ran our experiments to evaluate the system based on the VGGFace2 dataset consisting of 3.31 million face images. From the experimental results, we observed a gap in the detection performances between those age groups: children from (00-10) years and elderly with 55 years and more. Moreover, it noted that the proposed pedestrian age estimation model performance is high, also a good result can be obtained by using the model for new purpose.
Volume: 22
Issue: 3
Page: 1548-1555
Publish at: 2021-06-01

Modification of Calgary Cambridge for Indonesian medical students: Communication guidelines

10.11591/ijphs.v10i2.20612
Galih Cahya Wijayanti , Rizma Adlia Syakurah , Mariatul Fadilah
Effective communication skill applied by doctors in the doctor-patient consultation process becomes one of important factors that can improve the consultation outcomes such as patient satisfaction, adherence to treatment and recovery process. However, effective doctor-patient communication is rarely applied in practice. Limited consultation time, patient overload, doctor burnout, and poor communication skills are among the factors that cause ineffective doctor-patient communication process. This study aimed to develop a new effective communication guideline for doctor-patient communication in Indonesia by modifying the Calgary Cambridge medical interview guide. This study uses qualitative approach within four stages: expert panel, student panel and focus group discussion, expert review, and trials. Informants were chosen purposively. Three points of high category, 24 points of middle category and 44 points of low category are resulted from expert panel stage which consists of specialist representatives from 12 clinical divisions in Dr. Moehammad Hoesin central public hospital (RSMH), Palembang, South Sumatera, Indonesia. The high and middle category were discussed by two groups of internships doctors in RSMH in student panel and focus group discussion (FGD) session. The results were validated by a doctor-patient communication expert (expert reviewer) and then tested by the internship doctors through role play at the trial stage. The final result yields eight main points and eleven effective tips of the Calgary Cambridge Guide checklist modification with five to six minutes effective consultation time. This modified guideline is appropriately applicable for doctor-patient communication in daily consultation in Indonesian practical, social and cultural context.
Volume: 10
Issue: 2
Page: 361-369
Publish at: 2021-06-01

Relationship of knowledge and attitude with food handling practices: A systematic review

10.11591/ijphs.v10i2.20665
Kholis Ernawati , Qatrunnada Nadhifah , Anis Muslikha , Muhammad Hidayat , Tri Edhi Budhi Soesilo , Fathul Jannah , Dini Widianti , Yusnita Yusnita
Foodborne disease is still a public health problem in several countries. Food handler's knowledge, attitude, and practice (KAP) are factors that are risk factors for foodborne disease incidence. The research objective was to assess the level of knowledge, attitudes, and behavior of food handlers in maintaining food hygiene using a systematic review approach. The research method used is the preferred reporting items for systematic review and meta-analyses (PRISMA) protocol approach. The article search process was accessed on PLOS ONE, Pro-Quest, and Google Scholar. A descriptive analysis was carried out on each research variable. The results obtained eight papers (100% sociodemography, 100% knowledge, 62.5% attitude, and 87.5% behavior). The mean of significant articles on sociodemographic variables was 18.5%, experience 59.38%, attitudes 13.33%, and 23.81%. There are 37.5% of the articles showed significant relationship between knowledge and attitude with food handling practice.
Volume: 10
Issue: 2
Page: 336-347
Publish at: 2021-06-01

Half-face based recognition using principal component analysis

10.11591/ijeecs.v22.i3.pp1404-1410
Ahmed M. Alkababji , Sara Raed Abd
Face recognition is a considerable problem in the field of image processing. It is used daily in various applications from personal cameras to forensic investigations. Most of the provides solutions proposed based on full-face images, are slow to compute and need more storage. In this paper, we propose an effective way to reduce the features and size of the database in the face recognition method and thus we get an increase in the speed of discrimination by using half of the face. Taking advantage of face symmetry, the first step is to divide the face image into two halves, then the left half is processed using the principal component analysis (PCA) algorithm, and the results are compared by using Euclidian distance to distinguish the person. The system was trained and tested on ORL database. It was found that the accuracy of the system reached up to 96%, and the database was minimized by 46% and the running time was decreased from 120 msec to 70 msec with a 41.6% reduction.
Volume: 22
Issue: 3
Page: 1404-1410
Publish at: 2021-06-01

Healthy family index assessment through community-based health information system approach

10.11591/ijphs.v10i2.20751
Rico Kurniawan , Ryza Jazid Baharuddin Nur , Sayekti Yuliyanti , Dion Zein Nuridzin , Neng Tine Kartinah
The healthy Indonesia program with a family approach (PIS-PK) has not been implemented optimally. There are several obstacles and challenges in this program’s implementation, e.g., human resources. A community-based health information system (CBHIS) is a strategic approach to obtain data and information at the population level by directly involving cadres and the community. A project with the CBHIS approach was implemented in Kasemen Village, Serang, Banten Province, Indonesia to support the PIS-PK program. The study aimed to determine the population’s health status according to the healthy family index through the CBHIS approach. The data of healthy family indicators in the village were collected by cadres using a mHealth application. Overall, 1316 households consisting of 5312 residents were registered. The analysis results of the healthy family index showed that most families in the Kasemen subdistrict were pre-healthy (64.2%), almost one third were unhealthy (27.8%) and only a small proportion were healthy (8%). Assessing the healthy family index through the CBHIS approach can support decision-making at the community level, thereby determining the magnitude of family health problems and providing appropriate interventions to improve community health status. Well-trained cadres equipped with better electronic data collection tools may be an alternative to community-based data collection.
Volume: 10
Issue: 2
Page: 394-400
Publish at: 2021-06-01

Predictive model of water stress in tenera oil palm by means of spectral signature methods

10.11591/ijece.v11i3.pp2680-2687
Angie Marcela Galvez Valencia , Yeison Alberto Garces-Gomez , Erwin Leandro Lemus Rodriguez , Miguel Andres Arango Argoti
Agriculture as a competitive business, seeks to improve productivity within crops with a more sustainable environmental management. It is important that agriculture includes new technologies that allow it to generate differential, precise and real-time information. In Colombia, the current lack of knowledge about techniques that allow early identification of water stress in African palm could generate a loss in the investment made in the fertilization of the crop, cause an increase in diseases, pests, and susceptibility to compaction or abortions in female flowers that would lead to decreases in production. In this work, a predictive model is established to quantify water stress based on spectral, physiological and soil information in African palm plants. To this end, a study was carried out in an oil palm plantation where treatments were established with 3 ranges of humidity. It was found that the indices with the highest correlation with the biophysical variable soil moisture were: NDVI_1 and NDVI_16 for treatment 1, SR_4 for treatment 2 and NDVI_16 and NDVI_20 for treatment 3. Finally, the third order polynomial regression model that obtained higher correlation coefficients of Pearson R^2=0.73 was selected as the most suitable model to estimate soil moisture content for treatments 2 and 3.
Volume: 11
Issue: 3
Page: 2680-2687
Publish at: 2021-06-01

Files cryptography based on one-time pad algorithm

10.11591/ijece.v11i3.pp2335-2342
Ahmad Mohamad Al-Smadi , Ahmad Al-Smadi , Roba Mahmoud Ali Aloglah , Nisrein Abu-darwish , Ahed Abugabah
The Vernam-cipher is known as a one-time pad of algorithm that is an unbreakable algorithm because it uses a typically random key equal to the length of data to be coded, and a component of the text is encrypted with an element of the encryption key. In this paper, we propose a novel technique to overcome the obstacles that hinder the use of the Vernam algorithm. First, the Vernam and advance encryption standard AES algorithms are used to encrypt the data as well as to hide the encryption key; Second, a password is placed on the file because of the use of the AES algorithm; thus, the protection record becomes very high. The Huffman algorithm is then used for data compression to reduce the size of the output file. A set of files are encrypted and decrypted using our methodology. The experiments demonstrate the flexibility of our method, and it’s successful without losing any information.
Volume: 11
Issue: 3
Page: 2335-2342
Publish at: 2021-06-01

Interaction of IT investment mandates and mobile savvy affecting mobile office performance in corporates: Focusing on the moderating effects of IT savvy

10.11591/ijece.v11i3.pp2378-2385
Moon Junghoon , Yoo Sunggoo , Lee Jongtae
This study investigates the effect of IT investment portfolios on the performance of mobile business services, as well as the moderating role of IT savvy. This study pulls the concept of IT investment mandates into the conceptual research framework of mobile investment. A survey for the IT specialists working at 123 enterprise-level companies was conducted and hierarchical regression analysis was adopted. Our results show that IT investment and organizational IT capabilities influence the performance of the mobile office and that IT savvy plays as a moderator in the relationship between investment mandates and mobile office performance. This research also may indicate that transactional assets are most helpful factors for a change by the adoption of mobile technology. This study is a rare research paper to explain the impact of IT investment portfolios on the mobile office performance in an academic methodology.
Volume: 11
Issue: 3
Page: 2378-2385
Publish at: 2021-06-01

Fully automatic segmentation of intima/adventitia of the vessel using Bezier curve from intravascular ultrasound

10.11591/ijece.v11i3.pp2640-2646
Kwang Baek Kim , Doo Heon Song
Although medical image segmentation field is regarded as one of most established fields, still fully automatic segmentation to extract target object with high accuracy from intravascular ultrasound (IVUS) is very active area of research. In this paper, we propose a fully automatic morphological approach using Bezier curve in interpolating the boundaries of intima/adventitia of the vessel from IVUS with careful binarization algorithms. In experiment with 800 IVUS images, the proposed method is as good as fuzzy C-means based approach in comparison with human expert’s result with 84.4% satisfaction and better than other morphological method in all performance indices of curve fitting with 97.02% in accuracy and 58.19% in precision.
Volume: 11
Issue: 3
Page: 2640-2646
Publish at: 2021-06-01

Hybrid feature selection method based on particle swarm optimization and adaptive local search method

10.11591/ijece.v11i3.pp2414-2422
Malek Alzaqebah , Sana Jawarneh , Rami Mustafa A. Mohammad , Mutasem K. Alsmadi , Ibrahim Al-marashdeh , Eman A. E. Ahmed , Nashat Alrefai , Fahad A. Alghamdi
Machine learning has been expansively examined with data classification as the most popularly researched subject. The accurateness of prediction is impacted by the data provided to the classification algorithm. Meanwhile, utilizing a large amount of data may incur costs especially in data collection and preprocessing. Studies on feature selection were mainly to establish techniques that can decrease the number of utilized features (attributes) in classification, also using data that generate accurate prediction is important. Hence, a particle swarm optimization (PSO) algorithm is suggested in the current article for selecting the ideal set of features. PSO algorithm showed to be superior in different domains in exploring the search space and local search algorithms are good in exploiting the search regions. Thus, we propose the hybridized PSO algorithm with an adaptive local search technique which works based on the current PSO search state and used for accepting the candidate solution. Having this combination balances the local intensification as well as the global diversification of the searching process. Hence, the suggested algorithm surpasses the original PSO algorithm and other comparable approaches, in terms of performance.
Volume: 11
Issue: 3
Page: 2414-2422
Publish at: 2021-06-01

Outliers detection in state-space model using indicator saturation approach

10.11591/ijeecs.v22.i3.pp1688-1696
Farid Zamani Che Rose , Mohd Tahir Ismail , Mohd Hanafi Tumin
Structural changes that occur due to outliers may reduce the accuracy of an estimated time series model, shifting the mean distribution and causing forecast failure. This study used general-to-specific approach to detect outliers via indicator saturation approach in the local level model framework. Focusing on impulse indicator saturation, performance recorded by the suggested approach was evaluated using Monte Carlo simulations. To tackle the issue of higher number of regressors compared to the number of observations, this research utilized the split-half approach algorithm. We found that the impulse indicator saturation performance relies heavily on the size of outlier, location of outlier and number of splits in the series examined. Detection of outliers using sequential and non-sequential algorithms is the most crucial issue in this study. The sequential searching algorithm was able to outperform the non-sequential searching algorithm in eliminating the non-significant indicators based on potency and gauge. The outliers captured using impulse indicator saturation in financial times stock exchange (FTSE) United States of America (USA) shariah index correspond to the financial crisis in 2008-2009.
Volume: 22
Issue: 3
Page: 1688-1696
Publish at: 2021-06-01

Classification of ECG signals for detection of arrhythmia and congestive heart failure based on continuous wavelet transform and deep neural networks

10.11591/ijeecs.v22.i3.pp1520-1528
Rashidah Funke Olanrewaju , S. Noorjannah Ibrahim , Ani Liza Asnawi , Hunain Altaf
According to World Health Organization (WHO) report an estimated 17.9 million lives are being lost each year due to cardiovascular diseases (CVDs) and is the top contributor to the death causes. 80% of the cardiovascular cases include heart attacks and strokes. This work is an effort to accurately predict the common heart diseases such as arrhythmia (ARR) and congestive heart failure (CHF) along with the normal sinus rhythm (NSR) based on the integrated model developed using continuous wavelet transform (CWT) and deep neural networks. The proposed method used in this research analyses the time-frequency features of an electrocardiogram (ECG) signal by first converting the 1D ECG signals to the 2D Scalogram images and subsequently the 2D images are being used as an input to the 2D deep neural network model-AlexNet. The reason behind converting the ECG signals to 2D images is that it is easier to extract deep features from images rather than from the raw data for training purposes in AlexNet. The dataset used for this research was obtained from Massachusetts Institute of Technology-Boston's Beth Israel Hospital (MIT-BIH) arrhythmia database, MIT-BIH normal sinus rhythm database and Beth Israel Deaconess Medical Center (BIDMC) congestive heart failure database. In this work, we have identified the best fit parameters for the AlexNet model that could successfully predict the common heart diseases with an accuracy of 98.7%. This work is also being compared with the recent research done in the field of ECG Classification for detection of heart conditions and proves to be an effective technique for the classification.
Volume: 22
Issue: 3
Page: 1520-1528
Publish at: 2021-06-01
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