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31,456 Article Results

Impact study on indirect lightning strikes on photovoltaic systems near transmission lines

10.12928/telkomnika.v22i6.26613
Anis Niza; Universiti Teknikal Malaysia Melaka Ramani , Rayyan Che; Suria & Sonne Sdn. Bhd Razali , Aine Izzati; Universiti Teknikal Malaysia Melaka Tarmizi
Grid-integrated photovoltaic (PV) systems are currently undergoing explosive growth in Malaysia. However, as more PV systems are installed close to transmission lines, there are concerns about the impact of electromagnetic (EM) properties affecting the performance and operation of the PV systems if they are exposed to lightning strikes, particularly indirect ones. Therefore, this study aims to model the impact of indirect lightning strikes on PV systems installed in proximity to transmission lines. The model involves developing a 3D model of the PV system together with a sample transmission line and creating an artificial lightning event to study the EM activity within the area. The results are compared to the IEC 61000 standard to determine its level of r\hazard. From the simulation results, it was found that the current intensity, H, of the disturbance, can reach up to 63% more than the standard limit stipulated in the standards. The significance of the study ensures that PV systems installed within the vicinity of power lines or substations have adequate lightning protection systems as well as proper earthing systems.
Volume: 22
Issue: 6
Page: 1581-1589
Publish at: 2024-12-01

Risk analysis of adolescent sexual activity in college Surabaya, Indonesia: cross-sectional study

10.11591/ijphs.v13i4.24302
Eny Qurniyawati , Zida Husnina , Jayanti Dian Eka Sari , Asma Azzahra , Izzah Nur Shabrina , Prima Kartika , Nayla Mohamed Gomaa Nasr
Adolescence is characterized by active sexual hormones that can lead to sexual urges with the opposite sex. These urges, in turn, may trigger risky sexual behavior. College students, in a transitional period from adolescence to early adulthood, exhibit diversity in addressing sexual activity. This research aimed to analyze the risks associated with adolescent sexual activity in a college in Surabaya, Indonesia. The study utilizes a cross-sectional design with accidental sampling of active students aged 18-24 years. The total number of participants in this study was 221 people who filled out a questionnaire in the form of a Google Form, distributed through social media. The results show that, among all the factors identified, dating status has a significant relationship with PR 11.688 (95%CI 5.048-27.061) in engaging in risky sexual activities among adolescents. Reproductive health education at the university level is needed to reduce risky sexual activities among students.
Volume: 13
Issue: 4
Page: 1794-1802
Publish at: 2024-12-01

Performance analysis of terrestrial 6G networks in tropical region

10.12928/telkomnika.v22i6.26057
Husam; Universiti Teknologi Malaysia (UTM) M. Banwair , Jafri; Universiti Teknologi Malaysia (UTM) Din , Khalid Ibrahim; King Saud University Alkhedhairi , Ahmed; Chulalongkorn University Basahel
Next-generation (NG) optical technologies are expected to offer high data rates, multiple broadband services, expandable bandwidth, and flexible communication options for diverse end users. In optical technologies, free space optical (FSO) technology stands out as a promising component to meet the requirements of terrestrial sixth generation (6G) networks. This is due to its cost-effectiveness, ease of deployment, high bandwidth capacity, and robust security features. However, haze and rain are major challenges to FSO link performance. These adverse weather conditions reduce visibility, causing significant attenuation of the laser signal. The resulting attenuation negatively impacts the performance and availability of the FSO link. This paper assesses the performance of a terrestrial FSO link under tropical climate conditions. Predicted attenuation due to haze is analyzed and compared using two wavelengths: 850 nm and 1550 nm. The predicted attenuation is based on a whole year of visibility data in Malaysia, from January 1, 2023 to December 31, 2023. Additionally, the availability of the two wavelengths is evaluated. The findings show that higher wavelengths experience lower attenuation compared to lower wavelengths. These results provide valuable insights into the feasibility of deploying FSO links in tropical climates.
Volume: 22
Issue: 6
Page: 1351-1357
Publish at: 2024-12-01

Improving baseline reduction for emotion recognition based on electroencephalogram signals

10.11591/ijai.v13.i4.pp4263-4272
I Made Agus Wirawan , I Gede Mahendra Darmawiguna , Ida Bagus Nyoman Pascima
The baseline reduction method has been widely used to define electroencephalogram (EEG) signal patterns. However, because the baseline signal in this approach contains artifacts, the baseline reduction approach cannot perform optimally. As a result, decreasing artifacts in the baseline signal is critical. The mean, Gaussian, and Savitzky-Golay filters will be compared in this study to minimize artifacts in the baseline signal. Three secondary datasets are utilized to evaluate these approaches' capacity to remove artifacts. These three strategies are also tested with the convolution neural network classification algorithms. When applied to the dataset for emotion analysis using physiological signals (DEAP) and a dataset for multimodal research of affect, personality traits, and mood on individuals and groups (AMIGOS) datasets, the mean filter can increase baseline reduction performance based on twenty-four test scenarios. On the data readiness for machine learning research (DREAMER) dataset, however, the Gaussian filter is preferable. The relative difference approach was employed in this study's baseline reduction process to generate EEG signal patterns that are easy to recognize throughout the classification phase, which impacts increasing accuracy.
Volume: 13
Issue: 4
Page: 4263-4272
Publish at: 2024-12-01

The relationship between principal inclusive leadership, teacher efficacy and teachers’ innovative behavior

10.11591/ijere.v13i6.29187
Mo Dongxiao , Suhaida Abdul Kadir , Roshafiza Hassan , Enio Kang Mohd Sufian Kang
The objective of this study was to explore the relationship among principals’ inclusive leadership, teachers’ sense of efficacy, and teachers’ innovative behaviors. A sample of 671 middle school teachers from Guangxi, China was utilized. The study revealed that the practice of inclusive leadership by principals had a positive effect on teacher efficacy. Furthermore, teacher efficacy appeared to have a beneficial effect on teacher innovative behavior. Additionally, the study showed that principal inclusive leadership significantly influenced teacher innovative behavior. Lastly, it proved that teacher efficacy played a mediating role in the relationship between principal inclusive leadership and teacher innovative behavior. The study offers strategies for enhancing teacher’s propensity for innovative conduct. When designing programs to promote teacher innovative behavior, it is important to take into account the impact of inclusive leadership by principals and the magnitude of teacher efficacy.
Volume: 13
Issue: 6
Page: 4338-4345
Publish at: 2024-12-01

Examining the psychometric properties of the deputy-principal mentoring questionnaire

10.11591/ijere.v13i6.29360
Roslizam Hassan , Lokman Mohd Tahir , Mohammed Borhandden Musah , Norazah Abdul Aziz , Lina Mursyidah Hamzah , Hanin Naziha Hasnor , Roslee Ahmad
This article intends to inspect and validate the Malay language version of the self-developed instrument on informal leadership mentoring used by principals with their deputy principals in the Malaysian primary school context. This article relies on the survey responses by 318 Malaysian primary deputy principals. Descriptively, the responses to all 25 items produced high mean scores which indicated that deputy principals are well-satisfied with the mentoring and guidance provided to improve their leadership prowess. Based on exploratory factor analysis, three factors emerged: guidance, informal approaches, and substituting principals in official meetings. However, the third factor was removed because it was only represented by one item. Thus, there are two major factors: guidance and informal approaches with 24 items, all of which had high factor-loading values and were consistent in their internal validity. In addition, the average variance extracted and composite reliability were also calculated which received acceptable values. Lastly, the confirmatory factor analysis (CFA) results indicated that all 24 items achieved acceptable values.
Volume: 13
Issue: 6
Page: 3923-3934
Publish at: 2024-12-01

A new approach based on genetic algorithm for computation offloading optimization in multi-access edge computing networks

10.11591/ijai.v13.i4.pp4186-4194
Marouane Myyara , Oussama Lagnfdi , Anouar Darif , Abderrazak Farchane
The proliferation of smart devices and the increasing demand for resource-intensive applications present significant challenges in terms of computational efficiency, leading to surge in data traffic. While cloud computing offers partial solutions, its centralized architecture raises concerns about latency. Multi-access edge computing (MEC) emerges as promising alternative by deploying servers at the network edge to bring computations closer to user devices. However, optimizing computation offloading in the dynamic MEC environment remains a complex challenge. This paper introduces novel genetic algorithm-based approach for efficient computation offloading in MEC, considering processing and transmission delays, user preferences, and system constraints. The proposed approach integrates computation offloading and resource allocation algorithm based on evolutionary principles, combined with a greedy strategy to maximize overall system performance. By utilizing genetic algorithms, the proposed method enables dynamic adaptation to changing conditions, eliminating the need for intricate mathematical models and providing an appealing solution to the complexities inherent in MEC. The urgency of this research arises from the critical need to enhance mobile application performance. Simulation results demonstrate the robustness and efficacy of our approach in achieving near-optimal solutions while efficiently balancing computation offloading, minimizing latency, and maximizing resource utilization. Our approach offers flexibility and adaptability, contributing to advancement of MEC networks and addressing the requirements of latency-sensitive applications.
Volume: 13
Issue: 4
Page: 4186-4194
Publish at: 2024-12-01

A comprehensive analysis of eye diseases and medical data classification

10.12928/telkomnika.v22i6.26058
Raed; Zarqa University Alazaidah , Hamza Abu; Al-Ahliyya Amman University Owida , Nawaf; Applied Science Private University Alshdaifat , Abedalhakeem; Zarqa University Issa , Suhaila; Al al-Bayt University Abuowaida , Nidal; Zarqa University Yousef
Vision loss is a critical health issue that presents substantial challenges to both individuals and communities. For those affected, it can lead to difficulties in performing daily activities, hinder educational and employment opportunities, and significantly impact mental health and overall quality of life. The inability to see can also lead to increased dependence on others, creating emotional and financial strains on families and caregivers. This paper highlights the benefit of machine learning (ML) in exploring conditions that significantly affect vision loss. The goals that will be achieved in this paper are to determine the best classifier capable of dealing with medical datasets and to determine the best strategy for dealing with medical data. Determine which feature selection is most applicable to use for examining medical data. Two medical datasets, 4 strategies, 19 classifiers, and 2 feature selections were used. As for the best classifier, the stochastic gradient descent (SGD) model was the best in dataset 1 and 2. The function strategy showed the best performance, followed by the rules strategy. CorrelationAttributeEval was shown to be the best feature selection, while ClassifierAttributeEval was the second-best feature selection.
Volume: 22
Issue: 6
Page: 1422-1430
Publish at: 2024-12-01

Machine learning prediction of quality of life: Insight from property crime and tropical climate analysis

10.11591/ijai.v13.i4.pp4509-4515
Anis Zulaikha Mohd Zukri , Siti Rasidah Md Sakip , Suraya Masrom
The study addresses the prediction of quality of life, leveraging machine learning models with a focus on health, socioeconomics, subjective well-being, and environmental indicators. Thus, this study aims to evaluate the efficacy of machine learning in quality-of-life prediction based on property crime and temperature. Five machine learning algorithms were used to be empirically compared namely generalized linear model (GLM), random forest (RF), decision tree (DT), gradient boosted tree (GBT) and support vector machine (SVM) are compared empirically. The performance of each machine learning algorithm in predicting the quality of life has been observed based on the attributes of property crime and tropical climate (temperature). Despite initial low correlation with quality of life, temperature significantly contributes to specific algorithms, enhancing predictive accuracy. This shows the complexity of machine learning impacts. SVM emerges as the best-performing algorithm, followed by RF and DT. The findings highlight the importance of seemingly unrelated factors in prediction outcomes. This paper presents a fundamental research framework useful for helping educators and researchers to explore in depth quality of life prediction with using property crime and temperature as a factor. 
Volume: 13
Issue: 4
Page: 4509-4515
Publish at: 2024-12-01

Guided imitation optimizer: a metaheuristic combining guided search and imitation search

10.11591/ijai.v13.i4.pp4217-4228
Purba Daru Kusuma , Meta Kallista
This paper proposes a novel metaphor-free metaheuristic, namely the guided imitation optimizer (GIO). This metaheuristic combines the guided search and imitation-based search. There are five guided searches and three imitation based searches. Meanwhile, there are three references used in this metaheuristic: global finest, a randomly picked solution among the swarm, and a randomized solution within the search space. GIO is then evaluated by using 23 classic functions that consist of seven high dimension unimodal functions (HDUF), six high dimension multimodal functions (HDMF), and ten fixed dimension multimodal functions (FDMF). Through simulation, GIO is superior to golden search optimizer (GSO), grey wolf optimizer (GWO), puzzle optimization algorithm (POA), and coati optimization algorithm (COA) in handling most of these functions. GIO is the first finest in tackling seventeen functions and second finest in tackling six functions. Tight competition occurs between GIO and COA due to the performance of COA which becomes the second finest in handling most of these functions.
Volume: 13
Issue: 4
Page: 4217-4228
Publish at: 2024-12-01

Flood vulnerability index to aid decision making

10.12928/telkomnika.v22i6.26272
Geeta; University of Delhi Aggarwal , Harita; University of Delhi Ahuja , Sunita; University of Delhi Narang , Seema; University of Delhi Aggarwal
Floods damage ecosystem of the affected area resulting in destruction, loss of asset and life. The paper proposes a novel k-FVI, (k stands for Kerala and FVI for flood vulnerability index) to aid the decision makers reduce flood vulnerability of 14 districts of Kerala. Instead of usual classification of flood vulnerability indicators under exposure (𝔼), sensitivity (𝕊), and adaptive capacity (𝔸ℂ), k-FVI proposes that, indicators reflecting 𝕊 and preparedness (ℙ)govern pre-flood vulnerability, whereas those of 𝔼 and rehabilitation (ℝ) affects post-flood vulnerability. The division of 𝔸ℂ indicator into ℙ and ℝ indicators and clubbing them into pre-flood and post-flood vulnerability respectively results into reduced errors. The importance of high dimensional flood indicators is realized by measuring the entropy of affected areas. Use of technique for order preference by similarity to ideal solution (TOPSIS) and entropy-based weights to score flood affected area results in formulating robust k-FVI. The paper also compares k-FVI with existing FVIs in literature. It uses data of 2018 Kerala floods and assesses the flood vulnerability of its 14 districts. The results prove that k-FVI is an effective flood vulnerability score estimator. Variant of k-FVI can be used to obtain vulnerability for any other flood prone areas.
Volume: 22
Issue: 6
Page: 1431-1442
Publish at: 2024-12-01

Evaluating metaverse platforms for educational purposes: a heuristic evaluation study

10.11591/ijaas.v13.i4.pp1023-1031
Cadelina Cassandra , Mohamad Noorman Masrek , Fadhilah Aman
This research's primary objective is to investigate the educational potential by investigating the metaverse website, emphasizing from users' perspectives. It is critical to examine the functionality to identify any potential faults in the learning experience because of the complexities of metaverse apps, which include 3D virtual environments and complex interactions. This study uses heuristic evaluation, which is a useful method for analyzing application success by utilizing well-established design principles and best practices in user interface and user experience design. To conduct this study, a panel of five experts, each with outstanding competence in the topic, was assembled to test the metaverse website in an educational setting. The evaluation was built on the ten heuristic evaluation standards, which served as a solid framework for measuring its usability and functionality. According to the findings of this examination, the average severity number of heuristic issues is one. This result indicates that the website is under "cosmetic problems only." While this implies that specific areas need to be addressed to improve overall quality, it also means that these difficulties do not take precedence over other vital ones. As a result, the website has significant promise as a metaverse instructional platform, and changes can be made to further improve its efficiency.
Volume: 13
Issue: 4
Page: 1023-1031
Publish at: 2024-12-01

Optimized multi-layer self-attention network for feature-level data fusion in emotion recognition

10.11591/ijai.v13.i4.pp4435-4444
Basamma Umesh Patil , Ashoka Davanageri Virupakshappa , Ajay Prakash Basappa Vijaya
Understanding human emotions across diverse data sources presents challenges in various applications including healthcare, human-machine interaction, security, marketing, and gaming. Prior research has explored fusion techniques to address multimodal data heterogeneity, yet often overlooks the importance of discriminative unimodal information and potential complementarity among fusion strategies. Recognizing emotions from video and audio data poses challenges such as non-verbal cues interpretation, varying expression, ambiguity in context, and the need for nuanced feature extraction to capture subtle emotional nuances accurately. To tackle these issues, it is imperative to employ efficient emotion representation and multimodal fusion techniques, as these tasks have significant importance within the realm of multifaceted recognizing study. This study introduced a novel approach, optimized multi-layer self-attention network for emotion recognition (OMSN-ER), focusing on feature-level data fusion. OMSN-ER precisely assesses emotional states by merging facial and voice data, utilizing a multi-layer progressive dense residual fusion network and a self-attention mountain gazelle convolution neural network. Implemented in Python with the RAVDESS dataset, the methodology achieves exceptional accuracy (0.9908), surpassing benchmarks and demonstrating efficacy in multimodal emotion recognition. This research represents promising advancements in the intricate field of emotion recognition.
Volume: 13
Issue: 4
Page: 4435-4444
Publish at: 2024-12-01

IR4.0 and internet of things: future directions towards enhanced connectivity, automation, and sustainable innovation

10.12928/telkomnika.v22i6.25487
Yousef A. Baker; Universitas Sultan Zainal Abidin El-Ebiary , Salameh A.; Al-Balqa Applied University (BAU) Mjlae , Hadeel; Applied Science Private University (ASPU) Ahmad , Suzie Y.; Jadara University Rababa'h , Mahmoud A.; Jadara University Rababah , Omar G.; Al-Balqa Applied University Arabiat
This study provides a systematic review of the literature on the fourth industrial revolution (IR4.0) and the internet of things (IoT) in genetics, informatics, and biotechnology, as well as their many rapidly evolving applications, which often overlap with various aspects of life. The study reviews the latest research, books, scientific theses, and official websites in this field, placing them in a coherent context for researchers. It covers innovations that have driven the continuous development of IR4.0 and its challenges. The study highlights numerous fields and modern technologies expected to bring about tangible and radical changes in health, agriculture, and industry. It addresses key aspects of IR4.0 and the significant advancements brought by smart cities, and most importantly, artificial intelligence (AI), including robots, autonomous cars, 3D printing, big data, IoT, nanotechnology, biotechnology, energy storage, and quantum computing. By applying cutting-edge technology across various disciplines to boost productivity and foster development, technology plays a crucial role in linking the physical, digital, and biological realms. This revolution is built on multiple axes, including the convergence of biotechnology, digital media, and physical systems.
Volume: 22
Issue: 6
Page: 1469-1477
Publish at: 2024-12-01

Validation of instruments on the headmaster’s technology leadership model by using confirmatory factor analysis

10.11591/ijere.v13i6.29061
Pang Lai Chaw , Mat Rahimi Yusof , Mohamad Khairi Othman
In 21st-century education, the role of school headmasters in technology leadership is increasingly crucial. This is due to the fact that administrators are the main force behind efforts to integrate technology in classrooms. Some headmasters resist technology use and lack understanding of its role in leadership, refraining from participating in Malaysian Ministry of Education (MoE) initiatives for technology change. To promote teachers’ integration of technology into the teaching process, headmasters need a comprehensive understanding of its implementation for both management and leadership purposes. Therefore, this study aims to assess the impact of headmasters’ technology leadership and confirm its aspects in primary schools through cross-sectional quantitative analysis. The principal technology leadership assessment (PTLA) instrument, which was given online to 516 teachers using a straight forward random selection method, served as the basis for the headmaster technology leadership questionnaire. Using IBM-SPSS-AMOS software, descriptive statistics, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA) were used to evaluate the data. Six dimensions and 35 items in technology leadership are approved and validated, according to CFA results. This study successfully created an assessment model for headmasters’ technology leadership. To enhance benefits, contribute more, and address identified gaps, future researchers are encouraged to conduct larger-scale studies using both qualitative and quantitative methods.
Volume: 13
Issue: 6
Page: 3717-3724
Publish at: 2024-12-01
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