Akindoyo Oluwatosinloba Omotola, Cheah Waishiang, M. A. Khairuddin, Nurfauza binti Jalil, Eaqerzilla Phang
ICT4D is an acronym for information and communication technologies for development. This acronym represents the many initiatives that are now being carried out in underdeveloped countries all around the globe. These technology-oriented initiatives aim to promote the growth and prosperity of the regions they serve. People from the local community often volunteer their time to serve as program managers when NGOs or governments give funding. The term "sustainability" describes an information and communications technology's capacity to carry out a development project even after the initial funding has run out. The e3value technique will be broken down in this article so that we may better understand how it works. Using various tools for value-based modeling, this method is utilized to create an e-Business model. However, one of the main problems with e-business technologies is that they often get insufficient data to be effective. This study aims to examine the procedures that must be followed to learn more about an e-Business concept and mold it into a form that would allow for its implementation in a technologically and commercially practical manner. In order to gather information on the Long Lamai community's economic activities, a survey is being used in this research. The net value sheet for each of their businesses is then stimulated utilizing the data using E3 value. Initial findings indicate that 5 out of 13 enterprises' net incomes are negative, and each of those five businesses has its roots in a local enterprise. However, the figure does not consider labor costs, taxes, or long-term investments made with government money. We continued the stimulation with sensitivity analysis and scenario-based analysis, which results in total revenue of 1,410,000 for the five enterprises in the fourth year after accounting for taxes and fees in the sensitivity analysis. This opens the door for further research into how discrepancies in wealth and income may arise in the simulation of an economy due to the right use of ICT for long-term development and prosperity. Profitability sheets may be created if certain business model assumptions are specified, such as the monetary value of the commodities produced, distributed, and consumed. These may be used to decide if the project can become profitable for all parties concerned.
{"title":"Value-based modeling and simulation for sustainable ICT4D","authors":"Akindoyo Oluwatosinloba Omotola, Cheah Waishiang, M. A. Khairuddin, Nurfauza binti Jalil, Eaqerzilla Phang","doi":"10.30630/joiv.7.2.1314","DOIUrl":"https://doi.org/10.30630/joiv.7.2.1314","url":null,"abstract":"ICT4D is an acronym for information and communication technologies for development. This acronym represents the many initiatives that are now being carried out in underdeveloped countries all around the globe. These technology-oriented initiatives aim to promote the growth and prosperity of the regions they serve. People from the local community often volunteer their time to serve as program managers when NGOs or governments give funding. The term \"sustainability\" describes an information and communications technology's capacity to carry out a development project even after the initial funding has run out. The e3value technique will be broken down in this article so that we may better understand how it works. Using various tools for value-based modeling, this method is utilized to create an e-Business model. However, one of the main problems with e-business technologies is that they often get insufficient data to be effective. This study aims to examine the procedures that must be followed to learn more about an e-Business concept and mold it into a form that would allow for its implementation in a technologically and commercially practical manner. In order to gather information on the Long Lamai community's economic activities, a survey is being used in this research. The net value sheet for each of their businesses is then stimulated utilizing the data using E3 value. Initial findings indicate that 5 out of 13 enterprises' net incomes are negative, and each of those five businesses has its roots in a local enterprise. However, the figure does not consider labor costs, taxes, or long-term investments made with government money. We continued the stimulation with sensitivity analysis and scenario-based analysis, which results in total revenue of 1,410,000 for the five enterprises in the fourth year after accounting for taxes and fees in the sensitivity analysis. This opens the door for further research into how discrepancies in wealth and income may arise in the simulation of an economy due to the right use of ICT for long-term development and prosperity. Profitability sheets may be created if certain business model assumptions are specified, such as the monetary value of the commodities produced, distributed, and consumed. These may be used to decide if the project can become profitable for all parties concerned.","PeriodicalId":32468,"journal":{"name":"JOIV International Journal on Informatics Visualization","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81883307","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}
A. E. Minarno, Laofin Aripa, Yufis Azhar, Yuda Munarko
Malaria is a severe global public health problem caused by the bite of infected mosquitoes. It can be cured, but only with early detection and effective, quick treatment. It can cause severe conditions if not properly diagnosed and treated at an early stage. In the worst scenario, it can cause death. This study aims at focusing on classifying malaria cell images. Malaria is classified as a dangerous disease caused by the bite of the female Anophles mosquito. As such, it leads to mortality when immediate action and treatment fails to be administered. In particular, this study aims to classify malaria cell images by utilizing the Inception-V3 architecture. In this study, training was conducted on 27,558 malaria cell image data through Inception-V3 architecture by proposing 3 scenarios. The proposed scenario 1 model applies the SGD optimizer to generate a loss value of 0.13 and an accuracy value of 0.95; scenario 2 model applies the Adam optimizer to generate a loss value of 0.09 and an accuracy value of 0.96; and lastly scenario 3 implements the RMSprop optimizer to generate a loss value of 0.08 and an accuracy value of 0.97. Applying the three scenarios, the results of the study apparently indicate that the Inception-V3 model using the RMSprop optimizer is capable of providing the best accuracy results with an accuracy of 97% with the lowest loss value, compared to scenario 1 and scenario 2. Further, the test results confirms that the proposed model in this study is capable of classifying malaria cells effectively.
{"title":"Classification of Malaria Cell Image using Inception-V3 Architecture","authors":"A. E. Minarno, Laofin Aripa, Yufis Azhar, Yuda Munarko","doi":"10.30630/joiv.7.2.1301","DOIUrl":"https://doi.org/10.30630/joiv.7.2.1301","url":null,"abstract":"Malaria is a severe global public health problem caused by the bite of infected mosquitoes. It can be cured, but only with early detection and effective, quick treatment. It can cause severe conditions if not properly diagnosed and treated at an early stage. In the worst scenario, it can cause death. This study aims at focusing on classifying malaria cell images. Malaria is classified as a dangerous disease caused by the bite of the female Anophles mosquito. As such, it leads to mortality when immediate action and treatment fails to be administered. In particular, this study aims to classify malaria cell images by utilizing the Inception-V3 architecture. In this study, training was conducted on 27,558 malaria cell image data through Inception-V3 architecture by proposing 3 scenarios. The proposed scenario 1 model applies the SGD optimizer to generate a loss value of 0.13 and an accuracy value of 0.95; scenario 2 model applies the Adam optimizer to generate a loss value of 0.09 and an accuracy value of 0.96; and lastly scenario 3 implements the RMSprop optimizer to generate a loss value of 0.08 and an accuracy value of 0.97. Applying the three scenarios, the results of the study apparently indicate that the Inception-V3 model using the RMSprop optimizer is capable of providing the best accuracy results with an accuracy of 97% with the lowest loss value, compared to scenario 1 and scenario 2. Further, the test results confirms that the proposed model in this study is capable of classifying malaria cells effectively.","PeriodicalId":32468,"journal":{"name":"JOIV International Journal on Informatics Visualization","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83873315","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. Sukaridhoto, Evianita Dewi Fajrianti, Amma Liesvarastranta Haz, R. Budiarti, Lusiana Agustien
Virtual Reality (VR) technology is a computer technology capable of replicating a real environment into an immersive world. VR is also capable of simulating the user's physical condition so that they are able to interact. In the world of education as a support for educational activities, especially for vocational high school students who are more dominant in practicum, this study aims to show the results of the early stages of implementing Fiber Optic (FO) learning support modules. The module development process is carried out in several stages: scenario preparation, 3D asset development with low poly optimization, scenario integration with 3D assets, triggering every interaction, multiuser settings, and implementation. To build a good VR Fiber Optic application, measurements using OVR metrics are carried out. This measurement aims to determine the reliability of the application that affects the user experience. In the OVR metric measurement, the highest FPS value is 43, and the lowest FPS value is 27. The value obtained is good enough to run VR applications with low poly asset composition. Measurement of the level of user satisfaction is also carried out by using the PIECES Framework. From the measurement results, the value of each variable is in the range of 3.4 - 4.91, which means that users are satisfied with the VR FO application as a virtual learning support module. This research shows that Virtual Reality technology can provide an overview of practicum that is easy to access and not limited by space and material.
{"title":"Implementation of Virtual Fiber Optic Module Using Virtual Reality for Vocational Telecommunications Students","authors":"S. Sukaridhoto, Evianita Dewi Fajrianti, Amma Liesvarastranta Haz, R. Budiarti, Lusiana Agustien","doi":"10.30630/joiv.7.2.1361","DOIUrl":"https://doi.org/10.30630/joiv.7.2.1361","url":null,"abstract":"Virtual Reality (VR) technology is a computer technology capable of replicating a real environment into an immersive world. VR is also capable of simulating the user's physical condition so that they are able to interact. In the world of education as a support for educational activities, especially for vocational high school students who are more dominant in practicum, this study aims to show the results of the early stages of implementing Fiber Optic (FO) learning support modules. The module development process is carried out in several stages: scenario preparation, 3D asset development with low poly optimization, scenario integration with 3D assets, triggering every interaction, multiuser settings, and implementation. To build a good VR Fiber Optic application, measurements using OVR metrics are carried out. This measurement aims to determine the reliability of the application that affects the user experience. In the OVR metric measurement, the highest FPS value is 43, and the lowest FPS value is 27. The value obtained is good enough to run VR applications with low poly asset composition. Measurement of the level of user satisfaction is also carried out by using the PIECES Framework. From the measurement results, the value of each variable is in the range of 3.4 - 4.91, which means that users are satisfied with the VR FO application as a virtual learning support module. This research shows that Virtual Reality technology can provide an overview of practicum that is easy to access and not limited by space and material.","PeriodicalId":32468,"journal":{"name":"JOIV International Journal on Informatics Visualization","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85117416","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}
Classification and object recognition in image processing has significantly improved computer vision tasks. The method is often used for visual problems, especially in picture classification utilizing the Convolutional Neural Network (CNN). In the popular state-of-the-art (SOTA) task of generating a caption on an image, the implementation is often used for feature extraction of an image as an encoder. Instead of performing direct classification, these extracted features are sent from the encoder to the decoder section to generate the sequence. So, some CNN layers related to the classification task are not required. This study aims to determine which CNN pre-trained architecture or model performs best in extracting image features using a state-of-the-art Transformer model as its decoder. Unlike the original Transformer’s architecture, we implemented a vector-to-sequence way instead of sequence-to-sequence for the model. Indonesian Flickr8k and Flick30k datasets were used in this research. Evaluations were carried out using several pre-trained architectures, including ResNet18, ResNet34, ResNet50, ResNet101, VGG16, Efficientnet_b0, Efficientnet_b1, and Googlenet. The qualitative model inference results and quantitative evaluation scores were analyzed in this study. The test results show that the ResNet50 architecture can produce stable sequence generation with the highest accuracy value. With some experimentation, finetuning the encoder can significantly increase the model evaluation score. As for future work, further exploration with larger datasets like Flickr30k, MS COCO 14, MS COCO 17, and other image captioning datasets in Indonesian also implementing a new Transformers-based method can be used to get a better Indonesian automatic image captioning model.
{"title":"Pre-Trained CNN Architecture Analysis for Transformer-Based Indonesian Image Caption Generation Model","authors":"Rifqi Mulyawan, A. Sunyoto, Alva Hendi Muhammad","doi":"10.30630/joiv.7.2.1387","DOIUrl":"https://doi.org/10.30630/joiv.7.2.1387","url":null,"abstract":"Classification and object recognition in image processing has significantly improved computer vision tasks. The method is often used for visual problems, especially in picture classification utilizing the Convolutional Neural Network (CNN). In the popular state-of-the-art (SOTA) task of generating a caption on an image, the implementation is often used for feature extraction of an image as an encoder. Instead of performing direct classification, these extracted features are sent from the encoder to the decoder section to generate the sequence. So, some CNN layers related to the classification task are not required. This study aims to determine which CNN pre-trained architecture or model performs best in extracting image features using a state-of-the-art Transformer model as its decoder. Unlike the original Transformer’s architecture, we implemented a vector-to-sequence way instead of sequence-to-sequence for the model. Indonesian Flickr8k and Flick30k datasets were used in this research. Evaluations were carried out using several pre-trained architectures, including ResNet18, ResNet34, ResNet50, ResNet101, VGG16, Efficientnet_b0, Efficientnet_b1, and Googlenet. The qualitative model inference results and quantitative evaluation scores were analyzed in this study. The test results show that the ResNet50 architecture can produce stable sequence generation with the highest accuracy value. With some experimentation, finetuning the encoder can significantly increase the model evaluation score. As for future work, further exploration with larger datasets like Flickr30k, MS COCO 14, MS COCO 17, and other image captioning datasets in Indonesian also implementing a new Transformers-based method can be used to get a better Indonesian automatic image captioning model. ","PeriodicalId":32468,"journal":{"name":"JOIV International Journal on Informatics Visualization","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89724845","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 development of information technology occurs rapidly in almost all areas of life. All companies must immediately carry out a business transformation following the development of information technology to survive amid increasingly fierce competition. One of the keys to this business transformation's success is an enterprise architecture that is used as a reference in planning, developing, operating, and monitoring company information technology. Implementation of service management practices in state-owned enterprises needs to be translated into IT Services Management Architecture Design, that match the IT Governance Principles as mandated in PER-03/MBU/02/2018. This research focuses on preparing an enterprise architecture design in IT service management by referring to ITIL 4 best practices. The resulting solution is a target architecture design in the business domain, data, and applications arranged according to the TOGAF framework. It was carried out in four stages: scope identification, which defines practices; preliminary phase, which resulted in 11 architecture principles; architecture vision that produces a value chain for IT service provider organizations; a business architecture which resulted in a business service/function catalog consisting of 13 business functions and 43 business services; and an information system architecture that produces a conceptual data model on the three main priority processes of IT service management and an application use-case diagram that describes the relationship between the four actors (users, service managers, service desks, and support groups) with their roles in applications. The enterprise architecture has been designed following the scope of IT service management practices commonly used as a reference for all large and medium-sized companies.
{"title":"The IT Services Management Architecture Design for Large and Medium-sized Companies based on ITIL 4 and TOGAF Framework","authors":"I. Santosa, Rahmat Mulyana","doi":"10.30630/joiv.7.1.1590","DOIUrl":"https://doi.org/10.30630/joiv.7.1.1590","url":null,"abstract":"The development of information technology occurs rapidly in almost all areas of life. All companies must immediately carry out a business transformation following the development of information technology to survive amid increasingly fierce competition. One of the keys to this business transformation's success is an enterprise architecture that is used as a reference in planning, developing, operating, and monitoring company information technology. Implementation of service management practices in state-owned enterprises needs to be translated into IT Services Management Architecture Design, that match the IT Governance Principles as mandated in PER-03/MBU/02/2018. This research focuses on preparing an enterprise architecture design in IT service management by referring to ITIL 4 best practices. The resulting solution is a target architecture design in the business domain, data, and applications arranged according to the TOGAF framework. It was carried out in four stages: scope identification, which defines practices; preliminary phase, which resulted in 11 architecture principles; architecture vision that produces a value chain for IT service provider organizations; a business architecture which resulted in a business service/function catalog consisting of 13 business functions and 43 business services; and an information system architecture that produces a conceptual data model on the three main priority processes of IT service management and an application use-case diagram that describes the relationship between the four actors (users, service managers, service desks, and support groups) with their roles in applications. The enterprise architecture has been designed following the scope of IT service management practices commonly used as a reference for all large and medium-sized companies.","PeriodicalId":32468,"journal":{"name":"JOIV International Journal on Informatics Visualization","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82297539","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}
H. Nguyen, P. Q. Nguyen, Dang Khoa Pham Nguyen, V. Bui, Dinh Tuyen Nguyen
Seaports have a very important role in connecting freight by sea. Goods transported through seaports in the world are increasing day by day to meet human needs. This increases the pressure to apply more technologies for better port management. The world's seaports in the 4th generation, the generation in which seaports enhance connectivity to form a large network, have shown high efficiency when applying technology to port management. This optimizes port operations and connects port information into a network that improves productivity and reduces loading and unloading times. Today, the Internet of Things is the foundation for technologies to manage and optimize operations in various fields. It is considered by scientists to be a highly influential technology in the “4.0” era. The Internet of Things (IoT) technology directly affects the activities and processes of loading and unloading goods at seaports. Modern IoT-based port management technologies such as Radio Frequency Identification (RFID) and Dedicated Short Range Communications (DSRC) are contributing to the increased speed and safe movement of goods through seaports. The application of IoT in port management has become an inevitable trend and will be presented in this article. In the next generation, seaports tend to develop into smart ports based on rapidly developing technology platforms such as IoT, blockchain, and cloud computing. Smart port development also poses many issues to be resolved, including environmental issues. In this paper, the authors present some solutions to develop smart ports in an environmentally friendly manner.
{"title":"Application of IoT Technologies in Seaport Management","authors":"H. Nguyen, P. Q. Nguyen, Dang Khoa Pham Nguyen, V. Bui, Dinh Tuyen Nguyen","doi":"10.30630/joiv.7.1.1697","DOIUrl":"https://doi.org/10.30630/joiv.7.1.1697","url":null,"abstract":"Seaports have a very important role in connecting freight by sea. Goods transported through seaports in the world are increasing day by day to meet human needs. This increases the pressure to apply more technologies for better port management. The world's seaports in the 4th generation, the generation in which seaports enhance connectivity to form a large network, have shown high efficiency when applying technology to port management. This optimizes port operations and connects port information into a network that improves productivity and reduces loading and unloading times. Today, the Internet of Things is the foundation for technologies to manage and optimize operations in various fields. It is considered by scientists to be a highly influential technology in the “4.0” era. The Internet of Things (IoT) technology directly affects the activities and processes of loading and unloading goods at seaports. Modern IoT-based port management technologies such as Radio Frequency Identification (RFID) and Dedicated Short Range Communications (DSRC) are contributing to the increased speed and safe movement of goods through seaports. The application of IoT in port management has become an inevitable trend and will be presented in this article. In the next generation, seaports tend to develop into smart ports based on rapidly developing technology platforms such as IoT, blockchain, and cloud computing. Smart port development also poses many issues to be resolved, including environmental issues. In this paper, the authors present some solutions to develop smart ports in an environmentally friendly manner.","PeriodicalId":32468,"journal":{"name":"JOIV International Journal on Informatics Visualization","volume":"178 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75750030","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}
Muhammad Ikhsan Sani, Simon Siregar, F. Hamdani, Bagas Musamma Nanda, Ryan Febriansyah
In Indonesia, the COVID-19 pandemic has had an impact on a variety of sectors. Using all available technology for disaster mitigation is critical for pandemic prevention and control. Recent studies have uncovered the advantage of Unmanned Aerial Vehicle (UAV) or drones, particularly those with rotary wings, in dealing with the pandemic. Much effort has been devoted to developing a rotary-wing drone system as a flying platform for aerial monitoring. However, several factors must be considered when visually observing a specific region, i.e., the area's size, topographic contours, locations of special interest inside the area, approach points to the area, and the observation timeframe. Since fever is a common symptom of COVID-19, human body temperature monitoring is highlighted for fever screening, with the objective of minimizing people with high body temperatures going to the crowd. A major challenge is creating a system that can provide accurate body temperature data, which is critical for fighting the pandemic. The purpose of this paper is to present a rotary wing drone application for aerial human body temperature measurements. The paper also proposed an alternative solution based on using a portable, low-cost, Forward-looking Infrared (FLIR) thermal imaging camera. The FLIR thermal camera is incorporated into the drone's electronic system. Furthermore, thermal image data are transmitted into the ground station via a radio telemetry transceiver to allow flexible surveillance by the operator. Indoor and outdoor experiments reveal that the system has been effectively installed and provide data collection for further research. The results show that the system can be used for small-scale area aerial monitoring.
{"title":"Small Scale Aerial Monitoring for Human Body Temperature Measurement Using Rotary Wing Drone","authors":"Muhammad Ikhsan Sani, Simon Siregar, F. Hamdani, Bagas Musamma Nanda, Ryan Febriansyah","doi":"10.30630/joiv.7.1.1663","DOIUrl":"https://doi.org/10.30630/joiv.7.1.1663","url":null,"abstract":"In Indonesia, the COVID-19 pandemic has had an impact on a variety of sectors. Using all available technology for disaster mitigation is critical for pandemic prevention and control. Recent studies have uncovered the advantage of Unmanned Aerial Vehicle (UAV) or drones, particularly those with rotary wings, in dealing with the pandemic. Much effort has been devoted to developing a rotary-wing drone system as a flying platform for aerial monitoring. However, several factors must be considered when visually observing a specific region, i.e., the area's size, topographic contours, locations of special interest inside the area, approach points to the area, and the observation timeframe. Since fever is a common symptom of COVID-19, human body temperature monitoring is highlighted for fever screening, with the objective of minimizing people with high body temperatures going to the crowd. A major challenge is creating a system that can provide accurate body temperature data, which is critical for fighting the pandemic. The purpose of this paper is to present a rotary wing drone application for aerial human body temperature measurements. The paper also proposed an alternative solution based on using a portable, low-cost, Forward-looking Infrared (FLIR) thermal imaging camera. The FLIR thermal camera is incorporated into the drone's electronic system. Furthermore, thermal image data are transmitted into the ground station via a radio telemetry transceiver to allow flexible surveillance by the operator. Indoor and outdoor experiments reveal that the system has been effectively installed and provide data collection for further research. The results show that the system can be used for small-scale area aerial monitoring.","PeriodicalId":32468,"journal":{"name":"JOIV International Journal on Informatics Visualization","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85452250","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}
I. G. P. Suta Wijaya, H. Mulyana, H. Kadriyan, Riska Yanu Fa’rifah
An otorhinolaryngologist (ORL) or general practitioner diagnoses ear disease based on ear image information. However, general practitioners refer patients to ORL for chronic ear disease because the image of ear disease has high complexity, variety, and little difference between diseases. An artificial intelligence-based approach is needed to make it easier for doctors to diagnose ear diseases based on ear image information, such as the Convolutional Neural Network (CNN). This paper describes how CNN was designed to generate CNN models used to classify ear diseases. The model was developed using an ear image dataset from the practice of an ORL at the University of Mataram Teaching Hospital. This work aims to find the best CNN model for classifying ear diseases applicable to android mobile devices. Furthermore, the best CNN model is deployed for an Android-based application integrated with the Endoscope Ear Cleaning Tool Kit for registering patient ear images. The experimental results show 83% accuracy, 86% precision, 86% recall, and 4ms inference time. The application produces a System Usability Scale of 76.88% for testing, which shows it is easy to use. This achievement shows that the model can be developed and integrated into an ENT expert system. In the future, the ENT expert system can be operated by workers in community health centres/clinics to assist leading health them in diagnosing ENT diseases early.
{"title":"The Design of Convolutional Neural Networks Model for Classification of Ear Diseases on Android Mobile Devices","authors":"I. G. P. Suta Wijaya, H. Mulyana, H. Kadriyan, Riska Yanu Fa’rifah","doi":"10.30630/joiv.7.1.1591","DOIUrl":"https://doi.org/10.30630/joiv.7.1.1591","url":null,"abstract":"An otorhinolaryngologist (ORL) or general practitioner diagnoses ear disease based on ear image information. However, general practitioners refer patients to ORL for chronic ear disease because the image of ear disease has high complexity, variety, and little difference between diseases. An artificial intelligence-based approach is needed to make it easier for doctors to diagnose ear diseases based on ear image information, such as the Convolutional Neural Network (CNN). This paper describes how CNN was designed to generate CNN models used to classify ear diseases. The model was developed using an ear image dataset from the practice of an ORL at the University of Mataram Teaching Hospital. This work aims to find the best CNN model for classifying ear diseases applicable to android mobile devices. Furthermore, the best CNN model is deployed for an Android-based application integrated with the Endoscope Ear Cleaning Tool Kit for registering patient ear images. The experimental results show 83% accuracy, 86% precision, 86% recall, and 4ms inference time. The application produces a System Usability Scale of 76.88% for testing, which shows it is easy to use. This achievement shows that the model can be developed and integrated into an ENT expert system. In the future, the ENT expert system can be operated by workers in community health centres/clinics to assist leading health them in diagnosing ENT diseases early.","PeriodicalId":32468,"journal":{"name":"JOIV International Journal on Informatics Visualization","volume":"96 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86258534","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}
A. Rahmatulloh, Anjar Ginanjar, I. Darmawan, Neng Ika Kurniati, Erna Haerani
Artificial Intelligence has evolved in sophistication and widespread use. This study aims to create a chatbot application in the health sector regarding the early diagnosis of pregnancy disorders. Based on basic health research, only 44 percent of pregnant women know the danger signs of pregnancy. The chatbot application developed is expected to facilitate and increase knowledge for pregnant women about the danger signs of pregnancy, especially early diagnosis of pregnancy disorders. The chatbot application was developed with artificial intelligence technology based on Artificial Intelligence Markup Language with the question-answer concept using the Pandorabots framework. The test is carried out in two stages: functional and pattern matching. The functional testing uses the black-box testing method, and the pattern-matching test on the chatbot uses the sentence similarity and bigram methods based on user input and keywords similarity in the bot's knowledge base. The functional testing results show that the chatbot application runs well, with the eligibility criteria reaching 81.4% and the results of the keyword similarity test (pattern matching) are zero to one, in the sense that the value of one has the same similarity between user input and pattern. Meanwhile, the zero value has no similarities, so the bot will respond to it as free input. So it can be concluded that the bot can respond to user questions when the pattern and input have the same level of similarity.
{"title":"Chatbot for Diagnosis of Pregnancy Disorders using Artificial Intelligence Markup Language (AIML)","authors":"A. Rahmatulloh, Anjar Ginanjar, I. Darmawan, Neng Ika Kurniati, Erna Haerani","doi":"10.30630/joiv.7.1.1595","DOIUrl":"https://doi.org/10.30630/joiv.7.1.1595","url":null,"abstract":"Artificial Intelligence has evolved in sophistication and widespread use. This study aims to create a chatbot application in the health sector regarding the early diagnosis of pregnancy disorders. Based on basic health research, only 44 percent of pregnant women know the danger signs of pregnancy. The chatbot application developed is expected to facilitate and increase knowledge for pregnant women about the danger signs of pregnancy, especially early diagnosis of pregnancy disorders. The chatbot application was developed with artificial intelligence technology based on Artificial Intelligence Markup Language with the question-answer concept using the Pandorabots framework. The test is carried out in two stages: functional and pattern matching. The functional testing uses the black-box testing method, and the pattern-matching test on the chatbot uses the sentence similarity and bigram methods based on user input and keywords similarity in the bot's knowledge base. The functional testing results show that the chatbot application runs well, with the eligibility criteria reaching 81.4% and the results of the keyword similarity test (pattern matching) are zero to one, in the sense that the value of one has the same similarity between user input and pattern. Meanwhile, the zero value has no similarities, so the bot will respond to it as free input. So it can be concluded that the bot can respond to user questions when the pattern and input have the same level of similarity.","PeriodicalId":32468,"journal":{"name":"JOIV International Journal on Informatics Visualization","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77513517","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}
W. Wedashwara, M. Yadnya, I Wayan Sudiarta, I Wayan Agus Arimbawa, T. Mulyana
Prevention of the effects caused by natural disasters such as earthquakes and landslides requires analysis of vibration propagation. In outdoor applications, internet sources such as WIFI are not always available, so it requires alternative data communications such as nRF24l01. The system also requires a portable power source such as solar power. This research aims to develop a vibration propagation analysis system based on the nRF24l01 wireless sensor network and solar power by implementing the fuzzy rule-based regression (FRBR) algorithm. The system consists of two piezoelectric and nrf24l01 vibration sensors. The system also uses a third node equipped with temperature and soil moisture sensors, air temperature and humidity, and light intensity as environmental variables. The evaluation results show the Quality of Services (QoS) results with a throughput of 99.564%, PDR 99.675%, and a delay of 0.0073s. The Fuzzy Association Rule (FAR) extraction results yield nine rules with average support of 0.319 and confidence of 1 for vibration propagation. The availability of solar power was evaluated with an average current value of 0.250A and a voltage of 3.266V. The results of FRBR are based on the propagation of the vibration that propagated and produced a mean square error (MSE) of 0.141 and a mean absolute error (MAE) of 0.165. The correlation matrix and FAR results show that only soil moisture has a major effect on the magnitude and duration of propagation. However, other variables can regress soil moisture with MSE 0.232 and MAE 0.287.
{"title":"Solar Powered Vibration Propagation Analysis System using nRF24l01 based WSN and FRBR","authors":"W. Wedashwara, M. Yadnya, I Wayan Sudiarta, I Wayan Agus Arimbawa, T. Mulyana","doi":"10.30630/joiv.7.1.1592","DOIUrl":"https://doi.org/10.30630/joiv.7.1.1592","url":null,"abstract":"Prevention of the effects caused by natural disasters such as earthquakes and landslides requires analysis of vibration propagation. In outdoor applications, internet sources such as WIFI are not always available, so it requires alternative data communications such as nRF24l01. The system also requires a portable power source such as solar power. This research aims to develop a vibration propagation analysis system based on the nRF24l01 wireless sensor network and solar power by implementing the fuzzy rule-based regression (FRBR) algorithm. The system consists of two piezoelectric and nrf24l01 vibration sensors. The system also uses a third node equipped with temperature and soil moisture sensors, air temperature and humidity, and light intensity as environmental variables. The evaluation results show the Quality of Services (QoS) results with a throughput of 99.564%, PDR 99.675%, and a delay of 0.0073s. The Fuzzy Association Rule (FAR) extraction results yield nine rules with average support of 0.319 and confidence of 1 for vibration propagation. The availability of solar power was evaluated with an average current value of 0.250A and a voltage of 3.266V. The results of FRBR are based on the propagation of the vibration that propagated and produced a mean square error (MSE) of 0.141 and a mean absolute error (MAE) of 0.165. The correlation matrix and FAR results show that only soil moisture has a major effect on the magnitude and duration of propagation. However, other variables can regress soil moisture with MSE 0.232 and MAE 0.287.","PeriodicalId":32468,"journal":{"name":"JOIV International Journal on Informatics Visualization","volume":"49 4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77236603","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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