Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459355
Rifqy Muhammad Alfian, K. Lhaksmana
Machine learning methods have been implemented to perform prediction and classification tasks across various domain due to their superior time and cost efficiency compared to human expertise. This research employs such methods to predict student work readiness, which result is beneficial to assist universities to profile students and design career preparation programs tailored to their readiness level. The methods utilized in this research include Decision Tree and KNearest Neighborhood (KNN) classifiers. The confusion matrix demonstrates the applicability of these methods in predicting student work readiness. The KNN model, with k = 9, achieves accuracy of 97.50%, 96.90%, 96.80%, 97.60%, 95.80%, 97.00%, and 97.20%. On the other hand, the Decision Tree model achieves 98.60%, 98.80%, 98.90%, 98.70%, 98.60%, 98.70%, and 99.50%. Therefore, based on the given dataset of 6823 students, the Decision Tree model slightly outperforms KNN in predicting student work readiness.
{"title":"Classification of Student Work Readiness Using the Decision Tree and KNN Methods","authors":"Rifqy Muhammad Alfian, K. Lhaksmana","doi":"10.1109/ICETSIS61505.2024.10459355","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459355","url":null,"abstract":"Machine learning methods have been implemented to perform prediction and classification tasks across various domain due to their superior time and cost efficiency compared to human expertise. This research employs such methods to predict student work readiness, which result is beneficial to assist universities to profile students and design career preparation programs tailored to their readiness level. The methods utilized in this research include Decision Tree and KNearest Neighborhood (KNN) classifiers. The confusion matrix demonstrates the applicability of these methods in predicting student work readiness. The KNN model, with k = 9, achieves accuracy of 97.50%, 96.90%, 96.80%, 97.60%, 95.80%, 97.00%, and 97.20%. On the other hand, the Decision Tree model achieves 98.60%, 98.80%, 98.90%, 98.70%, 98.60%, 98.70%, and 99.50%. Therefore, based on the given dataset of 6823 students, the Decision Tree model slightly outperforms KNN in predicting student work readiness.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"400 5","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459644
Yasrin Zabidi, R. Pirdaus, Uyuunul Mauidzoh, Gunawan, M. Astuti, Riani Nurdin
Aircraft Replica SMEs have never known the level of productivity achieved because they have not carried out productivity measurements and analysis. This study aims to determine the level of productivity, the factors causing the decline in productivity, and provide suggestions for corrective actions. The methods used are OMAX and fishbone diagrams. There are five productivity ratios used. Ratios 1 and 4 are dominated by a very large number of bad productivity ratios. The lowest total productivity achievement occurred in July at 0, while the highest total productivity achievement occurred in February at 601.13. The index value of change in the achievement of total productivity to the best standard productivity occurred in February at 100.38%, while the worst value occurred in July at -100%. The best index value of changes to productivity in the previous period occurred in August at 395.15%, while the worst value occurred in July at - 100%. Corrective actions include optimizing rest hours so that at work they can concentrate even more, optimizing working hours so that no working hours are wasted, increasing the comfort of the workplace, optimizing all employees so that the results obtained can also be optimal, ensuring that production results achieved are always controlled, and motivating employees by giving bonuses to employees who perform well.
{"title":"Productivity Analysis Using the Objective Matrix and Fishbone Diagram Methods in SMEs of Airplane Replicas","authors":"Yasrin Zabidi, R. Pirdaus, Uyuunul Mauidzoh, Gunawan, M. Astuti, Riani Nurdin","doi":"10.1109/ICETSIS61505.2024.10459644","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459644","url":null,"abstract":"Aircraft Replica SMEs have never known the level of productivity achieved because they have not carried out productivity measurements and analysis. This study aims to determine the level of productivity, the factors causing the decline in productivity, and provide suggestions for corrective actions. The methods used are OMAX and fishbone diagrams. There are five productivity ratios used. Ratios 1 and 4 are dominated by a very large number of bad productivity ratios. The lowest total productivity achievement occurred in July at 0, while the highest total productivity achievement occurred in February at 601.13. The index value of change in the achievement of total productivity to the best standard productivity occurred in February at 100.38%, while the worst value occurred in July at -100%. The best index value of changes to productivity in the previous period occurred in August at 395.15%, while the worst value occurred in July at - 100%. Corrective actions include optimizing rest hours so that at work they can concentrate even more, optimizing working hours so that no working hours are wasted, increasing the comfort of the workplace, optimizing all employees so that the results obtained can also be optimal, ensuring that production results achieved are always controlled, and motivating employees by giving bonuses to employees who perform well.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"24 1","pages":"904-907"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459635
Karan Dorge, Deepika Pandita
In the era of modernization, digital solutions come to our aid providing economical, ecological and smart solutions over a wide array of domains. The authors have developed an e-assessment system named as QuizopediaPlus for visually impaired students. This paper describes in detail the design, development and functionality of QuizopediaPlus, a quiz platform focused towards users with visual impairment. The platform is focused on enabling the visually impaired users to attempt quizzes seamlessly, efficiently and independently on a web portal; fueling empowerment and independence during the process. This research provides a viable platform for conducting quizzes and tests. Focused towards students with visual impairment, the platform provides quizzing features and facilities for the visually impaired as well as the normal users.
{"title":"Leveraging Scalable Digital Platforms for E-Assessment of Visually Impaired Students","authors":"Karan Dorge, Deepika Pandita","doi":"10.1109/ICETSIS61505.2024.10459635","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459635","url":null,"abstract":"In the era of modernization, digital solutions come to our aid providing economical, ecological and smart solutions over a wide array of domains. The authors have developed an e-assessment system named as QuizopediaPlus for visually impaired students. This paper describes in detail the design, development and functionality of QuizopediaPlus, a quiz platform focused towards users with visual impairment. The platform is focused on enabling the visually impaired users to attempt quizzes seamlessly, efficiently and independently on a web portal; fueling empowerment and independence during the process. This research provides a viable platform for conducting quizzes and tests. Focused towards students with visual impairment, the platform provides quizzing features and facilities for the visually impaired as well as the normal users.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"382 5","pages":"1113-1116"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459373
Samer Shorman, Uday Al jubori, Mohamed Soltan
Employability skills are the fundamental competencies that help people succeed in their job and increase their employability. They are often referred to as soft skills or transferable talents. Employers place high importance on a variety of interpersonal, communication, problem-solving, and adaptability abilities that go beyond technical knowledge and credentials. Communication, teamwork, critical thinking, problem-solving, flexibility, time management, digital literacy, leadership, and professionalism are important employability skills. These abilities allow people to manage their time and resources, use technology, efficiently communicate with others, assess complex circumstances, make educated judgments, adjust to new obstacles, and work with professionalism. A combination of formal education, hands-on learning, professional development programs, internships, and ongoing self-improvement can help increase employable skills. The development and integration of these abilities into curriculum, employment settings, and training efforts are greatly aided by the cooperation of businesses, policymakers, and educational institutions. The employability skills for computer science, interior design, and graphic design will be reviewed in this article in order to highlight the most frequently needed abilities for those disciplines.
{"title":"Employability Skills in Computer Science, Interior Design, and Graphic Design","authors":"Samer Shorman, Uday Al jubori, Mohamed Soltan","doi":"10.1109/ICETSIS61505.2024.10459373","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459373","url":null,"abstract":"Employability skills are the fundamental competencies that help people succeed in their job and increase their employability. They are often referred to as soft skills or transferable talents. Employers place high importance on a variety of interpersonal, communication, problem-solving, and adaptability abilities that go beyond technical knowledge and credentials. Communication, teamwork, critical thinking, problem-solving, flexibility, time management, digital literacy, leadership, and professionalism are important employability skills. These abilities allow people to manage their time and resources, use technology, efficiently communicate with others, assess complex circumstances, make educated judgments, adjust to new obstacles, and work with professionalism. A combination of formal education, hands-on learning, professional development programs, internships, and ongoing self-improvement can help increase employable skills. The development and integration of these abilities into curriculum, employment settings, and training efforts are greatly aided by the cooperation of businesses, policymakers, and educational institutions. The employability skills for computer science, interior design, and graphic design will be reviewed in this article in order to highlight the most frequently needed abilities for those disciplines.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"100 9-10","pages":"375-380"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459362
Dewi Maharani, Hanny Juwitasary, Desman Hidayat
This study investigates the transformative impact of digitalization, with a particular focus on emerging digital banking in Indonesia. Amidst a landscape populated by digital banking brands such as Allobank, Blu, Jenius, Neobank, and TMRW, this research reveals distinct differences in their strategies for effectively attracting and retaining customers. Notably, two of the leading digital banks use a spectrum of gamification elements such as badges, levels, challenges, quests, social graphs, and virtual goods. However, a noteworthy aspect, the point system, remains unexplored. Through a quantitative approach involving an online questionnaire distributed to XYZ digital bank users and analyzed with SEM-PLS, this study explores the effect of hedonic, utilitarian, and social aspects of point system gamification on customer engagement and loyalty. The findings indicate a weak but significant positive relationship between the hedonic and social value of XYZ digital bank point system and customer engagement, while the utilitarian value shows a weak and insignificant negative relationship. Most importantly, customer engagement emerged as a powerful and positively significant driver of customer loyalty. Thus, XYZ digital bank is advised to prioritize enhancing the hedonic value, followed by the social value, in their customer engagement strategies, considering alternative avenues beyond the point system gamification to fortify customer loyalty.
{"title":"Point System in Digital Bank: Is It the Key to Successful Customer Engagement and Loyalty?","authors":"Dewi Maharani, Hanny Juwitasary, Desman Hidayat","doi":"10.1109/ICETSIS61505.2024.10459362","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459362","url":null,"abstract":"This study investigates the transformative impact of digitalization, with a particular focus on emerging digital banking in Indonesia. Amidst a landscape populated by digital banking brands such as Allobank, Blu, Jenius, Neobank, and TMRW, this research reveals distinct differences in their strategies for effectively attracting and retaining customers. Notably, two of the leading digital banks use a spectrum of gamification elements such as badges, levels, challenges, quests, social graphs, and virtual goods. However, a noteworthy aspect, the point system, remains unexplored. Through a quantitative approach involving an online questionnaire distributed to XYZ digital bank users and analyzed with SEM-PLS, this study explores the effect of hedonic, utilitarian, and social aspects of point system gamification on customer engagement and loyalty. The findings indicate a weak but significant positive relationship between the hedonic and social value of XYZ digital bank point system and customer engagement, while the utilitarian value shows a weak and insignificant negative relationship. Most importantly, customer engagement emerged as a powerful and positively significant driver of customer loyalty. Thus, XYZ digital bank is advised to prioritize enhancing the hedonic value, followed by the social value, in their customer engagement strategies, considering alternative avenues beyond the point system gamification to fortify customer loyalty.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"45 2","pages":"1154-1158"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459689
Wisdom Kalabeke, Lan Thi Phuong Nguyen
Ponzi Schemes represent deceptive online investment platforms that allure potential victims with exceptionally high returns. These schemes have inflicted significant financial losses on victims, leading to adverse repercussions on financial systems, especially in developing nations. Although victims may recognize signs of a Ponzi scheme, they often succumb to the allure of quick wealth, investing their money with the hope of substantial returns. This study investigated the correlation between the Get-Rich-Quick syndrome, risk appetite, financial knowledge, and investment intentions in Ponzi schemes in Nigeria. Using a structured questionnaire with simple random sampling, data was gathered from 368 past and current Ponzi scheme investors across Nigeria's six geopolitical zones. The results of Spearman rank correlation analysis indicate a strong positive correlation coefficient of 0.825 between the Get-Rich-Quick syndrome and investment intentions in Ponzi schemes. Conversely, there is a weak -0.198 negative relationships between the Get-Rich-Quick syndrome and risk appetite. Surprisingly, individual financial knowledge shows no significant correlation with Ponzi scheme investment intentions. The study concludes that Ponzi schemes may persist in Nigeria due to the prevalence of the Get-Rich-Quick syndrome, emphasizing the need for urgent economic development initiatives and policies encouraging legitimate business activities among young adults.
{"title":"Get-Rich-Quick Syndrome and Ponzi Scheme Investment Intention","authors":"Wisdom Kalabeke, Lan Thi Phuong Nguyen","doi":"10.1109/ICETSIS61505.2024.10459689","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459689","url":null,"abstract":"Ponzi Schemes represent deceptive online investment platforms that allure potential victims with exceptionally high returns. These schemes have inflicted significant financial losses on victims, leading to adverse repercussions on financial systems, especially in developing nations. Although victims may recognize signs of a Ponzi scheme, they often succumb to the allure of quick wealth, investing their money with the hope of substantial returns. This study investigated the correlation between the Get-Rich-Quick syndrome, risk appetite, financial knowledge, and investment intentions in Ponzi schemes in Nigeria. Using a structured questionnaire with simple random sampling, data was gathered from 368 past and current Ponzi scheme investors across Nigeria's six geopolitical zones. The results of Spearman rank correlation analysis indicate a strong positive correlation coefficient of 0.825 between the Get-Rich-Quick syndrome and investment intentions in Ponzi schemes. Conversely, there is a weak -0.198 negative relationships between the Get-Rich-Quick syndrome and risk appetite. Surprisingly, individual financial knowledge shows no significant correlation with Ponzi scheme investment intentions. The study concludes that Ponzi schemes may persist in Nigeria due to the prevalence of the Get-Rich-Quick syndrome, emphasizing the need for urgent economic development initiatives and policies encouraging legitimate business activities among young adults.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"411 29","pages":"1934-1939"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459621
Sanaa Mehnaz Baichoo, Raed Abdulla, Muhammad Ehsan Rana
This research comprises the implementation methods used to design and develop a human detection system and goods control system. The development of the TensorFlow Machine Learning algorithm for human detection is described in this work. The use of IoT devices, namely ESP32 CAM for data capture, ESP32 for controlling the overall system, and establishing Firebase Database for communication between the TensorFlow development platform, PyCharm, and ESP32 are explained and justified in this paper. The development of the goods control system using ultrasonic sensors and ESP32 as a micro controller, to control the stepper motor, is also explained and justified. Each system was tested individually first before integrating them. Five tests were performed, namely the response time to activate the stepper motor, the human detection accuracy test, the precision of the ultrasonic sensor responsible for height control, the precision of the ultrasonic sensor responsible for motion control, and the stress analysis test of goods lift. The tests present coherent data, but limitations were still found during the testing phase and had to be readjusted before the final integration of both systems.
{"title":"Integrated Systems Development: Human Detection and Goods Control with TensorFlow and IoT","authors":"Sanaa Mehnaz Baichoo, Raed Abdulla, Muhammad Ehsan Rana","doi":"10.1109/ICETSIS61505.2024.10459621","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459621","url":null,"abstract":"This research comprises the implementation methods used to design and develop a human detection system and goods control system. The development of the TensorFlow Machine Learning algorithm for human detection is described in this work. The use of IoT devices, namely ESP32 CAM for data capture, ESP32 for controlling the overall system, and establishing Firebase Database for communication between the TensorFlow development platform, PyCharm, and ESP32 are explained and justified in this paper. The development of the goods control system using ultrasonic sensors and ESP32 as a micro controller, to control the stepper motor, is also explained and justified. Each system was tested individually first before integrating them. Five tests were performed, namely the response time to activate the stepper motor, the human detection accuracy test, the precision of the ultrasonic sensor responsible for height control, the precision of the ultrasonic sensor responsible for motion control, and the stress analysis test of goods lift. The tests present coherent data, but limitations were still found during the testing phase and had to be readjusted before the final integration of both systems.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"322 1","pages":"553-558"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459452
Maryam Abdullah AL-Barrak, A. Al-Alawi
In today's competitive market, companies seek to give the most excellent customer service experience to retain customers. Sentiment analysis of customer reviews may help. Organizations may realize consumers' expectations, preferences, and negative feedback with this method. Understanding consumer expectations helps to improve the goods, services, and the purchase experience, which in turn increases sales. Client satisfaction depends on sentiment analysis. Offering exceptional customer service helps companies resolve consumer concerns proactively and gain a competitive advantage. A thorough literature review of 10 papers explored how sentiment analysis influences customer loyalty, and decision-making reveals sentiment analysis and its impacts on decision-making. The research showed that sentiment analysis is essential for customer satisfaction, feedback analysis, and brand loyalty prediction. Businesses may enhance their income by knowing customer needs. The work improves our understanding of sentiment analysis in decision-making but also has limitations. More research is required to fill knowledge gaps and validate sentiment analysis across decision-making stages and components. Customers' sentiment and decision-making impact necessitate sentiment analysis. Effective utilization of which may increase customer loyalty, satisfaction, and experience. Research should expand its use across industries and customize methods. Sentiment analysis boosts economic performance, customer involvement, and decision-making.
{"title":"Sentiment Analysis on Customer Feedback for Improved Decision Making: A Literature Review","authors":"Maryam Abdullah AL-Barrak, A. Al-Alawi","doi":"10.1109/ICETSIS61505.2024.10459452","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459452","url":null,"abstract":"In today's competitive market, companies seek to give the most excellent customer service experience to retain customers. Sentiment analysis of customer reviews may help. Organizations may realize consumers' expectations, preferences, and negative feedback with this method. Understanding consumer expectations helps to improve the goods, services, and the purchase experience, which in turn increases sales. Client satisfaction depends on sentiment analysis. Offering exceptional customer service helps companies resolve consumer concerns proactively and gain a competitive advantage. A thorough literature review of 10 papers explored how sentiment analysis influences customer loyalty, and decision-making reveals sentiment analysis and its impacts on decision-making. The research showed that sentiment analysis is essential for customer satisfaction, feedback analysis, and brand loyalty prediction. Businesses may enhance their income by knowing customer needs. The work improves our understanding of sentiment analysis in decision-making but also has limitations. More research is required to fill knowledge gaps and validate sentiment analysis across decision-making stages and components. Customers' sentiment and decision-making impact necessitate sentiment analysis. Effective utilization of which may increase customer loyalty, satisfaction, and experience. Research should expand its use across industries and customize methods. Sentiment analysis boosts economic performance, customer involvement, and decision-making.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"187 5","pages":"207-212"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459424
Muhamad Farhan Wirasantoso, Hasmawati, I. Kurniawan
One of significant parameters of Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) is Human Oral Bioavailability (HOB) which is crucial for determining the total of consumed drugs inside humans body circulation. Poor HOB results in undeterminable drug effects in the human body, with approximately 50% of drug candidates failing due to low oral availability. As many as 80% of drugs in the world use the oral route of entry into the body, so HOB prediction is very important to reduce side effects and the risk of toxicity brought by drugs. Unfortunately, oral bioavailability is currently predominantly measured in vivo consequently, developing in-silico methods is considered crucial. To reckon the human oral bioavailability of medication candidates, we used the Hybrid Bat Algorithm method for feature selection and the Ensemble method, i.e. Random Forest, AdaBoost, and XGBoost for the prediction model. The result showed that XGBoost as the best model in which the value of accuracy and Fl-score were 0.776, and 0.802, respectively.
{"title":"Implementation of Hybrid Bat Algorithm-Ensemble on Human Oral Bioavailability Prediction of Drug Candidate","authors":"Muhamad Farhan Wirasantoso, Hasmawati, I. Kurniawan","doi":"10.1109/ICETSIS61505.2024.10459424","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459424","url":null,"abstract":"One of significant parameters of Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) is Human Oral Bioavailability (HOB) which is crucial for determining the total of consumed drugs inside humans body circulation. Poor HOB results in undeterminable drug effects in the human body, with approximately 50% of drug candidates failing due to low oral availability. As many as 80% of drugs in the world use the oral route of entry into the body, so HOB prediction is very important to reduce side effects and the risk of toxicity brought by drugs. Unfortunately, oral bioavailability is currently predominantly measured in vivo consequently, developing in-silico methods is considered crucial. To reckon the human oral bioavailability of medication candidates, we used the Hybrid Bat Algorithm method for feature selection and the Ensemble method, i.e. Random Forest, AdaBoost, and XGBoost for the prediction model. The result showed that XGBoost as the best model in which the value of accuracy and Fl-score were 0.776, and 0.802, respectively.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"3 1","pages":"1663-1667"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-28DOI: 10.1109/ICETSIS61505.2024.10459458
Jie Sh'ng Yeow, Muhammad Ehsan Rana, Nur Amira Abdul Majid
While the potential of AI in software development is undeniable, integrating advanced models like GPT-3.5 into its core processes like requirements engineering remains largely unexplored. This research investigates the effectiveness of GPT-3.5 in automating key tasks within software requirements engineering. The primary objective is to comprehensively explore the capabilities, limitations, and potential applications of GPT-3.5 in software requirements engineering. Subsequently, the research undergoes thorough analysis and evaluation to gather insights into the strengths and limitations of GPT-3.5 in the requirement-gathering process. The research concludes by identifying the limitations and putting forth recommendations for future research endeavours aimed at integrating GPT-3.5 into software requirement engineering processes. While GPT-3.5 demonstrates proficiency in aspects like creative prototyping and question generation, limitations in areas like domain understanding and context awareness become evident. By outlining these limitations, the authors offer concrete recommendations for future research focusing on the seamless integration of GPT-3.5 and similar models into the broader framework of software requirements engineering.
{"title":"An Automated Model of Software Requirement Engineering Using GPT-3.5","authors":"Jie Sh'ng Yeow, Muhammad Ehsan Rana, Nur Amira Abdul Majid","doi":"10.1109/ICETSIS61505.2024.10459458","DOIUrl":"https://doi.org/10.1109/ICETSIS61505.2024.10459458","url":null,"abstract":"While the potential of AI in software development is undeniable, integrating advanced models like GPT-3.5 into its core processes like requirements engineering remains largely unexplored. This research investigates the effectiveness of GPT-3.5 in automating key tasks within software requirements engineering. The primary objective is to comprehensively explore the capabilities, limitations, and potential applications of GPT-3.5 in software requirements engineering. Subsequently, the research undergoes thorough analysis and evaluation to gather insights into the strengths and limitations of GPT-3.5 in the requirement-gathering process. The research concludes by identifying the limitations and putting forth recommendations for future research endeavours aimed at integrating GPT-3.5 into software requirement engineering processes. While GPT-3.5 demonstrates proficiency in aspects like creative prototyping and question generation, limitations in areas like domain understanding and context awareness become evident. By outlining these limitations, the authors offer concrete recommendations for future research focusing on the seamless integration of GPT-3.5 and similar models into the broader framework of software requirements engineering.","PeriodicalId":518932,"journal":{"name":"2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS)","volume":"50 6","pages":"1746-1755"},"PeriodicalIF":0.0,"publicationDate":"2024-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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