AI is transforming many fields, including higher education. The pandemic has shown how AI can improve learning and teaching in higher education. This review examines how AI affects education quality, learning assessment, and higher education jobs (HE). The study employs a systematic qualitative method to review the academic literature on AI and higher education between 1900 and 2021. The data was gathered from various sources, including ERIC, Scopus, and the Web of Science, using specific exclusion and inclusion criteria centred on publication date, language, reported outcomes, setting, and publication type. From there on, the articles were analysed by Rayyan Software and categorised in Excel according to a scale that included aspects such as the quality of learning and teaching, assessment, and potential ethical future careers. The research also produced two bibliometric figures using VOSviewer to investigate co-authorship and the frequency of keyword occurrences in academic journals published in AI and HE. The analysis was done to ensure the study's validity in the scientific community. The study found that AI can improve education quality, provide practical learning and teaching methods, and improve assessments to better prepare students for careers. The study also emphasises the potential of AI to shape future employment opportunities and the need for higher education institutions to adopt AI to meet market demands. The study calls for more research on AI's effects on assessment, integrity, and higher education careers.
人工智能正在改变许多领域，包括高等教育。这场大流行显示了人工智能如何改善高等教育的学习和教学。这篇综述探讨了人工智能如何影响教育质量、学习评估和高等教育工作(HE)。本研究采用系统的定性方法，回顾了1900年至2021年间人工智能与高等教育的学术文献。数据从各种来源收集，包括ERIC、Scopus和Web of Science，采用以出版日期、语言、报告结果、环境和出版类型为中心的特定排除和纳入标准。从那时起，Rayyan Software对这些文章进行了分析，并根据包括学习和教学质量、评估和潜在的道德未来职业等方面的量表在Excel中进行了分类。该研究还使用VOSviewer生成了两个文献计量数据，以调查人工智能和高等教育领域发表的学术期刊上的共同作者身份和关键词出现频率。进行分析是为了确保研究在科学界的有效性。该研究发现，人工智能可以提高教育质量，提供实用的学习和教学方法，并改进评估，以更好地为学生的职业生涯做好准备。该研究还强调了人工智能在塑造未来就业机会方面的潜力，以及高等教育机构采用人工智能来满足市场需求的必要性。该研究呼吁对人工智能对评估、诚信和高等教育职业的影响进行更多研究。
{"title":"Systematic Review: AI's Impact on Higher Education - Learning, Teaching, and Career Opportunities","authors":"Zouhaier Slimi, Beatriz Villarejo Carballido","doi":"10.18421/tem123-44","DOIUrl":"https://doi.org/10.18421/tem123-44","url":null,"abstract":"AI is transforming many fields, including higher education. The pandemic has shown how AI can improve learning and teaching in higher education. This review examines how AI affects education quality, learning assessment, and higher education jobs (HE). The study employs a systematic qualitative method to review the academic literature on AI and higher education between 1900 and 2021. The data was gathered from various sources, including ERIC, Scopus, and the Web of Science, using specific exclusion and inclusion criteria centred on publication date, language, reported outcomes, setting, and publication type. From there on, the articles were analysed by Rayyan Software and categorised in Excel according to a scale that included aspects such as the quality of learning and teaching, assessment, and potential ethical future careers. The research also produced two bibliometric figures using VOSviewer to investigate co-authorship and the frequency of keyword occurrences in academic journals published in AI and HE. The analysis was done to ensure the study's validity in the scientific community. The study found that AI can improve education quality, provide practical learning and teaching methods, and improve assessments to better prepare students for careers. The study also emphasises the potential of AI to shape future employment opportunities and the need for higher education institutions to adopt AI to meet market demands. The study calls for more research on AI's effects on assessment, integrity, and higher education careers.","PeriodicalId":45439,"journal":{"name":"TEM Journal-Technology Education Management Informatics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135033223","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}
Pavitra Kannadass, R. Hidayat, Pariang Sonang Siregar, Alma Pratiwi Husain
Participation in modelling activities significantly facilitates the development of mathematical skills. By utilizing the concept of mathematical modelling, students may be able to develop a more grounded understanding of mathematics. The objective of this research was to explore how computational thinking and critical thinking are connected to the mathematical modelling proficiency of pre-service teachers. Correlational quantitative research was conducted on 140 pre-service mathematics teachers from the Institute of Teacher Education, Penang and the Institute of Teacher Education, Ipoh, using a correlational research design. Using cluster random sampling, the Institute of Teacher Education was selected at random. The results revealed that pre-service mathematics teachers exhibited a strong aptitude for computational and critical thinking, but demonstrated a limited level of proficiency in mathematical modelling. In terms of modelling proficiency, the results indicated a significant correlation between computational thinking and critical thinking.The findings from this research demonstrated a significant correlation between critical thinking, computational thinking, and proficiency in modelling. Therefore, computational thinking and critical thinking improve prospective mathematics teachers' modelling skills.
{"title":"Relationship Between Computational and Critical Thinking Towards Modelling Competency Among Pre-Service Mathematics Teachers","authors":"Pavitra Kannadass, R. Hidayat, Pariang Sonang Siregar, Alma Pratiwi Husain","doi":"10.18421/tem123-17","DOIUrl":"https://doi.org/10.18421/tem123-17","url":null,"abstract":"Participation in modelling activities significantly facilitates the development of mathematical skills. By utilizing the concept of mathematical modelling, students may be able to develop a more grounded understanding of mathematics. The objective of this research was to explore how computational thinking and critical thinking are connected to the mathematical modelling proficiency of pre-service teachers. Correlational quantitative research was conducted on 140 pre-service mathematics teachers from the Institute of Teacher Education, Penang and the Institute of Teacher Education, Ipoh, using a correlational research design. Using cluster random sampling, the Institute of Teacher Education was selected at random. The results revealed that pre-service mathematics teachers exhibited a strong aptitude for computational and critical thinking, but demonstrated a limited level of proficiency in mathematical modelling. In terms of modelling proficiency, the results indicated a significant correlation between computational thinking and critical thinking.The findings from this research demonstrated a significant correlation between critical thinking, computational thinking, and proficiency in modelling. Therefore, computational thinking and critical thinking improve prospective mathematics teachers' modelling skills.","PeriodicalId":45439,"journal":{"name":"TEM Journal-Technology Education Management Informatics","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41370043","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}
Sentiment analysis was used to understand the key aspects of the hotel quest stay with emphasis on the drivers of positive/negative experience. Other studies evaluated the impact of the online reputation on the business performance but the minority of the studies focused on the use of online reputation analysis within the competitive strategy creation. This study uses an open-source tool to crawl and analyze 15 907 online reviews from Booking.com, TripAdvisor.com, and Google.com for selected company and its competitors. The results show strength and weaknesses of individual companies that might be used to strengthen the company’s position of the market.
{"title":"Extracting Insights From Competitor's Mistakes: A Sentiment Analysis Approach Using Competitive set Online Reviews","authors":"Štěpán Chalupa, M. Petříček, K. Chadt","doi":"10.18421/tem123-58","DOIUrl":"https://doi.org/10.18421/tem123-58","url":null,"abstract":"Sentiment analysis was used to understand the key aspects of the hotel quest stay with emphasis on the drivers of positive/negative experience. Other studies evaluated the impact of the online reputation on the business performance but the minority of the studies focused on the use of online reputation analysis within the competitive strategy creation. This study uses an open-source tool to crawl and analyze 15 907 online reviews from Booking.com, TripAdvisor.com, and Google.com for selected company and its competitors. The results show strength and weaknesses of individual companies that might be used to strengthen the company’s position of the market.","PeriodicalId":45439,"journal":{"name":"TEM Journal-Technology Education Management Informatics","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46043791","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}
This study examined the relationships among the dimensions of Unified Theory of Acceptance and Use of Technology (UTAUT) and external variables in the context of using artificial intelligence (AI)-powered tools for lecture design. After four months of utilizing the tools, 208 participants took the survey via Google Form. The structural equation model was utilized to analyze the obtained responses. Findings showed that performance expectancy, effort expectancy, social influence, and availability/accessibility are reliable predictors of users' intentions to utilize AI-powered design tools. However, the effects of facilitating conditions and trust and confidence are insignificant. The proposed conceptual model accounted for 54.6% of the data variation. This study provides designers and developers of AI-powered design tools with theoretical and practical implications that can enhance the practical adoption and utilization of these tools.
{"title":"An Empirical Analysis of Predictors of AI-Powered Design Tool Adoption","authors":"Nguyen Thi Hong Chuyen, Nguyen The Vinh","doi":"10.18421/tem123-28","DOIUrl":"https://doi.org/10.18421/tem123-28","url":null,"abstract":"This study examined the relationships among the dimensions of Unified Theory of Acceptance and Use of Technology (UTAUT) and external variables in the context of using artificial intelligence (AI)-powered tools for lecture design. After four months of utilizing the tools, 208 participants took the survey via Google Form. The structural equation model was utilized to analyze the obtained responses. Findings showed that performance expectancy, effort expectancy, social influence, and availability/accessibility are reliable predictors of users' intentions to utilize AI-powered design tools. However, the effects of facilitating conditions and trust and confidence are insignificant. The proposed conceptual model accounted for 54.6% of the data variation. This study provides designers and developers of AI-powered design tools with theoretical and practical implications that can enhance the practical adoption and utilization of these tools.","PeriodicalId":45439,"journal":{"name":"TEM Journal-Technology Education Management Informatics","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44747517","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}
Héctor Cardona, Carlos Lara-Álvarez, Ezra Parra, K. Villalba-Condori
A virtual tour is a guided tour facilitated through Virtual Reality (VR) technology. The primary focus of this paper is on Virtual Tours of Facilities (VTF) within academic contexts. These VTFs employ VR as a medium to provide immersive educational experiences within facilities, such as laboratories, industrial sites, and universities. Our study advances three hypotheses: firstly, that continuous variables distinguish VTFs; secondly, that VTFs offer distinct inherent advantages and disadvantages in comparison to conventional in-person visits; and thirdly, that various software types and developmental approaches for virtual tours can be systematically categorized based on their technical attributes and usability factors. Through a snowball rolling literature review method, we analyze 32 studies to identify current research trends, pinpoint gaps, and highlight areas of interest related to VTF. The ensuing analysis explores VTF applications, associated challenges, and potential technologies, culminating in a comprehensive and insightful overview of the field.
{"title":"Virtual Tours to Facilities for Educational Purposes: A Review","authors":"Héctor Cardona, Carlos Lara-Álvarez, Ezra Parra, K. Villalba-Condori","doi":"10.18421/tem123-55","DOIUrl":"https://doi.org/10.18421/tem123-55","url":null,"abstract":"A virtual tour is a guided tour facilitated through Virtual Reality (VR) technology. The primary focus of this paper is on Virtual Tours of Facilities (VTF) within academic contexts. These VTFs employ VR as a medium to provide immersive educational experiences within facilities, such as laboratories, industrial sites, and universities. Our study advances three hypotheses: firstly, that continuous variables distinguish VTFs; secondly, that VTFs offer distinct inherent advantages and disadvantages in comparison to conventional in-person visits; and thirdly, that various software types and developmental approaches for virtual tours can be systematically categorized based on their technical attributes and usability factors. Through a snowball rolling literature review method, we analyze 32 studies to identify current research trends, pinpoint gaps, and highlight areas of interest related to VTF. The ensuing analysis explores VTF applications, associated challenges, and potential technologies, culminating in a comprehensive and insightful overview of the field.","PeriodicalId":45439,"journal":{"name":"TEM Journal-Technology Education Management Informatics","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44055475","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}
M. Idhom, Akhmad Fauzi, Trimono Trimono, P. Riyantoko
Electrical energy is one of the components of Gross Domestic Product that is able to encourage the economy because it has become a basic need of the community. To meet the increasing demand for electrical energy, the Indonesia National Electricity Providers (PLN) need to predict the amount of electrical power required based on the customer numbers to meet the demand for adequate electricity supply. This study aims to predict electric power based on electricity user customers using a time series regression model. The data used in this study are secondary data which get from PLN annual report in 2021. This study resulted in a finding of the best prediction model based on the Akaike Information Criterion (AIC) value, namely the time series regression model with the error value modeled by the AR(1) model, while the forecasting accuracy measure used the value MAPE of 9.77%. This means that the result of model prediction is highly accurate.
电能是国内生产总值的一个组成部分，它能够鼓励经济发展，因为它已经成为社会的基本需求。为了满足日益增长的电力需求，印度尼西亚国家电力供应商(PLN)需要根据客户数量预测所需的电量，以满足充足的电力供应需求。本研究旨在利用时间序列回归模型对电力用户客户进行电力预测。本研究使用的数据为二手数据，来自PLN 2021年年报。本研究发现基于赤池信息准则(Akaike Information Criterion, AIC)值的预测模型为最佳预测模型，即以AR(1)模型为误差值的时间序列回归模型，而预测精度度量采用MAPE值为9.77%。这意味着模型预测的结果是非常准确的。
{"title":"Time Series Regression: Prediction of Electricity Consumption Based on Number of Consumers at National Electricity Supply Company","authors":"M. Idhom, Akhmad Fauzi, Trimono Trimono, P. Riyantoko","doi":"10.18421/tem123-39","DOIUrl":"https://doi.org/10.18421/tem123-39","url":null,"abstract":"Electrical energy is one of the components of Gross Domestic Product that is able to encourage the economy because it has become a basic need of the community. To meet the increasing demand for electrical energy, the Indonesia National Electricity Providers (PLN) need to predict the amount of electrical power required based on the customer numbers to meet the demand for adequate electricity supply. This study aims to predict electric power based on electricity user customers using a time series regression model. The data used in this study are secondary data which get from PLN annual report in 2021. This study resulted in a finding of the best prediction model based on the Akaike Information Criterion (AIC) value, namely the time series regression model with the error value modeled by the AR(1) model, while the forecasting accuracy measure used the value MAPE of 9.77%. This means that the result of model prediction is highly accurate.","PeriodicalId":45439,"journal":{"name":"TEM Journal-Technology Education Management Informatics","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45838999","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}
O. Kalaman, S. Bondarenko, M. Telovata, N. Petrenko, O. Yershova, O. Sagan
The aim of the study is to analyze, systematize, and formulate scenarios for managing the integration of digital and intelligent technologies in the informatization of education based on the influence of the factors of the existing external environment. It was shown that digital transformation is a process of digital technology integration into all aspects of business activities, requiring fundamental changes in technology, culture, operations, and principles of creating new products and services. Simulation models of digital and intelligent technologies in informatization of education are proposed. Possible scenarios for the development of the education system are described: inertial and transformational. A new viable base scenario is proposed, which can be called a divergent, or school dilution scenario. It is illustrated that these three rather general scenarios show the possible place and role of digital and intellectual technologies in the changes taking place in the informatization of education today.
{"title":"Management of Digital and Intellectual Technologies Integration in Education Informatization","authors":"O. Kalaman, S. Bondarenko, M. Telovata, N. Petrenko, O. Yershova, O. Sagan","doi":"10.18421/tem123-46","DOIUrl":"https://doi.org/10.18421/tem123-46","url":null,"abstract":"The aim of the study is to analyze, systematize, and formulate scenarios for managing the integration of digital and intelligent technologies in the informatization of education based on the influence of the factors of the existing external environment. It was shown that digital transformation is a process of digital technology integration into all aspects of business activities, requiring fundamental changes in technology, culture, operations, and principles of creating new products and services. Simulation models of digital and intelligent technologies in informatization of education are proposed. Possible scenarios for the development of the education system are described: inertial and transformational. A new viable base scenario is proposed, which can be called a divergent, or school dilution scenario. It is illustrated that these three rather general scenarios show the possible place and role of digital and intellectual technologies in the changes taking place in the informatization of education today.","PeriodicalId":45439,"journal":{"name":"TEM Journal-Technology Education Management Informatics","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48102720","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}
Whereas the Internet of Things (IoT) has become a research concern in education, the learning media in IoT is still minimal, and IoT-based research for education is still limited. It means that learning media and IoT research in education are still challenging for researchers. Bearing in mind mushroom cultivators do not understand what actions must be considered when cultivating mushrooms, and oyster mushroom cultivation frequently fails due to uncontrolled Baglog environmental conditions. Therefore this study aims to develop an IoT-based control system for oyster mushroom cultivation as a student practical lesson media and its learning effects for students. The research method combines experimental, surveys, and observation procedures. The research succeeded in carrying out educational activities with results that satisfied students and enabled most students to build an IoT-based control system and cultivate oyster mushrooms. This study's findings reinforce previous researchers' opinion that IoT technology has replaced traditional methods. Furthermore, the study's conclusions remove the dark side of concerns about the continuation of oyster mushroom production by previous researchers.
{"title":"Building an IoT-Based Oyster Mushroom Cultivation and Control System and Its Practical Learning Effects on Students","authors":"Anthony Anggrawan, Christofer Satria, M. Zulfikri","doi":"10.18421/tem123-69","DOIUrl":"https://doi.org/10.18421/tem123-69","url":null,"abstract":"Whereas the Internet of Things (IoT) has become a research concern in education, the learning media in IoT is still minimal, and IoT-based research for education is still limited. It means that learning media and IoT research in education are still challenging for researchers. Bearing in mind mushroom cultivators do not understand what actions must be considered when cultivating mushrooms, and oyster mushroom cultivation frequently fails due to uncontrolled Baglog environmental conditions. Therefore this study aims to develop an IoT-based control system for oyster mushroom cultivation as a student practical lesson media and its learning effects for students. The research method combines experimental, surveys, and observation procedures. The research succeeded in carrying out educational activities with results that satisfied students and enabled most students to build an IoT-based control system and cultivate oyster mushrooms. This study's findings reinforce previous researchers' opinion that IoT technology has replaced traditional methods. Furthermore, the study's conclusions remove the dark side of concerns about the continuation of oyster mushroom production by previous researchers.","PeriodicalId":45439,"journal":{"name":"TEM Journal-Technology Education Management Informatics","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44291667","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}
Examining the physical movements of students during their educational quests holds great significance as these nonverbal cues can exert a substantial influence on academic performance, and boost, learning outcomes, Consequently, numerous researchers are engaged in exploring the domain of gesture categorization employing machine learning techniques. Initially, we conducted an observation of students’ movements in a virtual learning environment during face-to-face interactions with their teachers. This procedure yielded a roster of thirteen motion-based behaviors, encompassing actions such as tilting the head towards either direction, lowering and lifting the head, as well as gesturing with the right and left hand towards the head and neck area, and positioning the shoulders in a front and lateral direction. This research offers a technique for establishing a set of criteria for categorizing students’ gesticulations in online learning by utilizing the comprehensive MediaPipe holistic library and OpenCV to detect, pose and extract salient landmarks. This endeavor culminated in the attainment of a percentage-based metric indicative of gesture identification efficacy pertaining to the aforementioned thirteen motion-based activities.
{"title":"Method Development Through Landmark Point Extraction for Gesture Classification With Computer Vision and MediaPipe","authors":"S. Suherman, Adang Suhendra, E. Ernastuti","doi":"10.18421/tem123-49","DOIUrl":"https://doi.org/10.18421/tem123-49","url":null,"abstract":"Examining the physical movements of students during their educational quests holds great significance as these nonverbal cues can exert a substantial influence on academic performance, and boost, learning outcomes, Consequently, numerous researchers are engaged in exploring the domain of gesture categorization employing machine learning techniques. Initially, we conducted an observation of students’ movements in a virtual learning environment during face-to-face interactions with their teachers. This procedure yielded a roster of thirteen motion-based behaviors, encompassing actions such as tilting the head towards either direction, lowering and lifting the head, as well as gesturing with the right and left hand towards the head and neck area, and positioning the shoulders in a front and lateral direction. This research offers a technique for establishing a set of criteria for categorizing students’ gesticulations in online learning by utilizing the comprehensive MediaPipe holistic library and OpenCV to detect, pose and extract salient landmarks. This endeavor culminated in the attainment of a percentage-based metric indicative of gesture identification efficacy pertaining to the aforementioned thirteen motion-based activities.","PeriodicalId":45439,"journal":{"name":"TEM Journal-Technology Education Management Informatics","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44393529","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}
Harun Mukhtar, Muhammad Akmal bin Remli, Khairul Nizar Syazwan Wan Salihin Wong, Mohd Saberi Mohamad
The DL (Deep Learning) method is the standard for forecasting tourist arrivals. This method provides very good forecasting results but needs improvement if the data is small. Statistical data from the BPS (Central Bureau of Statistics) needs to be corrected, resulting in forecasts that tend to be invalid. This study uses statistical data and GT (Google Trends) as a solution so that the data is sufficient. GT data has a lot of noise because there is a shift between web searches and departures. This difference will produce noise that needs to be cleaned. We use monthly data from January 2008 to December 2021 from BPS sources combined with GT. Hilbert-Huang Transform (HHT) is proposed to clean data from various disturbances. The DL used in this study is long short-time memory (LSTM) and was evaluated using the root mean squared error RMSE and mean absolute percentage error (MAPE). The evaluation results show that the HHT-LSTM results are better than without data cleaning.
{"title":"Deep Learning With Processing Algorithms for Forecasting Tourist Arrivals","authors":"Harun Mukhtar, Muhammad Akmal bin Remli, Khairul Nizar Syazwan Wan Salihin Wong, Mohd Saberi Mohamad","doi":"10.18421/tem123-57","DOIUrl":"https://doi.org/10.18421/tem123-57","url":null,"abstract":"The DL (Deep Learning) method is the standard for forecasting tourist arrivals. This method provides very good forecasting results but needs improvement if the data is small. Statistical data from the BPS (Central Bureau of Statistics) needs to be corrected, resulting in forecasts that tend to be invalid. This study uses statistical data and GT (Google Trends) as a solution so that the data is sufficient. GT data has a lot of noise because there is a shift between web searches and departures. This difference will produce noise that needs to be cleaned. We use monthly data from January 2008 to December 2021 from BPS sources combined with GT. Hilbert-Huang Transform (HHT) is proposed to clean data from various disturbances. The DL used in this study is long short-time memory (LSTM) and was evaluated using the root mean squared error RMSE and mean absolute percentage error (MAPE). The evaluation results show that the HHT-LSTM results are better than without data cleaning.","PeriodicalId":45439,"journal":{"name":"TEM Journal-Technology Education Management Informatics","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46654363","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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