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INDONESIA
Emerging Science Journal
Published by Ital Publication
ISSN : 26109182     EISSN : -     DOI : -
Core Subject : Social,
Environmental Science
Emerging Science Journal is not limited to a specific aspect of science and engineering but is instead devoted to a wide range of subfields in the engineering and sciences. While it encourages a broad spectrum of contribution in the engineering and sciences. Articles of interdisciplinary nature are particularly welcome.
Arjuna Subject : -
Articles 20 Documents
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Search results for , issue "Vol 6, No 6 (2022): December" : 20 Documents clear
Modified Weighted Mean Filter to Improve the Baseline Reduction Approach for Emotion Recognition I Made Agus Wirawan; Retantyo Wardoyo; Danang Lelono; Sri Kusrohmaniah
Emerging Science Journal Vol 6, No 6 (2022): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-06-03

Abstract

Participants' emotional reactions are strongly influenced by several factors such as personality traits, intellectual abilities, and gender. Several studies have examined the baseline reduction approach for emotion recognition using electroencephalogram signal patterns containing external and internal interferences, which prevented it from representing participants’ neutral state. Therefore, this study proposes two solutions to overcome this problem. Firstly, it offers a modified weighted mean filter method to eliminate the interference of the electroencephalogram baseline signal. Secondly, it determines an appropriate baseline reduction method to characterize emotional reactions after the smoothing process. Data collected from four scenarios conducted on three datasets was used to reduce the interference and amplitude of the electroencephalogram signals. The result showed that the smoothing process can eliminate interference and lower the signal's amplitude. Based on the three baseline reduction methods, the Relative Difference method is appropriate for characterizing emotional reactions in different electroencephalogram signal patterns and has higher accuracy. Based on testing on the DEAP dataset, these proposed methods achieved accuracies of 97.14, 99.70, and 96.70% for the four categories of emotions, the two categories of arousal, and the two categories of valence, respectively. Furthermore, on the DREAMER dataset, these proposed methods achieved accuracies of 89.71, 97.63, and 96.58% for the four categories of emotions, the two categories of arousal, and the two categories of valence, respectively. Finally, on the AMIGOS dataset, these proposed methods achieved accuracies of 99.59, 98.20, and 99.96% for the four categories of emotions, the two categories of arousal, and the two categories of valence, respectively. Doi: 10.28991/ESJ-2022-06-06-03 Full Text: PDF
Data Mining Applications in Banking Sector While Preserving Customer Privacy Özge Doğuç
Emerging Science Journal Vol 6, No 6 (2022): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-06-014

Abstract

In real-life data mining applications, organizations cooperate by using each other’s data on the same data mining task for more accurate results, although they may have different security and privacy concerns. Privacy-preserving data mining (PPDM) practices involve rules and techniques that allow parties to collaborate on data mining applications while keeping their data private. The objective of this paper is to present a number of PPDM protocols and show how PPDM can be used in data mining applications in the banking sector. For this purpose, the paper discusses homomorphic cryptosystems and secure multiparty computing. Supported by experimental analysis, the paper demonstrates that data mining tasks such as clustering and Bayesian networks (association rules) that are commonly used in the banking sector can be efficiently and securely performed. This is the first study that combines PPDM protocols with applications for banking data mining. Doi: 10.28991/ESJ-2022-06-06-014 Full Text: PDF
How does Spiritual Leadership Influences Employee Well-Being? Findings from PLS-SEM and FsQCA Chwen-Li Chang; Ivon Arisanti
Emerging Science Journal Vol 6, No 6 (2022): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-06-09

Abstract

This study aims to examine the relationship between spiritual leadership, affective commitment, work engagement, and employee well-being. In this test, the hypotheses of 356 public sector employees through Partial Least Squares-Structural Equation Modeling (PLS-SEM) and fuzzy set Qualitative Comparative Analysis (fsQCA). PLS-SEM results show that spiritual leadership affects affective commitment, work engagement, and employee well-being and shows that affective commitment and work engagement have different effects because of parallel mediation with spiritual leadership in improving employee well-being. The results of the FsQCA provide theoretical insights and practical recommendations on how to improve understanding of spiritual leadership, affective commitment, work engagement, and employee well-being. This research has implications for policymakers, especially in the public sector, to support and develop spiritual practices that can help employees improve employee well-being through affective commitment and work engagement. In addition, this research can help organizations improve the performance of individuals in organizations, especially public organizations, to make positive contributions to society at large. Doi: 10.28991/ESJ-2022-06-06-09 Full Text: PDF
The Effect of Digitalization on the Quality of Service and Customer Loyalty Lulzim Shabani; Arbëresha Behluli; Fidan Qerimi; Fellanze Pula; Pranvera Dalloshi
Emerging Science Journal Vol 6, No 6 (2022): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-06-04

Abstract

This research aims to measure the effect of digitalization on service quality through the SERVQUAL model (tangibility, reliability, responsiveness, assurance, and empathy) and customer loyalty. Also, we analyze the relationship between customer loyalty and their demographics. A quantitative method was used to achieve the objectives through a structured questionnaire, where part of the research sample was 400 clients of Kosovo banks. Results show that digitalization positively affects service quality and customer loyalty based on the OLS model. According to the T-test, there was no significant difference in customer loyalty between the genders. There has been a significant difference in loyalty between clients’ ages following the one-way ANOVA test. According to the Kruskal Wallis test, it also resulted in a significant difference between levels of education. This study will provide banks with feedback on the importance of digitalization and its correlation with their customers’ quality of service and loyalty. In this form, they decide to make even greater investments in digitalization by satisfying customer demands and creating loyal customers. Doi: 10.28991/ESJ-2022-06-06-04 Full Text: PDF
Optimization of Markov Weighted Fuzzy Time Series Forecasting Using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) Sugiyarto Surono; Khang Wen Goh; Choo Wou Onn; Afif Nurraihan; Nauval Satriani Siregar; A. Borumand Saeid; Tommy Tanu Wijaya
Emerging Science Journal Vol 6, No 6 (2022): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-06-010

Abstract

The Markov Weighted Fuzzy Time Series (MWFTS) is a method for making predictions based on developing a fuzzy time series (FTS) algorithm. The MWTS has overcome certain limitations of FTS, such as repetition of fuzzy logic relationships and weight considerations of fuzzy logic relationships. The main challenge of the MWFTS method is the absence of standardized rules for determining partition intervals. This study compares the MWFTS model to the partition methods Genetic Algorithm-Fuzzy K-Medoids clustering (GA-FKM) and Fuzzy K-Medoids clustering-Particle Swarm Optimization (FKM-PSO) to solve the problem of determining the partition interval and develop an algorithm. Optimal partition optimization. The GA optimization algorithm’s performance on GA-FKM depends on optimizing the clustering of FKM to obtain the most significant partition interval. Implementing the PSO optimization algorithm on FKM-PSO involves maximizing the interval length following the FKM procedure. The proposed method was applied to Anand Vihar, India’s air quality data. The MWFTS method combined with the GA-FKM partitioning method reduced the mean absolute square error (MAPE) from 17.440 to 16.85%. While the results of forecasting using the MWFTS method in conjunction with the FKM-PSO partition method were able to reduce the MAPE percentage from 9.78% to 7.58%, the MAPE percentage was still 9.78%. Initially, the root mean square error (RMSE) score for the GA-FKM partitioning technique was 48,179 to 47,01. After applying the FKM-PSO method, the initial RMSE score of 30,638 was reduced to 24,863. Doi: 10.28991/ESJ-2022-06-06-010 Full Text: PDF
Ensuring Healthcare Efficiency in the Context of the Medical and Pharmaceutical Staff Regulation Guzal G. Galiakbarova; Yenlik N. Nurgaliyeva; Elmira B. Omarova; Svetlana B. Zharkenova; Muslim K. Khassenov
Emerging Science Journal Vol 6, No 6 (2022): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-06-05

Abstract

This article aims to substantiate the impact of socio-economic labor protection for healthcare professionals based on developing legislative regulations in some OECD and EAEU countries and identifying their relationship with the efficiency of healthcare systems. The methodology includes general scientific methods (systemic analysis, synthesis, comparison, abstraction, induction, deduction, and modeling) and special research methods (formal logical, structural, and functional). The results of international rankings evaluating healthcare systems were used to determine the list of states for comparative legal analysis. Also, empirical methods were used: meetings, questionnaire surveys, and interviews held in 2021 with medical and pharmaceutical workers in Kazakhstan. The research results showed that states with special labor regulations for medical and pharmaceutical personnel occupy stable leading positions in international rankings regarding healthcare evaluation. On the other hand, based on the example of the EAEU countries with an insufficient level of specialization in labor regulation for these categories of workers, some states occupy weak positions in similar international ratings. This paper is novel because previously, there was no debate in the literature justifying the finding that specifics in the labor regulation of medical and pharmaceutical staff, along with other factors, influence the healthcare system's efficiency and development. Doi: 10.28991/ESJ-2022-06-06-05 Full Text: PDF
Examining the Key Factors that Drives Live Stream Shopping Behavior Sudaporn Sawmong
Emerging Science Journal Vol 6, No 6 (2022): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-06-011

Abstract

The purpose of this research was to examine the key factors that drive live-stream shopping behavior in Thailand. The specific objective was to determine the live stream shopping factors that influence purchase intention. The study was driven by the increasing role of e-commerce and live streaming shopping trends through social media marketing. For marketers, live-stream shopping is considered a valuable marketing strategy for commercial businesses to enhance sales, save expenses, and create unique marketing impacts. The study adopted the Uses and Gratification Theory and the Source Credibility Theory. Through these theories, the variables of the study were considered to be entertainment, informativeness, attractiveness, expertise, trustworthiness, culture, and purchase intention. A quantitative research methodology was adopted, with primary data collected from 370 respondents. The model was evaluated using reliability, validity, and CFA. SEM was used to analyse the hypotheses using AMOS and SPSS software. The results of the study indicated that four factors (entertainment, informativeness, expertise, and trustworthiness) have a significant and positive effect on purchase intention. Trustworthiness and entertainment had the highest effect. Attractiveness was found not to influence purchase intention, while culture did not moderate the effect of any variable on purchase intention. The research recommended that live streaming should be trustworthy in terms of sincerity, non-exaggeration, correct information, correct thoughts, and opinions. They should also be entertaining to establish positive interconnectivity between the user and the product or service, and also informative to contribute towards awareness of a product/service and offer insights that influence perceptions and behavioral intentions. Doi: 10.28991/ESJ-2022-06-06-011 Full Text: PDF
Development of a Technique for the Spectral Description of Curves of Complex Shape for Problems of Object Classification Aslan Tatarkanov; Islam Alexandrov; Alexander Muranov; Abas Lampezhev
Emerging Science Journal Vol 6, No 6 (2022): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-06-015

Abstract

Vascular pathology symptoms can be determined by retinal image segmentation and classification. However, the retinal images from non-invasive diagnostics have a complex structure containing tree-like vascular beds, multiple segment boundaries, false segments, and various distortions. It should be noted that complex structure images’ segmentation does not always provide a single solution. Thus, the goal is to increase the efficiency of vascular diagnostics. This study aims to develop a technique for describing the geometric properties of complexly structured image segments used for classifying vascular pathologies based on retinal images. The advantages and disadvantages of the existing methods and algorithms of segmentation were considered. The most effective use areas of the mentioned methods and algorithms are revealed. Through detecting retinal thrombosis, the algorithm's efficiency for constructing a mathematical model of an arbitrary shape segment based on the morphological processing of binary and halftone images was justified. A modified variant of this algorithm based on the spectral analysis procedure of arbitrary shape boundary curves was used for the spectral description of complex shape curves for classifying vascular pathologies based on retinal images. Two approaches have been developed. The first one allows obtaining a closing segment of the curve from a symmetric mapping of the initial parametric curves. The second involves intelligent data processing and obtaining contours of minimum thickness, forming convex sets. The results of experiments confirm the possibility of practical use of the developed technique to solve problems of vascular pathology classification based on retinal images, showing the correct forecast probability was 0.93 with all associated risk factors. Doi: 10.28991/ESJ-2022-06-06-015 Full Text: PDF
Microstrip Patch Antenna with C Slot for 5G Communication at 30 GHz Siddharth Kishore; A. R. Abdul Rajak
Emerging Science Journal Vol 6, No 6 (2022): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-06-06

Abstract

A novel design of a 30 GHz microstrip line-fed antenna for 5G communication has been presented in this paper. 5G is the latest industry standard in mobile communication, which is designed to deliver higher data speeds, lower latency, greater network capacity, and higher reliability. It uses major parts of the mmWave spectrum (28 GHz to 40 GHz), allowing for a wide range of applications like mobiles, vehicles, medical devices, and other IoT networks. This mmWave network requires efficient antennas for its effective communication. Patch antennas use the function of oscillating their physical structure to the wavelength of the transmitting wave. Thus, higher efficiency can be achieved in the mmWave spectrum due to its proximity to the actual dimensions of the patch antenna, which also allows us to design antennas at small sizes and high reliability. The design in this report has a patch antenna with a centre frequency of 30 GHz. The antenna was optimized for this frequency based on the best reflection coefficient and gain while keeping the restraints of staying within the FR-2 band of 28 GHz to 33 GHz. The proposed antenna has been implemented using Rogers RT5880 substrate for high gain and performance across a wide range of frequencies. The feed is also accompanied by a quarter-wave feed cut for performance increase and impedance matching. The design has a gain of 8.45, with a reflection coefficient of -8 dB at a resonant frequency of 30 GHz. It shows great directivity of 5o and VSWR of 2.3 over a bandwidth of 3.5 GHz. It also employs a 0.4 mm C slot, which induces a dipole effect, thereby increasing the directivity and gain of the antenna. Hence, it is recommended for use in applications related to 5G mobile communication. Doi: 10.28991/ESJ-2022-06-06-06 Full Text: PDF
Public Perceptions on Application Areas and Adoption Challenges of AI in Urban Services Tan Yigitcanlar; Rita Yi Man Li; Tommi Inkinen; Alexander Paz
Emerging Science Journal Vol 6, No 6 (2022): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2022-06-06-01

Abstract

Artificial intelligence (AI) deployment is exceedingly relevant to local governments, for example, in planning and delivering urban services. AI adoption in urban services, however, is an understudied area, particularly because there is limited knowledge and hence a research gap on the public's perceptions-users/receivers of these services. This study aims to examine people’s behaviors and preferences regarding the most suited urban services for application of AI technology and the challenges for governments to adopt AI for urban service delivery. The methodological approach includes data collection through an online survey from Australia and Hong Kong and statistical analysis of the data through binary logistic regression modeling. The study finds that: (a) Attitudes toward AI applications and ease of use have significant effects on forming an opinion on AI; (b) initial thoughts regarding the meaning of AI have a significant impact on AI application areas and adoption challenges; (c) perception differences between the two countries in AI application areas are significant; and (d) perception differences between the two countries in government AI adoption challenges are minimal. The study consolidates our understanding of how the public perceives the application areas and adoption challenges of AI, particularly in urban services, which informs local authorities that deploy or plan to adopt AI in their urban services. Doi: 10.28991/ESJ-2022-06-06-01 Full Text: PDF

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