The availability of LPG in the community is a sensitive issue. If there is a shortage, it has the potential to cause chaos and inflation. The final consumers, namely households and micro business stalls, will generally be disloyal. They are not tied to one particular store to get the LPG they need. Since the number of tanks in circulation will remain constant, the analysis of LPG availability can be focused on the number of tanks. Continuous simulation method with system dynamics is generally used in system growth analysis. In this paper the method is utilized to model the discrete movement of tanks circulating in the community which in this case is represented in a much smaller system, consisting of filling stations, agents, and stores. The modeling results provide a sufficient picture of how the availability of the tank can be optimized appropriately.
{"title":"System Dynamics Modeling of Multi-Channel Supply Chain System: A Hypothetical LPG Distribution with Disloyal Household Customers","authors":"P. Murdapa, P. Karningsih, I. N. Pujawan","doi":"10.24002/ijis.v5i1.6025","DOIUrl":"https://doi.org/10.24002/ijis.v5i1.6025","url":null,"abstract":"The availability of LPG in the community is a sensitive issue. If there is a shortage, it has the potential to cause chaos and inflation. The final consumers, namely households and micro business stalls, will generally be disloyal. They are not tied to one particular store to get the LPG they need. Since the number of tanks in circulation will remain constant, the analysis of LPG availability can be focused on the number of tanks. Continuous simulation method with system dynamics is generally used in system growth analysis. In this paper the method is utilized to model the discrete movement of tanks circulating in the community which in this case is represented in a much smaller system, consisting of filling stations, agents, and stores. The modeling results provide a sufficient picture of how the availability of the tank can be optimized appropriately.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"121 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80221201","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}
As an instance of a distributed computing system, opportunistic networks facilitate message dissemination in a store-carry-forward manner. In this setting, the mobile devices are communicating in opportunistic contacts as they move across the network areas. However, the movement of these mobile devices is exclusively reliant on the mobility of their human owner, thereby limiting the likelihood of contact. The current state of the art typically simulates human movement based on randomness, which is unsuitable for representing how people move in groups. Therefore, this paper proposes an implementation of a group-based human mobility model to simulate device-to-device communication in opportunistic networks. In this model, individuals are able to move as a set within a group and have the ability to join and leave the group dynamically We built the model in BonnMotion and subsequently implemented it in an opportunistic environment simulator, ONE Simulator. To evaluate the proposed model, we compared them to the random-based model as a benchmark. Subsequently, we assess the impact of the movement model on two major areas of network performance: message delivery performance and resource utilization, such as nodes’ energy consumption. We are concerned about these aspects since the mobile agents have limited resources yet are expected to achieve a high rate of message delivery as well. The simulation results show that our model outperformed the random-based model in terms of the number of successfully delivered messages and average delay. However, the number of message replications and the energy consumption is fairly higher than those of the benchmarks.
{"title":"Implementation of Group-Based Human Movement Model in Opportunistic Network","authors":"Vittalis Ayu, B. Soelistijanto","doi":"10.24002/ijis.v5i1.6164","DOIUrl":"https://doi.org/10.24002/ijis.v5i1.6164","url":null,"abstract":"As an instance of a distributed computing system, opportunistic networks facilitate message dissemination in a store-carry-forward manner. In this setting, the mobile devices are communicating in opportunistic contacts as they move across the network areas. However, the movement of these mobile devices is exclusively reliant on the mobility of their human owner, thereby limiting the likelihood of contact. The current state of the art typically simulates human movement based on randomness, which is unsuitable for representing how people move in groups. Therefore, this paper proposes an implementation of a group-based human mobility model to simulate device-to-device communication in opportunistic networks. In this model, individuals are able to move as a set within a group and have the ability to join and leave the group dynamically We built the model in BonnMotion and subsequently implemented it in an opportunistic environment simulator, ONE Simulator. To evaluate the proposed model, we compared them to the random-based model as a benchmark. Subsequently, we assess the impact of the movement model on two major areas of network performance: message delivery performance and resource utilization, such as nodes’ energy consumption. We are concerned about these aspects since the mobile agents have limited resources yet are expected to achieve a high rate of message delivery as well. The simulation results show that our model outperformed the random-based model in terms of the number of successfully delivered messages and average delay. However, the number of message replications and the energy consumption is fairly higher than those of the benchmarks.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91382439","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}
Sesilia Shania, Mohammad Farid Naufal, Vincentius Riandaru Prasetyo, Mohd Sanusi Bin Azmi
Sign language is a language used to communicate by utilizing gestures and facial expressions. This study focuses on classification of Bahasa Isyarat Indonesia (BISINDO). There are still many people who have difficulty communicating with the deaf people. This study builds video-based translator system using Convolutional Neural Network (CNN) with transfer learning which is commonly used in computer vision especially in image classification. Transfer learning used in this study are a MobileNetV2, ResNet50V2, and Xception. This study uses 11 different commonly used vocabularies in BISINDO. Predictions will be made in real-time scenario using a webcam. In addition, the system given good results in the experiment with an interaction approach between one pair of deaf and normal people. From all the experiments, it was found that the Xception architectures has the best F1 Score of 98.5%.
{"title":"Translator of Indonesian Sign Language Video using Convolutional Neural Network with Transfer Learning","authors":"Sesilia Shania, Mohammad Farid Naufal, Vincentius Riandaru Prasetyo, Mohd Sanusi Bin Azmi","doi":"10.24002/ijis.v5i1.5865","DOIUrl":"https://doi.org/10.24002/ijis.v5i1.5865","url":null,"abstract":"\u0000Sign language is a language used to communicate by utilizing gestures and facial expressions. This study focuses on classification of Bahasa Isyarat Indonesia (BISINDO). There are still many people who have difficulty communicating with the deaf people. This study builds video-based translator system using Convolutional Neural Network (CNN) with transfer learning which is commonly used in computer vision especially in image classification. Transfer learning used in this study are a MobileNetV2, ResNet50V2, and Xception. This study uses 11 different commonly used vocabularies in BISINDO. Predictions will be made in real-time scenario using a webcam. In addition, the system given good results in the experiment with an interaction approach between one pair of deaf and normal people. From all the experiments, it was found that the Xception architectures has the best F1 Score of 98.5%. \u0000","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72675009","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}
One of the influential learning resources utilized today is a web-based learning management system. The web-based e-learning’s usability is also influenced by the user interface. In measuring usability, eye-tracking technology can be employed to examine eye gaze of an individual when looks at a specific point at a certain time. The use of eye-tracking is beneficial in obtaining objective data. This study aims to evaluate the usability of UAJY Learning Management System website interface and examine the user's interaction with the website interface. Thirty-five participants were recruited in a usability testing experiment. Participants were asked to do three tasks related to the use of e-learning features while their eye movements were recorded. The USE Questionnaire and task-related question data were processed using statistical descriptive methods and eye movement data generated into heatmaps. The Usefulness, Ease of Use, Ease of Learn, and Satisfaction aspects of the UAJY LMS gains more than 80% feasibility percentage. Overall results of feasibility categorized the UAJY LMS as Very Feasible. There was no difference found in usability aspects between gender, faculty background, and eye condition groups. Heatmaps results show that navigational elements in the LMS are utilized properly and successfully help participants in performing tasks.
{"title":"Evaluation of UAJY Learning Management System’s Usability using USE Questionnaire and Eye-tracking","authors":"Aloysius Gonzaga Pradnya Sidhawara","doi":"10.24002/ijis.v4i2.5273","DOIUrl":"https://doi.org/10.24002/ijis.v4i2.5273","url":null,"abstract":"One of the influential learning resources utilized today is a web-based learning management system. The web-based e-learning’s usability is also influenced by the user interface. In measuring usability, eye-tracking technology can be employed to examine eye gaze of an individual when looks at a specific point at a certain time. The use of eye-tracking is beneficial in obtaining objective data. This study aims to evaluate the usability of UAJY Learning Management System website interface and examine the user's interaction with the website interface. Thirty-five participants were recruited in a usability testing experiment. Participants were asked to do three tasks related to the use of e-learning features while their eye movements were recorded. The USE Questionnaire and task-related question data were processed using statistical descriptive methods and eye movement data generated into heatmaps. The Usefulness, Ease of Use, Ease of Learn, and Satisfaction aspects of the UAJY LMS gains more than 80% feasibility percentage. Overall results of feasibility categorized the UAJY LMS as Very Feasible. There was no difference found in usability aspects between gender, faculty background, and eye condition groups. Heatmaps results show that navigational elements in the LMS are utilized properly and successfully help participants in performing tasks.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"149 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83129377","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}
Game products are one of the media to provide pleasure, satisfaction and knowledge for users. Game Selera Nusantara is a game product created by a game studio in Yogyakarta, namely Gambir Studio, created with the aim of providing pleasure, satisfaction and knowledge to its users. In order for the goal of the Selera Nusantara Game to be achieved, a game design by a user-centered game designer is needed. Game Selera Nusantara is a game with the Casual genre that has a target audience of children and teenagers with the main goal of introducing Nusantara cuisine. The good aim of the Selera Nusantara Game which introduces the culture of the archipelago is the basis of this research by assessing the quality of the game so that it can be accepted by the target audience optimally. The User Experience method with Game Design Factor Questionaire and compared with the results of interviews with game designers from Game Selera Nusantara used in this study provides an analysis of the quality of the game quantitatively. The results of the analysis show that Game Selera Nusantara has a high score on the criteria of Game Goals, Game Mechanism, Interaction, Fantasy Game, Narrative, Sensation, Game Value, Mystery, Flow, which is more than 90%. This means that the Selera Nusantara game has been able to fulfill the goal of providing pleasure, satisfaction and knowledge to its users in accordance with the design of the game designer.
{"title":"Game Design Factor Questionerin User Experience Analysis on Selera Nusantara Game","authors":"Kathryn Widhiyanti, Kusuma Dewangga, Firas Almukhtar","doi":"10.24002/ijis.v4i2.5449","DOIUrl":"https://doi.org/10.24002/ijis.v4i2.5449","url":null,"abstract":"Game products are one of the media to provide pleasure, satisfaction and knowledge for users. Game Selera Nusantara is a game product created by a game studio in Yogyakarta, namely Gambir Studio, created with the aim of providing pleasure, satisfaction and knowledge to its users. In order for the goal of the Selera Nusantara Game to be achieved, a game design by a user-centered game designer is needed. Game Selera Nusantara is a game with the Casual genre that has a target audience of children and teenagers with the main goal of introducing Nusantara cuisine. The good aim of the Selera Nusantara Game which introduces the culture of the archipelago is the basis of this research by assessing the quality of the game so that it can be accepted by the target audience optimally. The User Experience method with Game Design Factor Questionaire and compared with the results of interviews with game designers from Game Selera Nusantara used in this study provides an analysis of the quality of the game quantitatively. The results of the analysis show that Game Selera Nusantara has a high score on the criteria of Game Goals, Game Mechanism, Interaction, Fantasy Game, Narrative, Sensation, Game Value, Mystery, Flow, which is more than 90%. This means that the Selera Nusantara game has been able to fulfill the goal of providing pleasure, satisfaction and knowledge to its users in accordance with the design of the game designer.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"78 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72435568","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}
Robertus In Nugroho Budisantoso, Antonius Sumarwan
This paper aims to identify entrepreneurial modes towards information technology applications in business during pandemic Covid-19 based on Indonesia SMEs’ stories. This study uses phenomenological approach in discerning 33 Economics students’ reports on SMEs’ ways in relating to social media platforms in the midst of the pandemic as relatively different business instruments driven by information technology along with their encounters to new opportunities within novel landscape of business. The reports indicate a general pattern of three critical stages linked to entrepreneurial challenges namely in the first stage business distortion, in the middle efficiency calculation, and finally available resources allocation. Using two factors i.e. learning capability of the business actors and the sophistication degree of information technology applications, the ways through which entrepreneurs relate to information technology within pandemic context can be identified into four types of mode namely adoption, adaptation, aversion, and abandon. Most of them are in adoption mode, few are in adaptation and abandon modes, and none in aversion mode.
{"title":"Entrepreneurial Modes towards Information Technology Applications in Business during Pandemic Covid-19 Based on Indonesia SMEs’ Stories","authors":"Robertus In Nugroho Budisantoso, Antonius Sumarwan","doi":"10.24002/ijis.v4i2.4840","DOIUrl":"https://doi.org/10.24002/ijis.v4i2.4840","url":null,"abstract":"This paper aims to identify entrepreneurial modes towards information technology applications in business during pandemic Covid-19 based on Indonesia SMEs’ stories. This study uses phenomenological approach in discerning 33 Economics students’ reports on SMEs’ ways in relating to social media platforms in the midst of the pandemic as relatively different business instruments driven by information technology along with their encounters to new opportunities within novel landscape of business. The reports indicate a general pattern of three critical stages linked to entrepreneurial challenges namely in the first stage business distortion, in the middle efficiency calculation, and finally available resources allocation. Using two factors i.e. learning capability of the business actors and the sophistication degree of information technology applications, the ways through which entrepreneurs relate to information technology within pandemic context can be identified into four types of mode namely adoption, adaptation, aversion, and abandon. Most of them are in adoption mode, few are in adaptation and abandon modes, and none in aversion mode.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78146266","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}
S. Riyadi, Yunita Lestari, Cahya Damarjati, K. Ghazali
The SARS-Cov-2 outbreak caused by a coronavirus infection shocked dozens of countries. This disease has spread rapidly and become a new pandemic, a serious threat and even destroys various sectors of life. Along with technological developments, various deep learning models have been developed to classify between Covid-19 and Normal X-ray images of lungs, such as Inception V3, Inception V4 and MobileNet. These models have been separately reported to perform good classification on Covid-19. However, there is no comparison of their performance in classifying Covid-19 on the same data. This research aims to compare the performance of the three mentioned deep learning models in classifying Covid-19 based on X-ray images. The methods involve data collection, pre-processing, training, and testing using the three models. According to 2,169 dataset, the InceptionV3 model obtained an average accuracy value of 99.62%, precision value 99.65%, recall value 99.5%, specificity value 99.5%, and f-score value 99.52%; while the InceptionV4 model obtained an average accuracy value of 97.79%, precision value 98.11%, recall value 90.18%, specificity value 90.18%, and f-score value 97.25%; and the MobileNet model obtained an average accuracy value of 99.67%, precision value 99.77%, recall value 99.38%, specificity value 99.38%, and f-score value of 99.67%. The three models can classify the Covid-19 and Normal X-ray images based on research results, while the MobileNet model achieved the best performance. The model has stable performance in achieving graphic results and has extensive layers; the more layers there are to achieve better accuracy results.
{"title":"Performance Comparison of Deep Learning Models to Detect Covid-19 Based on X-Ray Images","authors":"S. Riyadi, Yunita Lestari, Cahya Damarjati, K. Ghazali","doi":"10.24002/ijis.v4i2.5491","DOIUrl":"https://doi.org/10.24002/ijis.v4i2.5491","url":null,"abstract":"The SARS-Cov-2 outbreak caused by a coronavirus infection shocked dozens of countries. This disease has spread rapidly and become a new pandemic, a serious threat and even destroys various sectors of life. Along with technological developments, various deep learning models have been developed to classify between Covid-19 and Normal X-ray images of lungs, such as Inception V3, Inception V4 and MobileNet. These models have been separately reported to perform good classification on Covid-19. However, there is no comparison of their performance in classifying Covid-19 on the same data. This research aims to compare the performance of the three mentioned deep learning models in classifying Covid-19 based on X-ray images. The methods involve data collection, pre-processing, training, and testing using the three models. According to 2,169 dataset, the InceptionV3 model obtained an average accuracy value of 99.62%, precision value 99.65%, recall value 99.5%, specificity value 99.5%, and f-score value 99.52%; while the InceptionV4 model obtained an average accuracy value of 97.79%, precision value 98.11%, recall value 90.18%, specificity value 90.18%, and f-score value 97.25%; and the MobileNet model obtained an average accuracy value of 99.67%, precision value 99.77%, recall value 99.38%, specificity value 99.38%, and f-score value of 99.67%. The three models can classify the Covid-19 and Normal X-ray images based on research results, while the MobileNet model achieved the best performance. The model has stable performance in achieving graphic results and has extensive layers; the more layers there are to achieve better accuracy results.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87007128","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}
Face recognition is one of the interesting research topics in the field of computer vision. In recent years, deep learning methods, especially the Convolutional Neural Network, have progressed. One of the successes of CNN is in face recognition. Face recognition by computer is a technique done so that the computer can automatically recognize faces in an image. Various researchers have conducted related research on facial recognition. This survey presents researches related to face recognition based on Convolutional Neural Network that has been conducted. The studies used are studies that have been published in the last five years. It was performed to determine the renewal that emerged in face recognition based on Convolutional Neural Network. The basic theory of the Convolutional Neural Network, face recognition, and description of the database used in various researches are also discussed. Hopefully, this survey can provide additional knowledge regarding face recognition based on the Convolutional Neural Network.
{"title":"A Survey of Face Recognition based on Convolutional Neural Network","authors":"R. E. Saragih, Quynh Huong To","doi":"10.24002/ijis.v4i2.5439","DOIUrl":"https://doi.org/10.24002/ijis.v4i2.5439","url":null,"abstract":"Face recognition is one of the interesting research topics in the field of computer vision. In recent years, deep learning methods, especially the Convolutional Neural Network, have progressed. One of the successes of CNN is in face recognition. Face recognition by computer is a technique done so that the computer can automatically recognize faces in an image. Various researchers have conducted related research on facial recognition. This survey presents researches related to face recognition based on Convolutional Neural Network that has been conducted. The studies used are studies that have been published in the last five years. It was performed to determine the renewal that emerged in face recognition based on Convolutional Neural Network. The basic theory of the Convolutional Neural Network, face recognition, and description of the database used in various researches are also discussed. Hopefully, this survey can provide additional knowledge regarding face recognition based on the Convolutional Neural Network.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90506973","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}
Jo Vianto, D. Setyohadi, Anton Satria Prabuwono, M. S. Azmi, Eddy Julianto
Artificial intelligence has developed in various fields. The development became more significant after Neural Networks(NN) began to gain popularity. Convolutional Neural Networks(CNNs) are good at solving problems such as classification and object detection. However, the CNNs model tends to function to solve a specific problem. In the case of both object detection and face recognition it is difficult to make a single model that works well. NoonGil Lens+ is expected to be an approach that can solve both problems at once. As well as being a solution, it is also hoped that this approach can reduce the trade-off of accuracy and execution speed. The approach we propose can be called as Noongil Lens+, a system that connects YOLOv3 and FaceNet. It is inspired from a korean series called ‘STARTUP’. The author only develops the FaceNet model and the proposed system in this paper (NoonGil Lens+). Region Selection, a machine learning-based greedy approach was proposed to determine snapshots to fed into FaceNet for facial identity classification. FaceNet is trained on the CelebA dataset which has gone through the preprocessing process and is validated using the LFW dataset. NoonGil Lens+ was validated using 70 images of 7 celebrities, characters, and athletes. In general, the research was carried out successfully. NoonGil Lens+ using Region Selection has an accuracy of up to 75.2%. The Region Selection execution speed is also faster compared to Cascade Faces.
{"title":"NoonGil Lens+: Second Level Face Recognition from Detected Objects to Decrease Computation and Performance Trade-off","authors":"Jo Vianto, D. Setyohadi, Anton Satria Prabuwono, M. S. Azmi, Eddy Julianto","doi":"10.24002/ijis.v4i2.5488","DOIUrl":"https://doi.org/10.24002/ijis.v4i2.5488","url":null,"abstract":"Artificial intelligence has developed in various fields. The development became more significant after Neural Networks(NN) began to gain popularity. Convolutional Neural Networks(CNNs) are good at solving problems such as classification and object detection. However, the CNNs model tends to function to solve a specific problem. In the case of both object detection and face recognition it is difficult to make a single model that works well. NoonGil Lens+ is expected to be an approach that can solve both problems at once. As well as being a solution, it is also hoped that this approach can reduce the trade-off of accuracy and execution speed. The approach we propose can be called as Noongil Lens+, a system that connects YOLOv3 and FaceNet. It is inspired from a korean series called ‘STARTUP’. The author only develops the FaceNet model and the proposed system in this paper (NoonGil Lens+). Region Selection, a machine learning-based greedy approach was proposed to determine snapshots to fed into FaceNet for facial identity classification. FaceNet is trained on the CelebA dataset which has gone through the preprocessing process and is validated using the LFW dataset. NoonGil Lens+ was validated using 70 images of 7 celebrities, characters, and athletes. In general, the research was carried out successfully. NoonGil Lens+ using Region Selection has an accuracy of up to 75.2%. The Region Selection execution speed is also faster compared to Cascade Faces.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91145020","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}
S. Kamarudin, Ahmad Hidayat Ahmad Khalili, Zakry Fitri Abd. Aziz, K. A. Kamarudin, Amelia Natasya Abdul Wahab
Business activities such as human resources management, payroll, finance, and accounting are crucial for Small and Medium Enterprises (SMEs). Therefore, adopting technologies such as cloud computing is expected to improve SMEs’ efficiency. The migration from current business practices to cloud computing amongst SME entrepreneurs remains a challenge. Therefore, this study presents a short review of cloud computing concepts, the characteristics, types of cloud computing service models, and also cloud computing deployment models. This study highlights the benefits and challenges faced by SMEs entrepreneurs in adopting cloud computing. Also, this study explores the existing cloud computing services provided for SMEs. The present study aims to provide a better understanding of cloud computing’s potential to be applied in helping SMEs manage their business activities.
{"title":"Exploring of Potential of Cloud Computing for Small and Medium Enterprises","authors":"S. Kamarudin, Ahmad Hidayat Ahmad Khalili, Zakry Fitri Abd. Aziz, K. A. Kamarudin, Amelia Natasya Abdul Wahab","doi":"10.24002/ijis.v4i2.5487","DOIUrl":"https://doi.org/10.24002/ijis.v4i2.5487","url":null,"abstract":"Business activities such as human resources management, payroll, finance, and accounting are crucial for Small and Medium Enterprises (SMEs). Therefore, adopting technologies such as cloud computing is expected to improve SMEs’ efficiency. The migration from current business practices to cloud computing amongst SME entrepreneurs remains a challenge. Therefore, this study presents a short review of cloud computing concepts, the characteristics, types of cloud computing service models, and also cloud computing deployment models. This study highlights the benefits and challenges faced by SMEs entrepreneurs in adopting cloud computing. Also, this study explores the existing cloud computing services provided for SMEs. The present study aims to provide a better understanding of cloud computing’s potential to be applied in helping SMEs manage their business activities.","PeriodicalId":34118,"journal":{"name":"Indonesian Journal of Information Systems","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87374054","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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