Crypto-ransomware is a class of malware that encrypt their victim’s data and only return the decryption key in exchange for a ransom. In a previous work, we have yet designed a solution able to detect any ciphering of files using statistical estimator. Once detected, a pop up requests the user to verify if that operation is allowed on not. To improve our tool, automation is needed. In this paper, an anomaly detection mechanism to determine if a suspected group of threads is an authorized cryptographic software or a malicious code is presented. The effectiveness of our solution to correctly distinguish between valid programs and ransomware is evaluated using a string analysis. The tf-idf metric is used to choose the most pertinent features. The distance of a candidate software with a vector representing the allowed cryptographic software is measured. If the distance exceeds a threshold, the suspected process is flagged as a ransomware. We have evaluated our approach with the samples provided by open databases and executed on our bare metal platform.
{"title":"Discriminating Unknown Software Using Distance Model","authors":"Yassine Lemmou, Hélène Le-Bouder, Jean-Louis Lanet","doi":"10.1109/ICACSIS47736.2019.8979970","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979970","url":null,"abstract":"Crypto-ransomware is a class of malware that encrypt their victim’s data and only return the decryption key in exchange for a ransom. In a previous work, we have yet designed a solution able to detect any ciphering of files using statistical estimator. Once detected, a pop up requests the user to verify if that operation is allowed on not. To improve our tool, automation is needed. In this paper, an anomaly detection mechanism to determine if a suspected group of threads is an authorized cryptographic software or a malicious code is presented. The effectiveness of our solution to correctly distinguish between valid programs and ransomware is evaluated using a string analysis. The tf-idf metric is used to choose the most pertinent features. The distance of a candidate software with a vector representing the allowed cryptographic software is measured. If the distance exceeds a threshold, the suspected process is flagged as a ransomware. We have evaluated our approach with the samples provided by open databases and executed on our bare metal platform.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114421773","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 : 2019-10-01DOI: 10.1109/icacsis47736.2019.8979651
{"title":"ICACSIS 2019 Committees","authors":"","doi":"10.1109/icacsis47736.2019.8979651","DOIUrl":"https://doi.org/10.1109/icacsis47736.2019.8979651","url":null,"abstract":"","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123458037","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 : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979703
Sinta Nur Asih, Y. G. Sucahyo, Arfive Gandhi, Y. Ruldeviyani
Online Gig Economy (OGE) as a result of digitalization results in a group of freelancers called gig workers. The rapid growth of the OGE platform and the high number of internet users in Indonesia has the potential to open up online job market opportunities and can lead to an excess supply of online gig workers. The growth of OGE in Indonesia needs to be balanced with the existence of research to find solutions to factors that influence people’s interest in using online gig worker services. Data collection is done by distributing online questionnaires. Based on the results of the study, the factors that are motivating the interest of the public to use the gig worker online services are the Perceived Usefulness, and Social Influence while the inhibiting factor is the Perceived of Risk.
{"title":"Inhibiting Motivating Factors on Online Gig Economy Client in Indonesia","authors":"Sinta Nur Asih, Y. G. Sucahyo, Arfive Gandhi, Y. Ruldeviyani","doi":"10.1109/ICACSIS47736.2019.8979703","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979703","url":null,"abstract":"Online Gig Economy (OGE) as a result of digitalization results in a group of freelancers called gig workers. The rapid growth of the OGE platform and the high number of internet users in Indonesia has the potential to open up online job market opportunities and can lead to an excess supply of online gig workers. The growth of OGE in Indonesia needs to be balanced with the existence of research to find solutions to factors that influence people’s interest in using online gig worker services. Data collection is done by distributing online questionnaires. Based on the results of the study, the factors that are motivating the interest of the public to use the gig worker online services are the Perceived Usefulness, and Social Influence while the inhibiting factor is the Perceived of Risk.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131760557","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 : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979925
Triando, Leena Arhippainen
Viena Karelian is a dialect of Karelian language, which is categorized as an endangered language and requires an innovative approach to increase motivation and skills of learners. Currently, there are mainly traditional ways to learn Viena Karelian dialect such as occasional gathering and language courses are conducted by a cultural community. Therefore, gamification approach was utilized to develop a mobile web game, so beginner learners could learn in a fun and effective ways, also location-independently. A mobile web game prototype was implemented by utilizing the Laravel PHP framework and Bootstrap frontend framework, which enable the game prototype accessible on mobile web browsers. The main concept of this game was constructed by using a language learning model, which was defined with levels of easy, medium, and hard, also skill sections of listening, reading, and writing. Preliminary user experience test was conducted with 12 game experts and the result shows the game prototype was experienced as Engaging, Easy to use, Useful, Approachable and Consistent.
{"title":"Development and User Experiences of the Learn Viena Karelian Mobile Web Game","authors":"Triando, Leena Arhippainen","doi":"10.1109/ICACSIS47736.2019.8979925","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979925","url":null,"abstract":"Viena Karelian is a dialect of Karelian language, which is categorized as an endangered language and requires an innovative approach to increase motivation and skills of learners. Currently, there are mainly traditional ways to learn Viena Karelian dialect such as occasional gathering and language courses are conducted by a cultural community. Therefore, gamification approach was utilized to develop a mobile web game, so beginner learners could learn in a fun and effective ways, also location-independently. A mobile web game prototype was implemented by utilizing the Laravel PHP framework and Bootstrap frontend framework, which enable the game prototype accessible on mobile web browsers. The main concept of this game was constructed by using a language learning model, which was defined with levels of easy, medium, and hard, also skill sections of listening, reading, and writing. Preliminary user experience test was conducted with 12 game experts and the result shows the game prototype was experienced as Engaging, Easy to use, Useful, Approachable and Consistent.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130341621","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 : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979938
Rahmanto Prabowo, Y. G. Sucahyo, Arfive Gandhi, Y. Ruldeviyani
The gamification in ride-sharing applications is actualized in a point system for incentives and ratings for feedback. By growth of driver’s number, the current gamification is facing problems. Drivers should spend more time and serve more orders to achieve targeted points. As the impact, their performance got worse, and their customers’ satisfaction was reduced. To analyze the gamification effect on driver motivation, this study synthesizes Self Determination Theory (SDT) and Motivational Affordance Perspective (MAP). This study is a case study based on empirical data using a quantitative approach. By involving 103 participants, this study examines seven variables: Identified Regulation, External Regulation, Need for Autonomy, Self-Efficacy, Playfulness, Extrinsic Motivation, and Intrinsic Motivation. After mapping them into nine hypotheses, there were five accepted ones. The results unveiled that gamification can influence extrinsic motivation, but it cannot influence intrinsic motivation. As general interpretation, gamification motivates drivers to take more orders since they are forced to reach targeted points. This study provides recommendations for ride-sharing operators to improve gamification by adding new features to cover self-efficacy, need for autonomy, and playfulness in order to influence drivers’ intrinsic motivation.
{"title":"Does Gamification Motivate Gig Workers? A Critical Issue in Ride-Sharing Industries","authors":"Rahmanto Prabowo, Y. G. Sucahyo, Arfive Gandhi, Y. Ruldeviyani","doi":"10.1109/ICACSIS47736.2019.8979938","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979938","url":null,"abstract":"The gamification in ride-sharing applications is actualized in a point system for incentives and ratings for feedback. By growth of driver’s number, the current gamification is facing problems. Drivers should spend more time and serve more orders to achieve targeted points. As the impact, their performance got worse, and their customers’ satisfaction was reduced. To analyze the gamification effect on driver motivation, this study synthesizes Self Determination Theory (SDT) and Motivational Affordance Perspective (MAP). This study is a case study based on empirical data using a quantitative approach. By involving 103 participants, this study examines seven variables: Identified Regulation, External Regulation, Need for Autonomy, Self-Efficacy, Playfulness, Extrinsic Motivation, and Intrinsic Motivation. After mapping them into nine hypotheses, there were five accepted ones. The results unveiled that gamification can influence extrinsic motivation, but it cannot influence intrinsic motivation. As general interpretation, gamification motivates drivers to take more orders since they are forced to reach targeted points. This study provides recommendations for ride-sharing operators to improve gamification by adding new features to cover self-efficacy, need for autonomy, and playfulness in order to influence drivers’ intrinsic motivation.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134117074","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 : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979715
A. Juliansyah, Gibran Satya Nugraha
Neuro retinal rim is an area between optic disc and optic cup. Neuro retinal rim area consists of four parts, namely inferior, superior, nasal, and temporal (ISNT). The diagnosis of glaucoma can be done by observing the shape of the neuro retinal rim. In normal eyes, the size of the four parts in the neuro retinal rim follows the ISNT rule, from the largest to the smallest, as follows: inferior, superior, nasal, and temporal. This research was conducted to examine an adaptive threshold of neuro retinal area segmentation. The neuro retinal rim area was obtained by reducing the optic disc and the optic cup parts. Before that, optic cup and optic disc was segmented by analyzing histogram features likes mean and standard deviation values. Normal image has the area from the largest to the smallest according to the ISNT rules, however, in glaucoma, it is usually the inferior and superior areas attacked first, so that they experience notching or narrowing and violate the ISNT rules. The accuracy of the system was 91.25%, with 73 images from DRISTHI-GS retinal image database successfully diagnosed with the ISNT area that experienced notching, while the 8 images were still failed to diagnose due to a poor level of brightness.
{"title":"Segmentation of Neuro Retinal Rim Area using Histogram Feature-based for Glaucoma Detection in Retinal Fundus Image","authors":"A. Juliansyah, Gibran Satya Nugraha","doi":"10.1109/ICACSIS47736.2019.8979715","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979715","url":null,"abstract":"Neuro retinal rim is an area between optic disc and optic cup. Neuro retinal rim area consists of four parts, namely inferior, superior, nasal, and temporal (ISNT). The diagnosis of glaucoma can be done by observing the shape of the neuro retinal rim. In normal eyes, the size of the four parts in the neuro retinal rim follows the ISNT rule, from the largest to the smallest, as follows: inferior, superior, nasal, and temporal. This research was conducted to examine an adaptive threshold of neuro retinal area segmentation. The neuro retinal rim area was obtained by reducing the optic disc and the optic cup parts. Before that, optic cup and optic disc was segmented by analyzing histogram features likes mean and standard deviation values. Normal image has the area from the largest to the smallest according to the ISNT rules, however, in glaucoma, it is usually the inferior and superior areas attacked first, so that they experience notching or narrowing and violate the ISNT rules. The accuracy of the system was 91.25%, with 73 images from DRISTHI-GS retinal image database successfully diagnosed with the ISNT area that experienced notching, while the 8 images were still failed to diagnose due to a poor level of brightness.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"2010 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133117051","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 : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979731
Atikah Zahrah Halim, P. W. Handayani, A. Pinem
The activity of exchanging information on social media has become widespread and more open in Indonesia with the increasing number of Internet users. This study analyzes the factors that influence users to exchange information related to health on social media, and users’ intention to implement or use information that has been obtained. This study used quantitative methods and an online questionnaire for data collection. There were 1,456 respondents, who had searched for and shared health information on social media. The collected data were analyzed by Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 3.0 tools. This study found that the outcome of the expectation of social relationship did not affect health information usage intention, and human-to-human interaction did not affect health information exchange.
{"title":"User’s Intentions in Health Information Exchange in Social Media","authors":"Atikah Zahrah Halim, P. W. Handayani, A. Pinem","doi":"10.1109/ICACSIS47736.2019.8979731","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979731","url":null,"abstract":"The activity of exchanging information on social media has become widespread and more open in Indonesia with the increasing number of Internet users. This study analyzes the factors that influence users to exchange information related to health on social media, and users’ intention to implement or use information that has been obtained. This study used quantitative methods and an online questionnaire for data collection. There were 1,456 respondents, who had searched for and shared health information on social media. The collected data were analyzed by Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 3.0 tools. This study found that the outcome of the expectation of social relationship did not affect health information usage intention, and human-to-human interaction did not affect health information exchange.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"603 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134327620","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 : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979806
R. N. Ruliputra, Y. G. Sucahyo, Arfive Gandhi, Y. Ruldeviyani
The large number of internet users in Indonesia contributes to Indonesia’s growth potential in general in the digital economy. This rapid growth urged the government to plan for the industrial 4.0 revolution with artificial intelligence (AI) technology as its basis. Innovations in the field of AI come from many startup companies. Despite many benefits, only 40 percent companies in Asia-Pacific utilized the AI technology in functional areas, such as chatbot services and customer service robots. This gap needs to be addressed considering that more than 87 percent of internet users in Indonesia utilize chat services and social media. AI utilization can be implemented by using the services of companies engaged in AI, including startups. However, AI-based startups in Indonesia are not yet mapped. Furthermore, practical impact of AI implementation needs to be surveyed as knowledge to implement AI in business. This research mapped 68 Indonesian startups of AI service providers. In addition, this study evaluates the implementation of AI in the Natural Language Processing (NLP) category for companies from the perspective of the service provider. Of all 8 mapped NLP service providers, 4 of them are chosen as the research objects. The impacts of its implementation are categorized into eight categories: motivation, profit, interest, change in strategy, competition, satisfaction, trust, and ethics. Recommendations are given to companies related to NLP with the most important things which are defining purposes and dare to try.
{"title":"Why do Enterprises Adopt Natural Language Processing Services? Startups’ Landscape and Opportunities in Artificial Intelligence","authors":"R. N. Ruliputra, Y. G. Sucahyo, Arfive Gandhi, Y. Ruldeviyani","doi":"10.1109/ICACSIS47736.2019.8979806","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979806","url":null,"abstract":"The large number of internet users in Indonesia contributes to Indonesia’s growth potential in general in the digital economy. This rapid growth urged the government to plan for the industrial 4.0 revolution with artificial intelligence (AI) technology as its basis. Innovations in the field of AI come from many startup companies. Despite many benefits, only 40 percent companies in Asia-Pacific utilized the AI technology in functional areas, such as chatbot services and customer service robots. This gap needs to be addressed considering that more than 87 percent of internet users in Indonesia utilize chat services and social media. AI utilization can be implemented by using the services of companies engaged in AI, including startups. However, AI-based startups in Indonesia are not yet mapped. Furthermore, practical impact of AI implementation needs to be surveyed as knowledge to implement AI in business. This research mapped 68 Indonesian startups of AI service providers. In addition, this study evaluates the implementation of AI in the Natural Language Processing (NLP) category for companies from the perspective of the service provider. Of all 8 mapped NLP service providers, 4 of them are chosen as the research objects. The impacts of its implementation are categorized into eight categories: motivation, profit, interest, change in strategy, competition, satisfaction, trust, and ethics. Recommendations are given to companies related to NLP with the most important things which are defining purposes and dare to try.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"235 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116088638","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 : 2019-10-01DOI: 10.1109/icacsis47736.2019.8979990
{"title":"ICACSIS 2019 Cover Page","authors":"","doi":"10.1109/icacsis47736.2019.8979990","DOIUrl":"https://doi.org/10.1109/icacsis47736.2019.8979990","url":null,"abstract":"","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124130879","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 : 2019-10-01DOI: 10.1109/ICACSIS47736.2019.8979958
Ari Auditianto, Y. G. Sucahyo, Arfive Gandhi, Y. Ruldeviyani
Physical Gig Economy (PGE) in Indonesia has rapid growth in the last few years. Unfortunately, a large gap among PGE services occurred. Compared with ride-hailing services with highly frequent transactions, cleaning and mechanical services have had few transactions. This study aims to identify and analyze the factors that influence clients to use PGE services. Previous studies about users’ intention were synthesized to develop the research model and hypothesis. Factors that are thought to have an influence on client behavior and intention are platform quality, trust, social influence, perceived risk, hedonic motivation, and economic benefits. Furthermore, a quantitative approach with Partial Least Squares Structural Equation Modeling (PLS-SEM) and 318 valid respondents is demonstrated. The results show that hedonic motivation is the most influencing factor followed by economic benefits, trust, and perceived platform quality. This study also informs that social influence only affects client on the early usage of PGE. Having the knowledge of these factors, PGE operators could develop the right strategies to further expand their business and attract new clients.
{"title":"Discovering the Influencing Factors of Physical Gig Economy Usage: Quantitative Approach on Clients9 Perception","authors":"Ari Auditianto, Y. G. Sucahyo, Arfive Gandhi, Y. Ruldeviyani","doi":"10.1109/ICACSIS47736.2019.8979958","DOIUrl":"https://doi.org/10.1109/ICACSIS47736.2019.8979958","url":null,"abstract":"Physical Gig Economy (PGE) in Indonesia has rapid growth in the last few years. Unfortunately, a large gap among PGE services occurred. Compared with ride-hailing services with highly frequent transactions, cleaning and mechanical services have had few transactions. This study aims to identify and analyze the factors that influence clients to use PGE services. Previous studies about users’ intention were synthesized to develop the research model and hypothesis. Factors that are thought to have an influence on client behavior and intention are platform quality, trust, social influence, perceived risk, hedonic motivation, and economic benefits. Furthermore, a quantitative approach with Partial Least Squares Structural Equation Modeling (PLS-SEM) and 318 valid respondents is demonstrated. The results show that hedonic motivation is the most influencing factor followed by economic benefits, trust, and perceived platform quality. This study also informs that social influence only affects client on the early usage of PGE. Having the knowledge of these factors, PGE operators could develop the right strategies to further expand their business and attract new clients.","PeriodicalId":165090,"journal":{"name":"2019 International Conference on Advanced Computer Science and information Systems (ICACSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129040647","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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