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29,939 Article Results

Family planning instructor’s performance in the toddler family development program

10.11591/ijphs.v10i3.20868
Simon Sumanjoyo Hutagalung , Dedy Hermawan , Amir Husin
Family planning instructors are vital in implementing the toddler family development program considering their function. This article aims: i) Analyze the performance of family planning instructors in the implementation of the toddler family development program/bina keluarga balita (BKB); ii) Analyse the factors supporting and inhibiting the effectiveness of the performance of family planning instructors in the community. This research used quantitative methods through survey instruments with a population of all family planning instructors which implementing toddler family development program. The pandemic situation has made the data collection process carried out by online questionnaires with Google Forms application. In order to obtain the required data, data collection was carried out through a questionnaire with a sample of 84 respondents. Data analysis was performed through descriptive statistical analysis using MS.Excel and SPSS. The data analysis concluded that the performance of family planning instructors in managing the program is in the good category. In the process approach, effectiveness is shown from the fulfillment of these performance variables in the implementation of the program, so that by looking at the categories in the cumulative analysis that are in the good category.
Volume: 10
Issue: 3
Page: 608-616
Publish at: 2021-09-01

Early childhood care and education trainees’ perspectives of their career path

10.11591/ijere.v10i3.20856
Roznim Mohamad Rasli , Nor Azah Abdul Aziz , Erni Marlina Saari , Mazlina Che Mustafa , Sopia Md Yassin
Education, either formal or informal, plays an important role to help the masses. As such, educators, especially trainees, are entrusted to teach young generations all important elements, principles, or concepts in a wide range of disciplines. Surely, such an undertaking, especially for early childhood care and education, requires quality teachers. In this regard, existing early childhood care and education modules or curricula should be periodically reviewed and revamped (if necessary) to help produce competent teachers who are excellent in all aspects encompassing content, pedagogical, and technological knowledge. This paper discusses the professional growth and development of trainees in early childhood care and education (ECCE) in terms of short- and long-term goals, missions, and career path-planning. The paper also elaborates on the relevant training workshops, courses, modules, and curricula that can be implemented to help improve their practical skills. The discussion also highlights the importance of incentives, such as attractive salaries, bonuses, acknowledgments, and awards, from employers that can not only motivate trainees but also advance their professional growth and development. Certainty, strong development knowledge, practical skills, and experiences can help such trainees to be become highly competent, which can significantly contribute to nation-building efforts in Malaysia.
Volume: 10
Issue: 3
Page: 1001-1007
Publish at: 2021-09-01

Performance evaluation of SIFT against common image deformations on iban plaited mat motif images

10.11591/ijeecs.v23.i3.pp1470-1477
Silvia Joseph , Irwandi Hipiny , Hamimah Ujir , Sarah Flora Samson Juan , Jacey-Lynn Minoi
Decorative plaited mat is one of the many examples of rich plait work often seen on Borneo handicraft products. The plaited mats are decorated with simple and complex motif designs; each has its own special meaning and taboos. The motif designs are used as a reflection of environment and the traditional beliefs in the Iban community. In line with efforts from UNESCO’s and Sarawak Government’s, digitization, and the use of IR4.0 technologies to preserve and promote this cultural heritage is encouraged. Towards this end goal, we present a novel image dataset containing 10 Iban plaited mat motif classes. The plaited mat motifs are made of diagonal and symmetrical shapes, as well as geometric and non-geometric patterns. Classification’s accuracy using scale-invariant feature transform (SIFT) features was evaluated against 6 common image deformations: zoom+rotation, viewpoint, image blur, JPEG compression, scale and illumination, across multiple threshold values. Varying degrees of each deformation were applied to a digitally cleaned (and cropped) image of each mat motif class. We used RANSAC to remove outliers from the noisy SIFT matching result. The optimal threshold value is 2.0e-2 with a reported 100.0% matching accuracy for the scale change and zoom+rotation set.
Volume: 23
Issue: 3
Page: 1470-1477
Publish at: 2021-09-01

Family support and quality of life of schizophrenia patients

10.11591/ijphs.v10i3.20915
Ni Made Setiawati , Anak Agung Sagung Sawitri , Cokorda Bagus Jaya Lesmana
Schizophrenia remains a global issue. More than half of those living with schizophrenia have yet to receive appropriate treatment that led to the impeded of their recovery and the low quality of life. This study aimed to understand the relationship between familial supports with the quality of life (QOL) of persons with schizophrenia. The cross-sectional study was conducted on randomly selected 161 outpatients at 13 community health centers (puskesmas). Family support and quality of life data were collected by interviewing the respondents with the Friedman’s family support questionnaire and WHO quality of life (WHOQOL-BREF) questionnaire. Subsequently, data was analyzed using logistic regression. The respondents have a mean age of 45 years, mostly males, have completed high school, mostly unemployed and unmarried. Instrumental (AOR=3.177; 95%CI 1.01-9.91) and appraisal support (AOR=7.620; 95%CI 2.83-20.4) were significantly associated with QOL. Conversely, no significant relationship was found between emotional (AOR=1.345; 95%CI 0.46-3.88) and informational (AOR=2.515; 95%CI 0.85-7.42) support toward QOL. Employment, being married and not experiencing relapse were significantly related to QOL. Instrumental support and appraisal support are important factors in determining the quality of life of persons with schizophrenia. Hence, the government needs to expand the roles of family and community to support these roles.
Volume: 10
Issue: 3
Page: 696-703
Publish at: 2021-09-01

A framework to shape the recommender system features based on participatory design and artificial intelligence approaches

10.11591/ijai.v10.i3.pp727-734
Tajul Rosli Razak , Mohammad Hafiz Ismail , Shukor Sanim Mohd Fauzi , Ray Adderley JM Gining , Ruhaila Maskat
A recommender system is an algorithm aiming at giving suggestions to users on relevant elements or items such as products to purchase, books to read, jobs to apply or anything else depending on industries or situations. Recently, there has been a surge in interest in developing a recommender system in a variety of areas. One of the most widely used approaches in recommender systems is collaborative filtering (CF). The CF is a strategy for automatically creating a filter based on a user's needs by extracting desires or recommendation information from a large number of users. The CF approach uses multiple correlation steps to do this. However, the occurrence of uncertainty in finding the best similarity measure is unavoidable. This paper outlines a method for improving the configuration of a recommender system that is tasked with recommending an appropriate study field and supervisor to a group of final-year project students. The framework we suggest is built on a participatory design methodology that allows students' individual opinions to be factored into the recommender system's design. The architecture of the recommender scheme was also illustrated using a real-world scenario, namely mapping the students' field of interest to a possible supervisor for the final year project.
Volume: 10
Issue: 3
Page: 727-734
Publish at: 2021-09-01

Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation

10.11591/ijeecs.v23.i3.pp1385-1397
Siti Fatimah Sulaiman , M. F. Rahmat , Ahmad Athif Faudzi , Khairuddin Osman , N. H. Sunar
The issues of inaccurate positioning control have made an industrial use of pneumatic actuator remains restricted to certain applications only. Non-compliance with system limits and properly control the operating system may also degrade the performance of pneumatic positioning systems. This study proposed a new approach to enhance pneumatic positioning system while considering the constraints of system. Firstly, a mathematical model that represented the pneumatic system was determined by system identification approach. Secondly, model predictive controller (MPC) was developed as a primary controller to control the pneumatic positioning system, which took into account the constraints of the system. Next, to enhance the performance of the overall system, nonlinear gain function was incorporated within the MPC algorithm. Finally, the performances were compared with other control methods such as constrained MPC (CMPC), proportional-integral (PI), and predictive functional control with observer (PFC-O). The validation based on real-time experimental results for 100 mm positioning control revealed that the incorporation of nonlinear gain within the MPC algorithm improved 21.03% and 2.69% of the speed response given by CMPC and PFC-O, and reduced 100% of the overshoot given by CMPC and PI controller; thus, providing fast and accurate pneumatic positioning control system.
Volume: 23
Issue: 3
Page: 1385-1397
Publish at: 2021-09-01

An effective face recognition method using guided image filter and convolutional neural network

10.11591/ijeecs.v23.i3.pp1699-1707
Yallamandaiah S. , Purnachand N.
In the area of computer vision, face recognition is a challenging task because of the pose, facial expression, and illumination variations. The performance of face recognition systems reduces in an unconstrained environment. In this work, a new face recognition approach is proposed using a guided image filter, and a convolutional neural network (CNN). The guided image filter is a smoothing operator and performs well near the edges. Initially, the ViolaJones algorithm is used to detect the face region and then smoothened by a guided image filter. Later the proposed CNN is used to extract the features and recognize the faces. The experiments were performed on face databases like ORL, JAFFE, and YALE and attained a recognition rate of 98.33%, 99.53%, and 98.65% respectively. The experimental results show that the suggested face recognition method attains good results than some of the state-of-the-art techniques.
Volume: 23
Issue: 3
Page: 1699-1707
Publish at: 2021-09-01

The cloud computing systems’ adoption in the higher education sector in Oman in light of the COVID-19 pandemic

10.11591/ijere.v10i3.21671
Salim Al-Hajri , Abdelghani Echchabi , Abdullah Mohammed Ayedh , Mohammed Mispah Said Omar
The objective of the research was to find out the key factors that influence the acceptance and usage of cloud computing systems in the Omani higher education sector, with special emphasis on the COVID-19 outbreak. For this purpose, a quantitative research approach was conducted where 200 students from several Omani higher education institutions were surveyed, and by using Partial Least Square (PLS) to analysis the collected data. The findings revealed that the intention to use cloud computing in this context is significantly dependent on its perceived ease of use, usefulness, perceived reliability and responsiveness. It is noteworthy that this is one of the early studies that address the subject of cloud computing usage during times of crises, and specifically the COVID-19 outbreak. As such, it provides significant contributions in the area of technology adoption.
Volume: 10
Issue: 3
Page: 930-937
Publish at: 2021-09-01

Knowledge, attitude and practices of the university students about COVID-19 during the Luzon lockdown in the Philippines

10.11591/ijphs.v10i3.20844
Jomell Miranda Santiago , Angelo Reyes Santos
The Philippines is one of the many countries around the world that imposed lockdowns to stop the transmission of coronavirus disease 2019 (COVID-19). During the lockdown period, the Department of Health carried out a massive information dissemination campaign about COVID-19. Thus, the researchers want to determine the knowledge, attitude and practices of the students about the COVID-19 during the Luzon lockdown. A descriptive research design and purposive sampling were used. A questionnaire was utilized to collect data composed of the profile, questions regarding their knowledge, attitude and practice towards COVID-19 and their source of knowledge. Permission to conduct and informed consent was obtained. Data were analyzed using various statistical tools. The majority of the respondents had well to very good knowledge of COVID-19 and their source of knowledge was mainly from television and the internet. They also had a very positive attitude and they practice the different ways to prevent COVID-19. The difference between their gender and family income to their knowledge about COVID-19 was significant. Therefore, an intensified campaign should be done to reach those individuals who have limited access to television and the internet and help them to have a positive attitude and correct practices towards COVID-19.
Volume: 10
Issue: 3
Page: 670-678
Publish at: 2021-09-01

Are students with disabilities ready for college? The influence of college readiness to college engagement

10.11591/ijere.v10i3.21692
Alies Poetri Lintangsari , Ive Emaliana , Fatmawati Fatmawati , Unita Werdi Rahajeng
Inclusive education is seen as promising way to accommodate students with disabilities in accessing higher education; yet, the implementation leaves challenges for the students with disabilities and also the faculties. Regarding the secondary education curriculum that is not preparing students with disabilities to attend higher education, students with disabilities are struggling in adjusting college life. This research aimed at confirming the influence of college readiness to college engagement of students with disabilities. There were 61 college students with disabilities participated in the survey on college readiness and college engagement. Independent T-Test and simple regression analysis was applied to test the hypothesis. The result showed that the college readiness influence college engagement with large effect size (r=.769>0.50, F=85.494, p (.000) <0.01) which indicates that the more students are college-ready, the more they are engaged. Subsection’s variables of gender and education background do not statistically significant affect the college readiness and engagement of students with disabilities. As the opportunity for students with disabilities attending college is uprising, college transition program is highly suggested to prepare students with disability for college life.
Volume: 10
Issue: 3
Page: 845-853
Publish at: 2021-09-01

Design and simulation of cascaded H-bridge multilevel inverter with energy storage

10.11591/ijeecs.v23.i3.pp1289-1298
Tan Chee Ting , Zulhani Rasin , Chan Sia Ching
Stand-alone power system provides a solution for the user in rural areas that are disconnected from the utility grid which requires power electronics device for the power conversion. This work proposes a design of 5-level cascaded H-bridge inverter with energy storage to realize DC-AC power conversion for such system. The DC-DC bidirectional converter is designed to control the charging and discharging of current into/from the battery during the buck and boost mode of operation. At the DC side, dual-loop control strategy using PI controllers is designed to control the current and voltage. The inner loop current controller controls the recharging/discharging of current for the battery, while the outer voltage controller controls the DC link voltage at 200 V for each of the H-bridge unit. At the AC side, multiple feedback loop control strategy regulates the inverter output voltage at 240 Vrms under various load change. The modelling and design of the system is implemented under Matlab Simulink environment. From the results, the battery storage unit works well with the DC link voltage to achieve a balance power transfer within the system between the PV source, load and battery storage under variation of PV power and loading condition.
Volume: 23
Issue: 3
Page: 1289-1298
Publish at: 2021-09-01

Novel deep learning model for vehicle and pothole detection

10.11591/ijeecs.v23.i3.pp1576-1582
Gayathri K. , Thangavelu S.
The most important aspect of automatic driving and traffic surveillance is vehicle detection. In addition, poor road conditions caused by potholes are the cause of traffic accidents and vehicle damage. The proposed work uses deep learning models. The proposed method can detect vehicles and potholes using images. The faster region-based convolutional neural network (CNN) and the inception network V2 model are used to implement the model. The proposed work compares the performance, accuracy numbers, detection time, and advantages and disadvantages of the faster region-based convolution neural network (Faster R-CNN) with single shot detector (SSD) and you only look once (YOLO) algorithms. The proposed method shows good progress than the existing methods such as SSD and YOLO. The measure of performance evaluation is Accuracy. The proposed method shows an improvement of 5% once compared with the previous methods such as SSD and YOLO.
Volume: 23
Issue: 3
Page: 1576-1582
Publish at: 2021-09-01

Internet of things and fuzzy logic for smart street lighting prototypes

10.11591/ijai.v10.i3.pp528-535
Mindit Eriyadi , Ade Gafar Abdullah , Hasbullah Hasbullah , Sandy Bhawana Mulia
Internet of things (IoT) and fuzzy logic are very useful in increasing the efficiency and effectiveness of a system; this study applies both to the street lighting systems. The prototype of a street lighting control and monitoring system has been completed. The status of lights that are on or off and the value of the light intensity can be monitored by using IoT. The intensity of the light is fuzzy controlled by utilizing the presence of vehicles and pedestrians around the lights. The prototype is made with a scale against real conditions. Data is processed and transmitted using a microcontroller and Wi-Fi on the IoT module. Mobile applications have been used on smartphone interfaces to monitor and control lamps wherever they are connected to the Internet. Changes in the status of lights to turn on or off are done by the relay module. The fuzzy light intensity control system uses sensors and microcontrollers by utilizing the presence of vehicles and pedestrians around the lights. Performance evaluation has been carried out on a miniature street lighting with the results of monitoring and control following its function. An analysis of the resulting energy savings has been demonstrated.
Volume: 10
Issue: 3
Page: 528-535
Publish at: 2021-09-01

Big transfer learning for automated skin cancer classification

10.11591/ijeecs.v23.i3.pp1611-1619
Zinah Mohsin Arkah , Dalya S. Al-Dulaimi , Ahlam R. Khekan
Skin cancer is an example of the most dangerous disease. Early diagnosis of skin cancer can save many people’s lives. Manual classification methods are time-consuming and costly. Deep learning has been proposed for the automated classification of skin cancer. Although deep learning showed impressive performance in several medical imaging tasks, it requires a big number of images to achieve a good performance. The skin cancer classification task suffers from providing deep learning with sufficient data due to the expensive annotation process and required experts. One of the most used solutions is transfer learning of pre-trained models of the ImageNet dataset. However, the learned features of pre-trained models are different from skin cancer image features. To end this, we introduce a novel approach of transfer learning by training the pre-trained models of the ImageNet (VGG, GoogleNet, and ResNet50) on a large number of unlabelled skin cancer images, first. We then train them on a small number of labeled skin images. Our experimental results proved that the proposed method is efficient by achieving an accuracy of 84% with ResNet50 when directly trained with a small number of labeled skin and 93.7% when trained with the proposed approach.
Volume: 23
Issue: 3
Page: 1611-1619
Publish at: 2021-09-01

The effects of the cross-entropy stopping criterion and quadrature amplitude modulation on iterative turbo decoding performance

10.11591/ijeecs.v23.i3.pp1557-1564
Roslina Mohamad , Mohamad Yusuf Mat Nasir , Nuzli Mohamad Anas
One of the most often-used stopping criteria is the cross-entropy stopping criterion (CESC). The CESC can stop turbo decoder iterations early by calculating mutual information improvements while maintaining bit error rate (BER) performance. Most research on iterative turbo decoding stopping criteria has utilised low-modulation methods, such as binary phase-shift keying. However, a high-speed network requires high modulation to transfer data at high speeds. Hence, a high modulation technique needs to be integrated into the CESC to match its speed. Therefore, the present paper investigated and analysed the effects of the CESC and quadrature amplitude modulation (QAM) on iterative turbo decoding. Three thresholds were simulated and tested under four situations: different code rates, different QAM formats, different code generators, and different frame sizes. The results revealed that in most situations, the use of CESC is suitable only when the signal-to-noise ratio (SNR) is high. This is because the CESC significantly reduces the average iteration number (AIN) while maintaining the BER. The CESC can terminate early at a high SNR and save more than 40% AIN compared with the fixed stopping criterion. Meanwhile, at a low SNR, the CESC fails to terminate early, which results in maximum AIN.
Volume: 23
Issue: 3
Page: 1557-1564
Publish at: 2021-09-01
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