Diabetes mellitus (DM) is a chronic disease, which can affect the entire body system. Early Diagnosis of patient's diabetics can help improve their health quality or reducing the risk factors. The main objective of this study is to evaluate the performance of some Machine Learning algorithms, used to predict diabetes diseases, for this purpose we apply and evaluate four Machine Learning algorithms (Decision Tree, K-Nearest Neighbours, Artificial Neural Network and Deep Neural Network) to predict diabetes mellitus. These techniques have been trained and tested on Pima Indian dataset. The performances of the experimented algorithms have been evaluated after removing noisy data and using features selection with Neighbourhood components Analysis in order to reduce the number of features and mitigate the complexity of dimensionality in favour of speeds up the learning process, enhances data understanding. Different similarity metrics used to compare model performance like Accuracy, Sensitivity, and Specificity.
{"title":"Diabetes Diseases Prediction Using Supervised Machine Learning and Neighbourhood Components Analysis","authors":"Othmane Daanouni, B. Cherradi, A. Tmiri","doi":"10.1145/3386723.3387887","DOIUrl":"https://doi.org/10.1145/3386723.3387887","url":null,"abstract":"Diabetes mellitus (DM) is a chronic disease, which can affect the entire body system. Early Diagnosis of patient's diabetics can help improve their health quality or reducing the risk factors. The main objective of this study is to evaluate the performance of some Machine Learning algorithms, used to predict diabetes diseases, for this purpose we apply and evaluate four Machine Learning algorithms (Decision Tree, K-Nearest Neighbours, Artificial Neural Network and Deep Neural Network) to predict diabetes mellitus. These techniques have been trained and tested on Pima Indian dataset. The performances of the experimented algorithms have been evaluated after removing noisy data and using features selection with Neighbourhood components Analysis in order to reduce the number of features and mitigate the complexity of dimensionality in favour of speeds up the learning process, enhances data understanding. Different similarity metrics used to compare model performance like Accuracy, Sensitivity, and Specificity.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124442684","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}
Data analysis methods have been widely used in various domains, such as medical, marketing, and agriculture. Since they have a good performance to reduce massive data. Unfortunately, those methods are limited without the usage of Computer Technologies (computer technologies, 'CT'), which lead to developing autonomous systems capable of making appropriate decisions in each situation, by the realization of algorithm and artificial intelligence (artificial intelligence, 'AI') tools. This paper presents the coupling of principal component analysis (principal component analysis, 'PCA') mathematical method and the counter propagation artificial neural network (counter propagation network, 'CPN'), as an objective to reduce and minimize the data before starting learning, improve the learning process results and accuracy of the classification and eliminate the obstacles detected between inputs objects. The results of this combination have been compared with the results of the standard CPN.
{"title":"Study and Analysis of Data Analysis Systems (Reconstruction of a Learning Data from the Initial Data)","authors":"S. Belattar, O. Abdoun, Haimoudi El Khatir","doi":"10.1145/3386723.3387837","DOIUrl":"https://doi.org/10.1145/3386723.3387837","url":null,"abstract":"Data analysis methods have been widely used in various domains, such as medical, marketing, and agriculture. Since they have a good performance to reduce massive data. Unfortunately, those methods are limited without the usage of Computer Technologies (computer technologies, 'CT'), which lead to developing autonomous systems capable of making appropriate decisions in each situation, by the realization of algorithm and artificial intelligence (artificial intelligence, 'AI') tools. This paper presents the coupling of principal component analysis (principal component analysis, 'PCA') mathematical method and the counter propagation artificial neural network (counter propagation network, 'CPN'), as an objective to reduce and minimize the data before starting learning, improve the learning process results and accuracy of the classification and eliminate the obstacles detected between inputs objects. The results of this combination have been compared with the results of the standard CPN.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127181480","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}
Stéphane Cédric KOUMETIO TEKOUABOU, E. A. Alaoui, I. Chabbar, Walid Cherif, H. Silkan
Glaucoma is one of the leading causes of blindness and visual impairment in adults and the elderly. Early detection of this disease through regular screening is particularly important in preventing vision loss. To do this, several diagnostic techniques are used ranging from classical techniques centered on an expert to modern diagnostic methods, sometimes completely computerized. The implementation of computerized systems based on the early detection and classification of clinical signs of glaucoma can greatly improve the diagnosis of this disease. Several authors have proposed models allowing the automatic classification of clinical signs of glaucoma. However, not only these models are not efficient enough and remain optimizable but also often do not take into account the problem of data instability in their construction and the performance test measures adapted to evaluate them. In this paper, a predictive model based on the Support Vector Machine (SVM) has been introduced to optimize the automated diagnosis of glaucoma signs using patient visual field data. A comparative study of performance as a function of the parameters of this algorithm, which is particularly effective for this type of problem, has been made. The best results for the data collected at the Glaucoma Center of Semmelweis University in Budapest have proven to significantly improve the performance of the models offered so far especially in terms of precision, accuracy and AUC while reducing execution time.
{"title":"Machine Learning Aprroach for Early Detection of Glaucoma from Visual Fields","authors":"Stéphane Cédric KOUMETIO TEKOUABOU, E. A. Alaoui, I. Chabbar, Walid Cherif, H. Silkan","doi":"10.1145/3386723.3387858","DOIUrl":"https://doi.org/10.1145/3386723.3387858","url":null,"abstract":"Glaucoma is one of the leading causes of blindness and visual impairment in adults and the elderly. Early detection of this disease through regular screening is particularly important in preventing vision loss. To do this, several diagnostic techniques are used ranging from classical techniques centered on an expert to modern diagnostic methods, sometimes completely computerized. The implementation of computerized systems based on the early detection and classification of clinical signs of glaucoma can greatly improve the diagnosis of this disease. Several authors have proposed models allowing the automatic classification of clinical signs of glaucoma. However, not only these models are not efficient enough and remain optimizable but also often do not take into account the problem of data instability in their construction and the performance test measures adapted to evaluate them. In this paper, a predictive model based on the Support Vector Machine (SVM) has been introduced to optimize the automated diagnosis of glaucoma signs using patient visual field data. A comparative study of performance as a function of the parameters of this algorithm, which is particularly effective for this type of problem, has been made. The best results for the data collected at the Glaucoma Center of Semmelweis University in Budapest have proven to significantly improve the performance of the models offered so far especially in terms of precision, accuracy and AUC while reducing execution time.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127298347","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}
Younès Alaoui, Amine Belahbib, Lotfi El Achaak, M. Bouhorma
Serious Games start playing an important role in education [8]. Developed economies start using serious games for a variety of objectives among whish we find retraining the workforce, offering off-hours training in self-service mode, supplementing teachers work with games appealing to young generations, and reducing training costs [6], [7]. Learning in these developed economies is based usually on active methods and serious games bring additional training activities to the learning process[14][15]. Learning in some developing countries is based on remembering and reciting mainly. Training schoolchildren on applying knowledge is a challenge for teachers in some developing countries. Developing countries can use serious games as a catalyst to train schoolchildren on applying knowledge. The development of such serious games for schoolchildren requires collaboration between pedagogues, game designers and software developers. In this paper, we present a process and a methodology to design and develop serious games for schoolchildren. This process is called Gaming and Learning Unified Process to engineer Software, or GLUPS. We present the foundations of GLUPS, list its main artifacts, and illustrate this paper with the application of GLUPS to design a serious game that train on applying the Euclidean Division.
{"title":"Unified Process to Design and Develop Serious Games for Schoolchildren","authors":"Younès Alaoui, Amine Belahbib, Lotfi El Achaak, M. Bouhorma","doi":"10.1145/3386723.3387831","DOIUrl":"https://doi.org/10.1145/3386723.3387831","url":null,"abstract":"Serious Games start playing an important role in education [8]. Developed economies start using serious games for a variety of objectives among whish we find retraining the workforce, offering off-hours training in self-service mode, supplementing teachers work with games appealing to young generations, and reducing training costs [6], [7]. Learning in these developed economies is based usually on active methods and serious games bring additional training activities to the learning process[14][15]. Learning in some developing countries is based on remembering and reciting mainly. Training schoolchildren on applying knowledge is a challenge for teachers in some developing countries. Developing countries can use serious games as a catalyst to train schoolchildren on applying knowledge. The development of such serious games for schoolchildren requires collaboration between pedagogues, game designers and software developers. In this paper, we present a process and a methodology to design and develop serious games for schoolchildren. This process is called Gaming and Learning Unified Process to engineer Software, or GLUPS. We present the foundations of GLUPS, list its main artifacts, and illustrate this paper with the application of GLUPS to design a serious game that train on applying the Euclidean Division.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127320838","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}
Massive-Multiple Input Multiple Output (M-MIMO) is a new technology offers large antenna at the Base Station (BS), simultaneously serving multiple single-antenna users. In this paper, two geometrical channels are established and compared, based on Plane Wave (PW) and Spherical Wave (SW). The Multipolarized-Uniform-Linear-Array Massive-MIMO (MULA-mMIMO) and Multipolarized-Uniform-Circular-Array Massive-MIMO (MUCA-mMIMO) systems are used to decrease the channel orthogonality. The three dimensional MUCA-mMIMO and MULA-mMIMO are evaluated and analyzed for various parameters. Simulation results demonstrate that MUCA-mMIMO performs better than MULA-mMIMO, and will be the best choice for the new technology Massive-MIMO.
{"title":"Massive-MIMO Configuration of Multipolarized ULA and UCA in 5G Wireless Communications","authors":"Abdelhamid Riadi, M. Boulouird, M. Hassani","doi":"10.1145/3386723.3387871","DOIUrl":"https://doi.org/10.1145/3386723.3387871","url":null,"abstract":"Massive-Multiple Input Multiple Output (M-MIMO) is a new technology offers large antenna at the Base Station (BS), simultaneously serving multiple single-antenna users. In this paper, two geometrical channels are established and compared, based on Plane Wave (PW) and Spherical Wave (SW). The Multipolarized-Uniform-Linear-Array Massive-MIMO (MULA-mMIMO) and Multipolarized-Uniform-Circular-Array Massive-MIMO (MUCA-mMIMO) systems are used to decrease the channel orthogonality. The three dimensional MUCA-mMIMO and MULA-mMIMO are evaluated and analyzed for various parameters. Simulation results demonstrate that MUCA-mMIMO performs better than MULA-mMIMO, and will be the best choice for the new technology Massive-MIMO.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114153294","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}
D. Bystrov, Olimjon Toirov, Giyasov Sanjar, Taniev Mirzokhid, Urokov Sardor
Nowadays training of specialists for different branches of national economy acquires more significance than 20-25 years ago. As in other branches of economy, the same competition is met in an educational system in a marketplace. The main reason of it is globalization and general development of production technology and service in developed countries. It should be noted that in conditions of globalization of economy the competition envelopes not only the marketplace, but also the production process itself. The purpose of the work is investigation of problems of improving education system in conditions of severe competition and possibility of applying of REENGINEERING in revealing of a number of priority factors of success.
{"title":"Role of Reengineering in Training of Specialists","authors":"D. Bystrov, Olimjon Toirov, Giyasov Sanjar, Taniev Mirzokhid, Urokov Sardor","doi":"10.1145/3386723.3387868","DOIUrl":"https://doi.org/10.1145/3386723.3387868","url":null,"abstract":"Nowadays training of specialists for different branches of national economy acquires more significance than 20-25 years ago. As in other branches of economy, the same competition is met in an educational system in a marketplace. The main reason of it is globalization and general development of production technology and service in developed countries. It should be noted that in conditions of globalization of economy the competition envelopes not only the marketplace, but also the production process itself. The purpose of the work is investigation of problems of improving education system in conditions of severe competition and possibility of applying of REENGINEERING in revealing of a number of priority factors of success.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123212430","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}
Soufyane Ayanouz, Boudhir Anouar Abdelhakim, M. Benahmed
A chatbot or conversational agent is a software that can communicate with a human by using natural language. One of the essential tasks in artificial intelligence and natural language processing is the modeling of conversation. Since the beginning of artificial intelligence, its been the hardest challenge to create a good chatbot. Although chatbots can perform many tasks, the primary function they have to play is to understand the utterances of humans and to respond to them appropriately. In the past, simple statistic methods or handwritten templates and rules were used for the constructions of chatbot architectures. With the increasing learning capabilities, end-to-end neural networks have taken the place of these models in around 2015. Especially now, the encoder-decoder recurrent model is dominant in the modeling of conversations. This architecture is taken from the neural machine translation domain, and it performed very well there. Until now, plenty of features and variations are introduced that have remarkably enhanced the conversational capabilities of chatbots. In this paper, we performed a detailed survey on recent literature. We examined many publications from the last five years, which are related to chatbots. Then we presented different related works to our subject, and the AI concepts needed to build an intelligent conversational agent based on deep learning models Finally, we presented a functional architecture that we propose to build an intelligent chatbot for health care assistance.
{"title":"A Smart Chatbot Architecture based NLP and Machine Learning for Health Care Assistance","authors":"Soufyane Ayanouz, Boudhir Anouar Abdelhakim, M. Benahmed","doi":"10.1145/3386723.3387897","DOIUrl":"https://doi.org/10.1145/3386723.3387897","url":null,"abstract":"A chatbot or conversational agent is a software that can communicate with a human by using natural language. One of the essential tasks in artificial intelligence and natural language processing is the modeling of conversation. Since the beginning of artificial intelligence, its been the hardest challenge to create a good chatbot. Although chatbots can perform many tasks, the primary function they have to play is to understand the utterances of humans and to respond to them appropriately. In the past, simple statistic methods or handwritten templates and rules were used for the constructions of chatbot architectures. With the increasing learning capabilities, end-to-end neural networks have taken the place of these models in around 2015. Especially now, the encoder-decoder recurrent model is dominant in the modeling of conversations. This architecture is taken from the neural machine translation domain, and it performed very well there. Until now, plenty of features and variations are introduced that have remarkably enhanced the conversational capabilities of chatbots. In this paper, we performed a detailed survey on recent literature. We examined many publications from the last five years, which are related to chatbots. Then we presented different related works to our subject, and the AI concepts needed to build an intelligent conversational agent based on deep learning models Finally, we presented a functional architecture that we propose to build an intelligent chatbot for health care assistance.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127714093","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}
Several studies have identified the importance of knowledge domain in the intelligent tutoring system. However, this system required a knowledge processing especially in the expert model. In this paper, we report that the combination of the state of the activity (Implicit/ explicit) and the knowledge processing of: declarative, procedural and conditional knowledge is mandated to compare the learner's behavior with that of an expert in regard to assessing their knowledge. The implementation of the expert model problem will be executed using the Bayesian network. For that purpose, the integration of the Bayes Network will be: the probability of the types of Knowledge (Declarative, Procedural or Conditional) and the choice is based on two criteria; the first one is the type of assessment (Memorization, Administration, Expertise) and the status (Explicit/Implicit).
{"title":"Knowledge Management in the Expert Model of the Smart Tutoring System","authors":"Fatima-Zohra Hibbi, O. Abdoun, Haimoudi El Khatir","doi":"10.1145/3386723.3387895","DOIUrl":"https://doi.org/10.1145/3386723.3387895","url":null,"abstract":"Several studies have identified the importance of knowledge domain in the intelligent tutoring system. However, this system required a knowledge processing especially in the expert model. In this paper, we report that the combination of the state of the activity (Implicit/ explicit) and the knowledge processing of: declarative, procedural and conditional knowledge is mandated to compare the learner's behavior with that of an expert in regard to assessing their knowledge. The implementation of the expert model problem will be executed using the Bayesian network. For that purpose, the integration of the Bayes Network will be: the probability of the types of Knowledge (Declarative, Procedural or Conditional) and the choice is based on two criteria; the first one is the type of assessment (Memorization, Administration, Expertise) and the status (Explicit/Implicit).","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134380458","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}
The evolution of the IoT field and its strong presence in multiple domains has raised new security challenges and concerns, which explain the large number of existing studies on this phenomenon. Despite the fact that many security solutions have been applied, security threats and vulnerabilities remain present with new leaks discovery and malicious attempt to gain unauthorized access. In this research, we tackle this problem by providing a new solution of implementing open source IDS (Intrusion Detection Systems) into an IoT architecture and we perform a comprehensive study of the performance of our selected IDS regarding their detection rate and usage consumption. The proposed model is innovative since it brings a novel approach of implementing existing IDSs over the WBANs network taking into consideration all specifications and characteristics of the different layers that compose the architecture of the IoT system implemented to monitor human health.
{"title":"Performance Assessment of Open Source IDS for improving IoT Architecture Security implemented on WBANs","authors":"Mouna Boujrad, S. Lazaar, M. Hassine","doi":"10.1145/3386723.3387892","DOIUrl":"https://doi.org/10.1145/3386723.3387892","url":null,"abstract":"The evolution of the IoT field and its strong presence in multiple domains has raised new security challenges and concerns, which explain the large number of existing studies on this phenomenon. Despite the fact that many security solutions have been applied, security threats and vulnerabilities remain present with new leaks discovery and malicious attempt to gain unauthorized access. In this research, we tackle this problem by providing a new solution of implementing open source IDS (Intrusion Detection Systems) into an IoT architecture and we perform a comprehensive study of the performance of our selected IDS regarding their detection rate and usage consumption. The proposed model is innovative since it brings a novel approach of implementing existing IDSs over the WBANs network taking into consideration all specifications and characteristics of the different layers that compose the architecture of the IoT system implemented to monitor human health.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115785828","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}
Nur Nadira Izlyn Kamaruddin, A. Mohamed, Syaripah Ruzaini Syed Aris
Online advertising has captured prominence attention in most of the advertisement channel along with current revolution of technology era. Its commercial value has grown drastically over the years. In order to maximize commercial value, effective elements of online advertisement which may influence toward consumer purchasing behavior should be considered. The primary purpose of this study is to provide effective conceptual model of online advertising context that influence consumer purchasing behavior. Notification of advertisement in digital media has not shown significant increase. It happens due to lack of attractive components of online advertising content that perceived by consumer which lead to deficit amount of consumer purchasing from online advertisement. Therefore, the rise of online advertising on consumer purchasing behavior is reviewed in this study. The methods of analyzing, classifying and prioritizing of the related components are reviewed and introduced. The mediums and effective elements of online advertising content as perceived by consumer namely the consumers' attitude towards advertising as well as the factor of decision to purchase and consumer purchasing behavior are being examined. The conceptual model of online advertising elements that influence consumer behavior is portrayed and elaborated. In particular, this research uncovers effective elements and its impact toward online advertising of consumer purchasing behavior and the theoretical contributions are discussed accordingly.
{"title":"Online Advertising on Consumer Purchasing Behavior: Effective Elements and its Impact","authors":"Nur Nadira Izlyn Kamaruddin, A. Mohamed, Syaripah Ruzaini Syed Aris","doi":"10.1145/3386723.3387854","DOIUrl":"https://doi.org/10.1145/3386723.3387854","url":null,"abstract":"Online advertising has captured prominence attention in most of the advertisement channel along with current revolution of technology era. Its commercial value has grown drastically over the years. In order to maximize commercial value, effective elements of online advertisement which may influence toward consumer purchasing behavior should be considered. The primary purpose of this study is to provide effective conceptual model of online advertising context that influence consumer purchasing behavior. Notification of advertisement in digital media has not shown significant increase. It happens due to lack of attractive components of online advertising content that perceived by consumer which lead to deficit amount of consumer purchasing from online advertisement. Therefore, the rise of online advertising on consumer purchasing behavior is reviewed in this study. The methods of analyzing, classifying and prioritizing of the related components are reviewed and introduced. The mediums and effective elements of online advertising content as perceived by consumer namely the consumers' attitude towards advertising as well as the factor of decision to purchase and consumer purchasing behavior are being examined. The conceptual model of online advertising elements that influence consumer behavior is portrayed and elaborated. In particular, this research uncovers effective elements and its impact toward online advertising of consumer purchasing behavior and the theoretical contributions are discussed accordingly.","PeriodicalId":139072,"journal":{"name":"Proceedings of the 3rd International Conference on Networking, Information Systems & Security","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122113839","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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