Pub Date : 2022-07-27DOI: 10.1109/ICISIT54091.2022.9873097
Timothy Harlian, M. F. Ruriawan, Yudha Purwanto
The progress in technology and the digital paradigm forces a new standard, such as switching from physical to digital documents. Digital documents are implemented in various ways like certificates, certificates of merit, even diplomas. However, those things are vulnerable to counterfeit, and the integrity compromise of its content will be challenging to detect. One of the solutions is increasing transparency for the document data to ensure that no single point of failure exists. Blockchain has the potential to solve the problem. Blockchain has the transparency aspect to it. Therefore, it can be used to maintain the validity of document data. Because in blockchain, only read and write operations could be done, nothing could compromise the integrity of the data. This paper implemented a document validation system with Ethereum blockchain and Rinkeby Test Network as blockchain network. This blockchain application can do input, retrieve, update, and delete with 100% black-box testing and 100% white box testing. Performance testing for all transactions has the fastest time, 6.04 seconds, and slowest time, 93.32 seconds.
{"title":"Implementation of Blockchain for Digital Document Data Collection Website","authors":"Timothy Harlian, M. F. Ruriawan, Yudha Purwanto","doi":"10.1109/ICISIT54091.2022.9873097","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9873097","url":null,"abstract":"The progress in technology and the digital paradigm forces a new standard, such as switching from physical to digital documents. Digital documents are implemented in various ways like certificates, certificates of merit, even diplomas. However, those things are vulnerable to counterfeit, and the integrity compromise of its content will be challenging to detect. One of the solutions is increasing transparency for the document data to ensure that no single point of failure exists. Blockchain has the potential to solve the problem. Blockchain has the transparency aspect to it. Therefore, it can be used to maintain the validity of document data. Because in blockchain, only read and write operations could be done, nothing could compromise the integrity of the data. This paper implemented a document validation system with Ethereum blockchain and Rinkeby Test Network as blockchain network. This blockchain application can do input, retrieve, update, and delete with 100% black-box testing and 100% white box testing. Performance testing for all transactions has the fastest time, 6.04 seconds, and slowest time, 93.32 seconds.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133217717","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 : 2022-07-27DOI: 10.1109/ICISIT54091.2022.9872713
Basith Abdurrohman Asy’Ari, M. Rivai, M. Attamimi, D. Purwanto
LiDAR is one of the visual sensors which can measure a distance and form an environment description. This device is needed for many kinds of vehicle navigation especially for the autonomous system. Nowadays, the 3D LiDAR is still expensive in the market. This study has developed and constructed a 3D LiDAR consisting of a single point LiDAR as the main sensor and a Neural Network for classifying objects. Proportional-integral-derivative (PID) controller was involved to maintain the motor rotation in order to stabilize the scanning process. Arduino Mega microcontroller was used as the main processor to obtain the LiDAR data, to control the motor speed, and to communicate the data with computer. In this case, the 3D LiDAR was tested using five different objects. The experimental results show that the system can recognize all objects with a 100% success rate. This proposed system can be expected to support the road safety on an autonomous vehicle. In addition, the 3D LiDAR can be marketed in a low price.
{"title":"Design of 3D LiDAR Combined with Neural Network for Object Classification","authors":"Basith Abdurrohman Asy’Ari, M. Rivai, M. Attamimi, D. Purwanto","doi":"10.1109/ICISIT54091.2022.9872713","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872713","url":null,"abstract":"LiDAR is one of the visual sensors which can measure a distance and form an environment description. This device is needed for many kinds of vehicle navigation especially for the autonomous system. Nowadays, the 3D LiDAR is still expensive in the market. This study has developed and constructed a 3D LiDAR consisting of a single point LiDAR as the main sensor and a Neural Network for classifying objects. Proportional-integral-derivative (PID) controller was involved to maintain the motor rotation in order to stabilize the scanning process. Arduino Mega microcontroller was used as the main processor to obtain the LiDAR data, to control the motor speed, and to communicate the data with computer. In this case, the 3D LiDAR was tested using five different objects. The experimental results show that the system can recognize all objects with a 100% success rate. This proposed system can be expected to support the road safety on an autonomous vehicle. In addition, the 3D LiDAR can be marketed in a low price.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127465639","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 : 2022-07-27DOI: 10.1109/ICISIT54091.2022.9872719
Gregorius Kevin Satrya Ananta, Y. Kusumawati, A. Pramono
Art Block problems occur until today in the design world, where designers struggle to find ideas. Sometimes, designers open social media to solve art block problems. But the solution they have are not effective enough to increase their creativity and start their work, because the search engine could not help them enough, and the lack of others’ opinions about each other’s work. The researcher came out with the idea to create an application that can solve art block problems by increasing the work of the search engine, widening the category, and adding the Art Helper feature where designers can discuss their work and can help others who needed help. By using design thinking methods this research proposed Artlution mobile apps design concept, meaning a solution for your art problems. Hopefully, this research can be used as a recommendation for further development to make the designer relatively more creative.
{"title":"Artlution: Architecture Design of Mobile Apps for Artblock Problems","authors":"Gregorius Kevin Satrya Ananta, Y. Kusumawati, A. Pramono","doi":"10.1109/ICISIT54091.2022.9872719","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872719","url":null,"abstract":"Art Block problems occur until today in the design world, where designers struggle to find ideas. Sometimes, designers open social media to solve art block problems. But the solution they have are not effective enough to increase their creativity and start their work, because the search engine could not help them enough, and the lack of others’ opinions about each other’s work. The researcher came out with the idea to create an application that can solve art block problems by increasing the work of the search engine, widening the category, and adding the Art Helper feature where designers can discuss their work and can help others who needed help. By using design thinking methods this research proposed Artlution mobile apps design concept, meaning a solution for your art problems. Hopefully, this research can be used as a recommendation for further development to make the designer relatively more creative.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115795547","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}
Builders are workers with specific expertise in development. Community needs for workers with special skills to repair parts of homes remain difficult to find due to space and space constraints. In the current era of the Covid-19 pandemic, there are many people like construction workers who want to find work, and many people who need construction workers to repair parts of their homes but are not sure if construction workers are performing well or not well recruited by them. In this study, the authors propose an application to understand how construction workers can be found through an online application, and how potential clients can find suitable and trustworthy contractors. Smartphone users only need a smartphone and an internet connection to access this HoMain app. The purpose of this study is to design an online application for a mobile-based construction service ordering system to support the needs of the community and builders during construction work. With this app, people can easily order construction services based on online location. The HoMain application development method adopts the Rapid Application method, and the application development is relatively fast and efficient.
{"title":"Information System Analysis And Design For Mobile-Based Homain Applications","authors":"Muhammad Alttha Ikhsan, Daffa Albaihaqi Santoso, Fauzan Farrel Maulana Ruchiyat, Henkie Ongowarsito","doi":"10.1109/ICISIT54091.2022.9872900","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872900","url":null,"abstract":"Builders are workers with specific expertise in development. Community needs for workers with special skills to repair parts of homes remain difficult to find due to space and space constraints. In the current era of the Covid-19 pandemic, there are many people like construction workers who want to find work, and many people who need construction workers to repair parts of their homes but are not sure if construction workers are performing well or not well recruited by them. In this study, the authors propose an application to understand how construction workers can be found through an online application, and how potential clients can find suitable and trustworthy contractors. Smartphone users only need a smartphone and an internet connection to access this HoMain app. The purpose of this study is to design an online application for a mobile-based construction service ordering system to support the needs of the community and builders during construction work. With this app, people can easily order construction services based on online location. The HoMain application development method adopts the Rapid Application method, and the application development is relatively fast and efficient.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114433274","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 : 2022-07-27DOI: 10.1109/ICISIT54091.2022.9872690
Antonius Schmidt, Dominik Aufderheide
Generating three-dimensional models from real world objects based on images from a single camera is an important application in computer vision and numerous possible applications. For this Structure-from-Motion (SfM) algorithms provide an approach based on the successful tracking of 2D feature points throughout an image sequence and the subsequent camera egomotion estimation and a global 3D structure recovery. However, the performance of those approaches is still limited according their precision, denseness and completeness of the reconstructed scene model. This paper introduces an approach based on Inventive Design Methodology (IDM) for the systematic analysis of existing SfM approaches and a subsequent derivation of a novel sensor fusion approach in order to overcome current application-related restrictions.
{"title":"Application of Inventive Design Methodology for a Sensor Fusion Approach in Structure-from-Motion (SfM) Applications","authors":"Antonius Schmidt, Dominik Aufderheide","doi":"10.1109/ICISIT54091.2022.9872690","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872690","url":null,"abstract":"Generating three-dimensional models from real world objects based on images from a single camera is an important application in computer vision and numerous possible applications. For this Structure-from-Motion (SfM) algorithms provide an approach based on the successful tracking of 2D feature points throughout an image sequence and the subsequent camera egomotion estimation and a global 3D structure recovery. However, the performance of those approaches is still limited according their precision, denseness and completeness of the reconstructed scene model. This paper introduces an approach based on Inventive Design Methodology (IDM) for the systematic analysis of existing SfM approaches and a subsequent derivation of a novel sensor fusion approach in order to overcome current application-related restrictions.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121563332","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 : 2022-07-27DOI: 10.1109/ICISIT54091.2022.9872865
Mohammad Farizshah Ismail Kamil, N. Jamaludin, Mohd Rizal Mohd Isa, S. Jusoh
According to UN Committee on World Food Security, people must always have access to sufficient food supplies such as meat, chicken, and sheep. Although important to Malaysian Muslims which account for about 60% of the population, sheep are in short supply locally due to the high mortality rate caused by fatal diseases such as Foot and Mouth Disease (FMD), Tetanus, etc. Because of inbreeding, qualities such as disease resistance, fertility, prolificacy, vigor, and survivability are reduced in animals, often referred to as inbreeding depression. It is important to note that infected sheep may cause contaminated sheep meat produce, transmitting foodborne bacteria such as E.coli and Salmonella to humans during different stages of food preparation. Previously, other papers compared hundreds of images of sheep to deep learning models to learn of its breed. Although successful, both methods took a long period to complete. This paper proposes a framework based on deep learning techniques that will identify and predict breed lineage and inherited disease in sheep. The adopted deep learning algorithm will improve time efficiency in retrieving immediate information while still maintaining a high accuracy rate. From a wider perspective, the proposed framework has the potential to be used across domains as it can be trained with any other dataset.
{"title":"Prediction of Breed Lineage for Small Ruminant Production using Deep Learning Technique","authors":"Mohammad Farizshah Ismail Kamil, N. Jamaludin, Mohd Rizal Mohd Isa, S. Jusoh","doi":"10.1109/ICISIT54091.2022.9872865","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872865","url":null,"abstract":"According to UN Committee on World Food Security, people must always have access to sufficient food supplies such as meat, chicken, and sheep. Although important to Malaysian Muslims which account for about 60% of the population, sheep are in short supply locally due to the high mortality rate caused by fatal diseases such as Foot and Mouth Disease (FMD), Tetanus, etc. Because of inbreeding, qualities such as disease resistance, fertility, prolificacy, vigor, and survivability are reduced in animals, often referred to as inbreeding depression. It is important to note that infected sheep may cause contaminated sheep meat produce, transmitting foodborne bacteria such as E.coli and Salmonella to humans during different stages of food preparation. Previously, other papers compared hundreds of images of sheep to deep learning models to learn of its breed. Although successful, both methods took a long period to complete. This paper proposes a framework based on deep learning techniques that will identify and predict breed lineage and inherited disease in sheep. The adopted deep learning algorithm will improve time efficiency in retrieving immediate information while still maintaining a high accuracy rate. From a wider perspective, the proposed framework has the potential to be used across domains as it can be trained with any other dataset.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117335807","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 : 2022-07-27DOI: 10.1109/ICISIT54091.2022.9872884
Arsy Yudha Prinanto, M. Rivai, Rachmad Setiawan
The magnetron transmitter system is one of the most important components of weather radar. Monitoring the condition of the system is crucial to ensure the radar is operating normally. In this study, the temperature monitoring of the magnetron transmitter system was carried out. Thermal camera MLX90640 accompanied by NodeMCU ESP32 microcontroller provides a temperature matrix, which can represent the overall temperature of the radar system. The diagnosis system is built based on a neural network consisting of a hidden layer, and an output layer that classifies six system conditions. The results of this study showed that the thermal camera can measure the temperature of the magnetron transmitter system. This system can obtain 100% accuracy in identifying the conditions of the magnetron transmitter system, namely magnetron on, magnetron off, radar off, modulator power supply overheat, switch array unit overheat, and signal processing faulty. This innovation is expected to be early detection of an anomaly that occurs in the magnetron transmitter system so that it can minimize downtime to make repairs due to the unpreparedness of spare parts.
{"title":"Diagnostics of Magnetron Transmitter System using Thermal Camera and Neural Network","authors":"Arsy Yudha Prinanto, M. Rivai, Rachmad Setiawan","doi":"10.1109/ICISIT54091.2022.9872884","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872884","url":null,"abstract":"The magnetron transmitter system is one of the most important components of weather radar. Monitoring the condition of the system is crucial to ensure the radar is operating normally. In this study, the temperature monitoring of the magnetron transmitter system was carried out. Thermal camera MLX90640 accompanied by NodeMCU ESP32 microcontroller provides a temperature matrix, which can represent the overall temperature of the radar system. The diagnosis system is built based on a neural network consisting of a hidden layer, and an output layer that classifies six system conditions. The results of this study showed that the thermal camera can measure the temperature of the magnetron transmitter system. This system can obtain 100% accuracy in identifying the conditions of the magnetron transmitter system, namely magnetron on, magnetron off, radar off, modulator power supply overheat, switch array unit overheat, and signal processing faulty. This innovation is expected to be early detection of an anomaly that occurs in the magnetron transmitter system so that it can minimize downtime to make repairs due to the unpreparedness of spare parts.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117091118","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 : 2022-07-27DOI: 10.1109/ICISIT54091.2022.9872891
F. F. Taliningsih, Y. Fu’adah, S. Rizal, Achmad Rizal, M. A. Pramudito, Giyan Sukma Pratama, Andi Fany
Biometric is an analysis of individual characteristics. For instance, fingerprint, voice, i ris, a nd face a re biometrics. Nowadays, those methods are often used; it still has the disadvantage of being easy to manipulate. Identification using Electrocardiogram (ECG) signal is one of the biometric methods developed to prevent individual manipulation since ECG signals are unique for each individual. This study designed a system using ECG signals for biometric verification. The ECG signals are unique since each individual has different physiological, geometric, and characteristics. The ECG-ID dataset used for evaluation contains 90 subjects. The One Dimensioanal Convolutional Neural Network is used in this research. We compared the difference using two ECG signal fragments, namely PQRST and PQRS waves. The best results show an accuracy of 91.57% using PQRST waves. This proposed study is feasible enough to be used as verification biometrics.
{"title":"Biometric Verification Based on ECG Signal using 1 Dimensional Convolutional Neural Network","authors":"F. F. Taliningsih, Y. Fu’adah, S. Rizal, Achmad Rizal, M. A. Pramudito, Giyan Sukma Pratama, Andi Fany","doi":"10.1109/ICISIT54091.2022.9872891","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872891","url":null,"abstract":"Biometric is an analysis of individual characteristics. For instance, fingerprint, voice, i ris, a nd face a re biometrics. Nowadays, those methods are often used; it still has the disadvantage of being easy to manipulate. Identification using Electrocardiogram (ECG) signal is one of the biometric methods developed to prevent individual manipulation since ECG signals are unique for each individual. This study designed a system using ECG signals for biometric verification. The ECG signals are unique since each individual has different physiological, geometric, and characteristics. The ECG-ID dataset used for evaluation contains 90 subjects. The One Dimensioanal Convolutional Neural Network is used in this research. We compared the difference using two ECG signal fragments, namely PQRST and PQRS waves. The best results show an accuracy of 91.57% using PQRST waves. This proposed study is feasible enough to be used as verification biometrics.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132720122","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 : 2022-07-27DOI: 10.1109/ICISIT54091.2022.9872812
W. Safitri, T. Ahmad, Dandy Pramana Hostiadi
In this cyber era, the number of cybercrime problems grows significantly, impacting network communication security. Some factors have been identified, such as malware. It is a malicious code attack that is harmful. On the other hand, a botnet can exploit malware to threaten whole computer networks. Therefore, it needs to be handled appropriately. Several botnet activity detection models have been developed using a classification approach in previous studies. However, it has not been analyzed about selecting features to be used in the learning process of the classification algorithm. In fact, the number and selection of features implemented can affect the detection accuracy of the classification algorithm. This paper proposes an analysis technique for determining the number and selection of features developed based on previous research. It aims to obtain the analysis of using features. The experiment has been conducted using several classification algorithms, namely Decision tree, k-NN, Naïve Bayes, Random Forest, and Support Vector Machine (SVM). The results show that taking a certain number of features increases the detection accuracy. Compared with previous studies, the results obtained show that the average detection accuracy of 98.34% using four features has the highest value from the previous study, 97.46% using 11 features. These results indicate that the selection of the correct number and features affects the performance of the botnet detection model.
{"title":"Analyzing Machine Learning-based Feature Selection for Botnet Detection","authors":"W. Safitri, T. Ahmad, Dandy Pramana Hostiadi","doi":"10.1109/ICISIT54091.2022.9872812","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872812","url":null,"abstract":"In this cyber era, the number of cybercrime problems grows significantly, impacting network communication security. Some factors have been identified, such as malware. It is a malicious code attack that is harmful. On the other hand, a botnet can exploit malware to threaten whole computer networks. Therefore, it needs to be handled appropriately. Several botnet activity detection models have been developed using a classification approach in previous studies. However, it has not been analyzed about selecting features to be used in the learning process of the classification algorithm. In fact, the number and selection of features implemented can affect the detection accuracy of the classification algorithm. This paper proposes an analysis technique for determining the number and selection of features developed based on previous research. It aims to obtain the analysis of using features. The experiment has been conducted using several classification algorithms, namely Decision tree, k-NN, Naïve Bayes, Random Forest, and Support Vector Machine (SVM). The results show that taking a certain number of features increases the detection accuracy. Compared with previous studies, the results obtained show that the average detection accuracy of 98.34% using four features has the highest value from the previous study, 97.46% using 11 features. These results indicate that the selection of the correct number and features affects the performance of the botnet detection model.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130028946","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 : 2022-07-27DOI: 10.1109/ICISIT54091.2022.9872874
Devina Arnyndiasari, R. Ferdiana, P. Santosa
Software development is one of the work practices in a company’s startup, academics, and industries. Agile is a software development methodology that is currently quite popular. Agile development practices existing methodologies include Test-Driven Development (TDD), Behavior-Driven Development (BDD), Domain-Driven Design (DDD), and Model-Driven Development (MDD). Each software development practice is unique as it could hinder or contribute greatly to the creation of said software. Agile is a consideration for developers when selecting appropriate development practices due to the breadth of available practices. Thus, this study identifies the characteristics and effectiveness of Agile methods. Our opinion is that this study can help software developers to better understand the challenges of each agile practices and implement them to create better optimized softwares.
{"title":"Software Practices For Agile Developers: A Systematic Literature Review","authors":"Devina Arnyndiasari, R. Ferdiana, P. Santosa","doi":"10.1109/ICISIT54091.2022.9872874","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872874","url":null,"abstract":"Software development is one of the work practices in a company’s startup, academics, and industries. Agile is a software development methodology that is currently quite popular. Agile development practices existing methodologies include Test-Driven Development (TDD), Behavior-Driven Development (BDD), Domain-Driven Design (DDD), and Model-Driven Development (MDD). Each software development practice is unique as it could hinder or contribute greatly to the creation of said software. Agile is a consideration for developers when selecting appropriate development practices due to the breadth of available practices. Thus, this study identifies the characteristics and effectiveness of Agile methods. Our opinion is that this study can help software developers to better understand the challenges of each agile practices and implement them to create better optimized softwares.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130400482","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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