Pub Date : 2019-11-01DOI: 10.1109/ICISS48059.2019.8969841
Firdaus Basbeth, U. Sedyowidodo, Arief Sumanto
Unceasing growth of population and urbanization, have intensified innovative ways to handle social and environmental impact. The smart city concept supports the idea of environmental sustainability and social sustainability as its main to address the challenges arise with issues such as: urbanization, population growth, greenhouse gas emissions, waste management, education and illiteracy through the deployment of innovative technologies. The growing interest in the smart city and the needs to solve those challenges lead to social innovation, creation of applications and technology development. The use of mobile application e.g. smart weather forecasting, community development, and smart transportation, which offers intelligent services influences population directly and lead to smart city orientation. Basically, smart city is mainly made for and by technology savvy people, whilst community is consisting of many varieties of citizens from silent generation to Z generation. In spite of a sizeable body of research describing smart city definitions, the architecture, and the study on how smart city’s performance should be assessed, the moderating role of tech savvy population in the relationship between mobile application usage and smart city orientation has rarely been examined. Therefore, this study highlights the role of tech savvy citizen in moderating the relationship between mobile applications usage towards the intention of smart city. The paper presents an overview of the relationship between mobile application usage and smart cities orientation, followed by the literature review and methodology of the research. Finally, we present the expected result and implication of the result.
{"title":"Mobile Application and Smart City Orientation: The Moderating Role of Tech Savvy Population","authors":"Firdaus Basbeth, U. Sedyowidodo, Arief Sumanto","doi":"10.1109/ICISS48059.2019.8969841","DOIUrl":"https://doi.org/10.1109/ICISS48059.2019.8969841","url":null,"abstract":"Unceasing growth of population and urbanization, have intensified innovative ways to handle social and environmental impact. The smart city concept supports the idea of environmental sustainability and social sustainability as its main to address the challenges arise with issues such as: urbanization, population growth, greenhouse gas emissions, waste management, education and illiteracy through the deployment of innovative technologies. The growing interest in the smart city and the needs to solve those challenges lead to social innovation, creation of applications and technology development. The use of mobile application e.g. smart weather forecasting, community development, and smart transportation, which offers intelligent services influences population directly and lead to smart city orientation. Basically, smart city is mainly made for and by technology savvy people, whilst community is consisting of many varieties of citizens from silent generation to Z generation. In spite of a sizeable body of research describing smart city definitions, the architecture, and the study on how smart city’s performance should be assessed, the moderating role of tech savvy population in the relationship between mobile application usage and smart city orientation has rarely been examined. Therefore, this study highlights the role of tech savvy citizen in moderating the relationship between mobile applications usage towards the intention of smart city. The paper presents an overview of the relationship between mobile application usage and smart cities orientation, followed by the literature review and methodology of the research. Finally, we present the expected result and implication of the result.","PeriodicalId":125643,"journal":{"name":"2019 International Conference on ICT for Smart Society (ICISS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124918142","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 : 2019-11-01DOI: 10.1109/ICISS48059.2019.8969840
Hasna Ardina, I. G. Bagus Baskara Nugraha
Blockchain system is distributed and decentralized that make it can be applied to develop a tamper proof-employee attendance system. There are many attendance systems have been developed but most of it still use conventional systems and databases that have not been distributed yet. A conventional databases do not have special features in checking whether a piece of information has experienced unauthorized changes. On a blockchain based system, no administrator permission is allowed to editing or deleting data. Someone who inserts an information record on the blockchain will not be able to deny that he is doing the activity. Each party on the blockchain has access to the whole database and history. The blockchain-based employee attendance system is required to provide a database that keeps its reliability and integrity and tamper proof.
{"title":"Design of A Blockchain-based Employee Attendance System","authors":"Hasna Ardina, I. G. Bagus Baskara Nugraha","doi":"10.1109/ICISS48059.2019.8969840","DOIUrl":"https://doi.org/10.1109/ICISS48059.2019.8969840","url":null,"abstract":"Blockchain system is distributed and decentralized that make it can be applied to develop a tamper proof-employee attendance system. There are many attendance systems have been developed but most of it still use conventional systems and databases that have not been distributed yet. A conventional databases do not have special features in checking whether a piece of information has experienced unauthorized changes. On a blockchain based system, no administrator permission is allowed to editing or deleting data. Someone who inserts an information record on the blockchain will not be able to deny that he is doing the activity. Each party on the blockchain has access to the whole database and history. The blockchain-based employee attendance system is required to provide a database that keeps its reliability and integrity and tamper proof.","PeriodicalId":125643,"journal":{"name":"2019 International Conference on ICT for Smart Society (ICISS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113942384","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 : 2019-11-01DOI: 10.1109/ICISS48059.2019.8969819
D. Gustian, A. Darmawan, Muhamad Ikhsan Tohir, D. Supardi, S. Nurjanah, Anggy Pradifta Junfihrana
One of the keys of the Broiler farm is in the initial process of choosing the chicken seeds or known as the day DoC. Some criteria are free special diseases of the mushroom, derived from good quality chicken and so on. The problem is that many electoral processes can make it difficult for farmers and companies to choose good quality broiler chickens. Plus the limited ability of farmers to choose broiler chickens, because they still choose them manually. The research is divided into 3 phases i.e. using AHP to sort the criteria of weights that exist among them the first order free of disease with a weight of 0.207, normal body with a weight of 0.174, weight according to the standard with weights 0.172 and Beyond. While Fuzzy CMeans is used for cluster processes in monitoring the quality level of each chicken nursery process by dividing 3 clusters of cluster 1 as much as 410 breeders (96.70%), a cluster of 2 as many as 12 breeders (2.83%) and cluster 3 as many as 2 farmers (0.47%). The second phase is used by the Decision Tree C 4.5 to process the classification of the selection process whether it enters the category A (good), B (Enough) and C (less). While the third phase is still in development research. The result of this classification process gives the info that the Decision Tree C 4.5 works well marked with a validation accuracy value of about 92.03% with a RoC value of about 0881. This research provides a solution for companies to be able to monitor from 3 parts, they are the inputs, processes and outputs of the farmer's chicken nursery. Contributions for the company are able to reduce losses caused by the fault of the three sections so that the company's profits will increase.
{"title":"Selecting Quality Broiler Chicken using Data Mining Technique","authors":"D. Gustian, A. Darmawan, Muhamad Ikhsan Tohir, D. Supardi, S. Nurjanah, Anggy Pradifta Junfihrana","doi":"10.1109/ICISS48059.2019.8969819","DOIUrl":"https://doi.org/10.1109/ICISS48059.2019.8969819","url":null,"abstract":"One of the keys of the Broiler farm is in the initial process of choosing the chicken seeds or known as the day DoC. Some criteria are free special diseases of the mushroom, derived from good quality chicken and so on. The problem is that many electoral processes can make it difficult for farmers and companies to choose good quality broiler chickens. Plus the limited ability of farmers to choose broiler chickens, because they still choose them manually. The research is divided into 3 phases i.e. using AHP to sort the criteria of weights that exist among them the first order free of disease with a weight of 0.207, normal body with a weight of 0.174, weight according to the standard with weights 0.172 and Beyond. While Fuzzy CMeans is used for cluster processes in monitoring the quality level of each chicken nursery process by dividing 3 clusters of cluster 1 as much as 410 breeders (96.70%), a cluster of 2 as many as 12 breeders (2.83%) and cluster 3 as many as 2 farmers (0.47%). The second phase is used by the Decision Tree C 4.5 to process the classification of the selection process whether it enters the category A (good), B (Enough) and C (less). While the third phase is still in development research. The result of this classification process gives the info that the Decision Tree C 4.5 works well marked with a validation accuracy value of about 92.03% with a RoC value of about 0881. This research provides a solution for companies to be able to monitor from 3 parts, they are the inputs, processes and outputs of the farmer's chicken nursery. Contributions for the company are able to reduce losses caused by the fault of the three sections so that the company's profits will increase.","PeriodicalId":125643,"journal":{"name":"2019 International Conference on ICT for Smart Society (ICISS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129525382","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 : 2019-11-01DOI: 10.1109/ICISS48059.2019.8969797
Shafiera Amalia, Agus Wahyuadianto
Mini Lab Food Security Program is a smart city program initiated by Bandung City Government which adopted collaborative governance mechanism. This study scrutinizes collaborative governance model in this program since it was implemented in 2016. Using descriptive qualitative approach, this study results in two outputs. Collaborative model was explained which was covering actor and role description, trust building, communication, and commitment. A cost analysis model was drawn to give detail picture relating to collaboration process. This budgeting projection is useful for replication purposes and further review.
{"title":"Drawing Collaborative Model for Food Security","authors":"Shafiera Amalia, Agus Wahyuadianto","doi":"10.1109/ICISS48059.2019.8969797","DOIUrl":"https://doi.org/10.1109/ICISS48059.2019.8969797","url":null,"abstract":"Mini Lab Food Security Program is a smart city program initiated by Bandung City Government which adopted collaborative governance mechanism. This study scrutinizes collaborative governance model in this program since it was implemented in 2016. Using descriptive qualitative approach, this study results in two outputs. Collaborative model was explained which was covering actor and role description, trust building, communication, and commitment. A cost analysis model was drawn to give detail picture relating to collaboration process. This budgeting projection is useful for replication purposes and further review.","PeriodicalId":125643,"journal":{"name":"2019 International Conference on ICT for Smart Society (ICISS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129945851","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 : 2019-11-01DOI: 10.1109/ICISS48059.2019.8969850
P. Telnoni, Reza Budiawan, Mutia Qana’a
As Artificial Intelligence (AI) and Machine Learning (ML) gaining momentum on industry and academic field, a deeper understanding for AI and ML are highly required. One of the most popular sub-field in this field is text analysis. This paper will discuss the performance of classification methods for text-based data and give the best choices of classification method in term of accuracy and training time, so that will help ML enthusiast to build ML project that does not require high computational cost. This paper aimed to give recommendation to practitioner and academic about which classifier best for text classification. This paper will limit its study in supervised learning only. The tested algorithm will be Support Vector Machine, Logistic Regression, Naive Bayes, Random Forest, and K-Nearest Neighbor. To simplify the project, text will be labelled into single-label data, not multi-label. The test shows that SVM gives best result, in term of accuracy and training time among other methods.
{"title":"Comparison of Machine Learning Classification Method on Text-based Case in Twitter","authors":"P. Telnoni, Reza Budiawan, Mutia Qana’a","doi":"10.1109/ICISS48059.2019.8969850","DOIUrl":"https://doi.org/10.1109/ICISS48059.2019.8969850","url":null,"abstract":"As Artificial Intelligence (AI) and Machine Learning (ML) gaining momentum on industry and academic field, a deeper understanding for AI and ML are highly required. One of the most popular sub-field in this field is text analysis. This paper will discuss the performance of classification methods for text-based data and give the best choices of classification method in term of accuracy and training time, so that will help ML enthusiast to build ML project that does not require high computational cost. This paper aimed to give recommendation to practitioner and academic about which classifier best for text classification. This paper will limit its study in supervised learning only. The tested algorithm will be Support Vector Machine, Logistic Regression, Naive Bayes, Random Forest, and K-Nearest Neighbor. To simplify the project, text will be labelled into single-label data, not multi-label. The test shows that SVM gives best result, in term of accuracy and training time among other methods.","PeriodicalId":125643,"journal":{"name":"2019 International Conference on ICT for Smart Society (ICISS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128900092","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 : 2019-11-01DOI: 10.1109/ICISS48059.2019.8969827
Natalia Limantara, R. Kosala, B. Ranti, S. Supangkat
The use of smart mobile devices in the learning process is one of the factors that can influence the success of the learning process. Lecturers are a key factor in the success of this implementation. How lecturers can be ready to accept the use of a smart mobile device in the middle of the learning process that is still considered a nuisance. The purpose of this study is to analyze what factors affect lecturers’ readiness to use smart mobile devices into learning activities and also provide an overview of how IT Governance implementation can help the implementation of smart mobile devices. The researcher took a sample of lecturers who actively taught at the Information Systems Department, BINUS University in the even semester 2018 period. Authors used PLS-SEM to analyze data. The results of this study show whether computer self-efficacy, subjective norms and relative benefits have a significant impact on the willingness of teachers to integrate smart mobile devices into the learning process.
{"title":"Human and Technology Factors in the Readiness to Use Smart Mobile Devices in Learning Activities","authors":"Natalia Limantara, R. Kosala, B. Ranti, S. Supangkat","doi":"10.1109/ICISS48059.2019.8969827","DOIUrl":"https://doi.org/10.1109/ICISS48059.2019.8969827","url":null,"abstract":"The use of smart mobile devices in the learning process is one of the factors that can influence the success of the learning process. Lecturers are a key factor in the success of this implementation. How lecturers can be ready to accept the use of a smart mobile device in the middle of the learning process that is still considered a nuisance. The purpose of this study is to analyze what factors affect lecturers’ readiness to use smart mobile devices into learning activities and also provide an overview of how IT Governance implementation can help the implementation of smart mobile devices. The researcher took a sample of lecturers who actively taught at the Information Systems Department, BINUS University in the even semester 2018 period. Authors used PLS-SEM to analyze data. The results of this study show whether computer self-efficacy, subjective norms and relative benefits have a significant impact on the willingness of teachers to integrate smart mobile devices into the learning process.","PeriodicalId":125643,"journal":{"name":"2019 International Conference on ICT for Smart Society (ICISS)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128097470","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 : 2019-11-01DOI: 10.1109/ICISS48059.2019.8969832
Anderson King Junior, Suharjito, Novan Zulkarnain, Devriady Pratama, Eric Gunawan, Ditdit Nugeraha Utama
In the K-Means algorithm, the determination of the center point coordinates (centroid) directly affects the quality of the clustering process. Determination of the coordinates of the center point (centroid) is generally done by generating random numbers and each instance will then be placed based on proximity to random numbers generated. Determining a good centroid will prevent the occurrence of local optima problems in K-Means. The GenClust++ algorithm is a pretty good algorithm in determining centroid. However, what needs to be considered is the influence of the selection and crossover process on the performance of clustering. This study will discuss the combination of selection and crossover processes that are good in the process of determining the centroid. Performance measurement method will be based on the measurement of Mean Square Error and distance calculation using Euclidean Distance. The results show that the Roulette Wheel Selection and Whole Arithmetic Crossover selection processes will give the best performance for the GenClust++ Algorithm.
{"title":"The Effect Analysis of Crossover and Selection Methods on the Performance of GenClust++ Algorithm","authors":"Anderson King Junior, Suharjito, Novan Zulkarnain, Devriady Pratama, Eric Gunawan, Ditdit Nugeraha Utama","doi":"10.1109/ICISS48059.2019.8969832","DOIUrl":"https://doi.org/10.1109/ICISS48059.2019.8969832","url":null,"abstract":"In the K-Means algorithm, the determination of the center point coordinates (centroid) directly affects the quality of the clustering process. Determination of the coordinates of the center point (centroid) is generally done by generating random numbers and each instance will then be placed based on proximity to random numbers generated. Determining a good centroid will prevent the occurrence of local optima problems in K-Means. The GenClust++ algorithm is a pretty good algorithm in determining centroid. However, what needs to be considered is the influence of the selection and crossover process on the performance of clustering. This study will discuss the combination of selection and crossover processes that are good in the process of determining the centroid. Performance measurement method will be based on the measurement of Mean Square Error and distance calculation using Euclidean Distance. The results show that the Roulette Wheel Selection and Whole Arithmetic Crossover selection processes will give the best performance for the GenClust++ Algorithm.","PeriodicalId":125643,"journal":{"name":"2019 International Conference on ICT for Smart Society (ICISS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131413942","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 : 2019-11-01DOI: 10.1109/ICISS48059.2019.8969821
Mohammad Isa, Albarda
Incident management has play an important role in the business processes of service provider. Well implemented incident management can increase the availability of services and as well as user satisfaction level. However, incident management is a dominant process that consumes resources, both time and cost. Artificial intelligence-based technologies can be utilized to improve the efficiency of the incident management process. Thus, organizations can receive added value from more efficient process as well as more accurate information. This research proposed machine learning machine learning model for incident categorization and incident duration prediction that could be adopted into business process of incident handling.
{"title":"Designing Supervised Learning-Based Incident Management Model : Case Study: Broadband Network Service Provider","authors":"Mohammad Isa, Albarda","doi":"10.1109/ICISS48059.2019.8969821","DOIUrl":"https://doi.org/10.1109/ICISS48059.2019.8969821","url":null,"abstract":"Incident management has play an important role in the business processes of service provider. Well implemented incident management can increase the availability of services and as well as user satisfaction level. However, incident management is a dominant process that consumes resources, both time and cost. Artificial intelligence-based technologies can be utilized to improve the efficiency of the incident management process. Thus, organizations can receive added value from more efficient process as well as more accurate information. This research proposed machine learning machine learning model for incident categorization and incident duration prediction that could be adopted into business process of incident handling.","PeriodicalId":125643,"journal":{"name":"2019 International Conference on ICT for Smart Society (ICISS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123538630","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 : 2019-11-01DOI: 10.1109/ICISS48059.2019.8969805
S. Wibowo, Tesar Sandikapura
Presidential Decree on One Data Indonesia is intended to govern data produced by central agencies and local agencies to support planning, implementation, evaluation, and development control, including one of them is the local tax. It is a Big Data development contains a lot of data from the central and local government of Indonesia. The defining factors of data collection on Big Data are volume, velocity, variety, and veracity. Volume and velocity state how much and how soon the data is generated. Variety states the condition of the data is structured or not, while veracity speaks the level of trust in data validity. Data veracity is a big problem on Big Data Analytics and using data integrity protection feature and other methods, Blockchain can offer solutions to improve data interoperability, security, and veracity.
{"title":"Improving Data Security, Interoperability, and Veracity using Blockchain for One Data Governance, Case Study of Local Tax Big Data","authors":"S. Wibowo, Tesar Sandikapura","doi":"10.1109/ICISS48059.2019.8969805","DOIUrl":"https://doi.org/10.1109/ICISS48059.2019.8969805","url":null,"abstract":"Presidential Decree on One Data Indonesia is intended to govern data produced by central agencies and local agencies to support planning, implementation, evaluation, and development control, including one of them is the local tax. It is a Big Data development contains a lot of data from the central and local government of Indonesia. The defining factors of data collection on Big Data are volume, velocity, variety, and veracity. Volume and velocity state how much and how soon the data is generated. Variety states the condition of the data is structured or not, while veracity speaks the level of trust in data validity. Data veracity is a big problem on Big Data Analytics and using data integrity protection feature and other methods, Blockchain can offer solutions to improve data interoperability, security, and veracity.","PeriodicalId":125643,"journal":{"name":"2019 International Conference on ICT for Smart Society (ICISS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115907314","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 : 2019-11-01DOI: 10.1109/ICISS48059.2019.8969783
A. Aisha, I. Sudirman, Joe Monang, I. Prasetyo
The implementation of e-learning for SMEs is recommended because it is cost-effective and offers flexibility for usage. However, the current e-learning system for SMEs provided by the Government has limitations. This study aims to develop a website based e-learning system for SMEs. The proposed e-learning system will have two main subsystems, namely access to the framework and training material, and self-assessment. This e-learning system is developed to accommodate self-learning mechanism intending to improve relevant SMEs competencies for business successes.
{"title":"A Web Based Interactive e-Learning Systems for SMEs in Indonesia","authors":"A. Aisha, I. Sudirman, Joe Monang, I. Prasetyo","doi":"10.1109/ICISS48059.2019.8969783","DOIUrl":"https://doi.org/10.1109/ICISS48059.2019.8969783","url":null,"abstract":"The implementation of e-learning for SMEs is recommended because it is cost-effective and offers flexibility for usage. However, the current e-learning system for SMEs provided by the Government has limitations. This study aims to develop a website based e-learning system for SMEs. The proposed e-learning system will have two main subsystems, namely access to the framework and training material, and self-assessment. This e-learning system is developed to accommodate self-learning mechanism intending to improve relevant SMEs competencies for business successes.","PeriodicalId":125643,"journal":{"name":"2019 International Conference on ICT for Smart Society (ICISS)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124776222","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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