Pub Date : 2022-07-27DOI: 10.1109/ICISIT54091.2022.9872805
Ridwan Budiman, R. A. Hanindito, D. I. Sensuse, Nadya Safitri
Innovation is one of the important things for organizations in increasing competitiveness and maintaining the company’s existence in the current technological era. In order to continue to innovate, PT XYZ realized the importance of the role of employees, who are important assets of the company, and knowledge as the foundation for the creation of new innovations. However, it turned out there was a knowledge gap in PT XYZ. This was due to incomplete project documentation, knowledge related to features that was not evenly distributed and was only owned by a few people, tacit knowledge that had not become explicit knowledge, and the occurrence of key employee turnover in the company. To overcome and prevent knowledge gap in the future, research using qualitative methods was conducted by using semi-structured and open interviews with three subject matter experts in PT XYZ. Then, gap analysis using the Zack Framework and SWOT analysis was carried out to obtain a knowledge management (KM) strategy. Based on the interview results, there were 5 strength factors and 5 weakness factors from the company’s internal, as well as 4 opportunity factors and 4 threat factors from external companies. Based on gap analysis result, there were 8 recommended KM strategies. Then, the KM strategy recommendations were prioritized based on interview result. There were 4 KM strategies classified as primary priority, which were KM1, KM2, KM5, and KM6, while 4 KM strategies were considered as secondary category, which were KM3, KM4, KM7, and KM8.
{"title":"Knowledge Management Strategy in Indonesia Startup Company: Case Study in PT XYZ","authors":"Ridwan Budiman, R. A. Hanindito, D. I. Sensuse, Nadya Safitri","doi":"10.1109/ICISIT54091.2022.9872805","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872805","url":null,"abstract":"Innovation is one of the important things for organizations in increasing competitiveness and maintaining the company’s existence in the current technological era. In order to continue to innovate, PT XYZ realized the importance of the role of employees, who are important assets of the company, and knowledge as the foundation for the creation of new innovations. However, it turned out there was a knowledge gap in PT XYZ. This was due to incomplete project documentation, knowledge related to features that was not evenly distributed and was only owned by a few people, tacit knowledge that had not become explicit knowledge, and the occurrence of key employee turnover in the company. To overcome and prevent knowledge gap in the future, research using qualitative methods was conducted by using semi-structured and open interviews with three subject matter experts in PT XYZ. Then, gap analysis using the Zack Framework and SWOT analysis was carried out to obtain a knowledge management (KM) strategy. Based on the interview results, there were 5 strength factors and 5 weakness factors from the company’s internal, as well as 4 opportunity factors and 4 threat factors from external companies. Based on gap analysis result, there were 8 recommended KM strategies. Then, the KM strategy recommendations were prioritized based on interview result. There were 4 KM strategies classified as primary priority, which were KM1, KM2, KM5, and KM6, while 4 KM strategies were considered as secondary category, which were KM3, KM4, KM7, and KM8.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"19 7 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":"125915838","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/ICISIT54091.2022.9873070
Husni Iskandar Pohan, H. Warnars, B. Soewito, F. Gaol
Online transactions are significant in the pandemic era. Using online transactions can minimize the risk of physical contact with disease transmission between buyers and sellers. However, with so many choices of items, it becomes challenging for users to decide which item suits their needs. For this reason, the recommender system was created as a handy tool. Recommender systems can help provide ratings, compare with other user data, use personal transaction history, use current events, or combine the above methods. Currently, computer science experts are constantly trying to improve recommender systems. In 2017 a new method emerged that uses transformers as one of the deep learning models. The combination of recommender systems and transformers can process extensive data, create different weights for each input data, and process data without sequentially allowing parallel processing and reducing training time significantly. Many papers in various countries are continuously trying to improve this methodology. In this literature review, we try to analyze the technology used, the dataset used, and the area where the technology is implemented. In this case, we carry out collecting papers, then filtering, classifying and analyzing, and making conclusions.
{"title":"Recommender System Using Transformer Model: A Systematic Literature Review","authors":"Husni Iskandar Pohan, H. Warnars, B. Soewito, F. Gaol","doi":"10.1109/ICISIT54091.2022.9873070","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9873070","url":null,"abstract":"Online transactions are significant in the pandemic era. Using online transactions can minimize the risk of physical contact with disease transmission between buyers and sellers. However, with so many choices of items, it becomes challenging for users to decide which item suits their needs. For this reason, the recommender system was created as a handy tool. Recommender systems can help provide ratings, compare with other user data, use personal transaction history, use current events, or combine the above methods. Currently, computer science experts are constantly trying to improve recommender systems. In 2017 a new method emerged that uses transformers as one of the deep learning models. The combination of recommender systems and transformers can process extensive data, create different weights for each input data, and process data without sequentially allowing parallel processing and reducing training time significantly. Many papers in various countries are continuously trying to improve this methodology. In this literature review, we try to analyze the technology used, the dataset used, and the area where the technology is implemented. In this case, we carry out collecting papers, then filtering, classifying and analyzing, and making conclusions.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"10 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":"122413556","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/ICISIT54091.2022.9873033
B. I. Nasution, Sri Indriyani Siregar
COVID-19 has impacted Indonesia and caused an economic recession during 2020. The economic condition in Indonesia should be evaluated through the regional economic condition. One well-known approach to do a regional analysis is a geodemographic analysis using Fuzzy Geographically Weighted Clustering (FGWC). However, FGWC is still weak against the local optima, so it is necessary to use an optimisation algorithm to enhance it. This study proposes a new approach of FGWC enhancement using Elicit Teaching-Learning Based Optimisation (ETLBO) to analyse the regional economic condition in Indonesia. We compare ETLBO with previously implemented optimisation algorithms in FGWC, such as Particle Swarm Optimisation (PSO) and Intelligent Firefly Algorithm (IFA). This study found that ETLBO performs well in identifying Indonesia’s regional economic condition. Moreover, the clustering results showed the difference of problematic sectors. We also found that the provinces in Java Island joined into a cluster and have problems in many sectors. This study can be used as the basis for the evaluation of regional economic conditions in Indonesia.
{"title":"Regional Economy Condition in Indonesia during COVID-19 Pandemic: An Analysis using Teaching Learning-Based Fuzzy Geodemographic Clustering","authors":"B. I. Nasution, Sri Indriyani Siregar","doi":"10.1109/ICISIT54091.2022.9873033","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9873033","url":null,"abstract":"COVID-19 has impacted Indonesia and caused an economic recession during 2020. The economic condition in Indonesia should be evaluated through the regional economic condition. One well-known approach to do a regional analysis is a geodemographic analysis using Fuzzy Geographically Weighted Clustering (FGWC). However, FGWC is still weak against the local optima, so it is necessary to use an optimisation algorithm to enhance it. This study proposes a new approach of FGWC enhancement using Elicit Teaching-Learning Based Optimisation (ETLBO) to analyse the regional economic condition in Indonesia. We compare ETLBO with previously implemented optimisation algorithms in FGWC, such as Particle Swarm Optimisation (PSO) and Intelligent Firefly Algorithm (IFA). This study found that ETLBO performs well in identifying Indonesia’s regional economic condition. Moreover, the clustering results showed the difference of problematic sectors. We also found that the provinces in Java Island joined into a cluster and have problems in many sectors. This study can be used as the basis for the evaluation of regional economic conditions in Indonesia.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"18 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":"122758457","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/ICISIT54091.2022.9872945
Ibnu Da’wan Salim Ubaidah, Y. Fu’adah, Sofia Sa’idah, R. Magdalena, Abel Bima Wiratama, Richard Bina Jadi Simanjuntak
Glaucoma is a damaged optic nerve due to increased pressure on the eyeball. The cause is a mismatch between eye fluid (aqueous humor) produced and the amount of eye fluid secreted. Ophthalmologists usually detect glaucoma using Cup to Disc Ratio or CDR parameter. However, the calculation of CDR parameters is still done manually, usually done by trained doctors and relatively expensive and limited equipment. This study proposes a system that can classify glaucoma using the Convolutional Neural Network method with MobileNet architecture. MobileNet has two convolution parts: depthwise convolution and pointwise convolution. The function of the Depthwise Convolution is to apply a single convolution filter per input channel, while the function of the pointwise convolution is to build new features by calculating the linear combination of the input channels by applying the 1x1 convolution. The data used comes from rimone-r1 database. Result accuracy of the proposed method reaches 99%. Automated glaucoma classification can assist medical staff in identifying the best treatment for their patients.
{"title":"Classification of Glaucoma in Fundus Images Using Convolutional Neural Network with MobileNet Architecture","authors":"Ibnu Da’wan Salim Ubaidah, Y. Fu’adah, Sofia Sa’idah, R. Magdalena, Abel Bima Wiratama, Richard Bina Jadi Simanjuntak","doi":"10.1109/ICISIT54091.2022.9872945","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872945","url":null,"abstract":"Glaucoma is a damaged optic nerve due to increased pressure on the eyeball. The cause is a mismatch between eye fluid (aqueous humor) produced and the amount of eye fluid secreted. Ophthalmologists usually detect glaucoma using Cup to Disc Ratio or CDR parameter. However, the calculation of CDR parameters is still done manually, usually done by trained doctors and relatively expensive and limited equipment. This study proposes a system that can classify glaucoma using the Convolutional Neural Network method with MobileNet architecture. MobileNet has two convolution parts: depthwise convolution and pointwise convolution. The function of the Depthwise Convolution is to apply a single convolution filter per input channel, while the function of the pointwise convolution is to build new features by calculating the linear combination of the input channels by applying the 1x1 convolution. The data used comes from rimone-r1 database. Result accuracy of the proposed method reaches 99%. Automated glaucoma classification can assist medical staff in identifying the best treatment for their patients.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"16 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":"115090829","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/ICISIT54091.2022.9873077
Vina Ardelia Effendy, Y. Ruldeviyani, Muhammad Muslim Rifa’i, Vien Aulia Rahmatika, Wiwin Nur’Aini, Yosua Pangihutan Sagala
Information security is a critical national policy issue. Cyber-attacks and information security breaches are becoming more and more common. Fears of a growing attack could occur far outnumber the recorded cases. This is felt at the XYZ Polytechnic, there were 926 cases of Brute Password Attacks in the third quarter of 2021. Efforts for information security have not been fully carried out. Therefore, it is necessary to know the level of information security awareness, especially among XYZ Polytechnic employees, and develop strategies to improve information security. The measurement uses HAIS-Q with seven areas of information security. An information security assessment is processed using AHP method. This study pointed out that the value of focus area was at the medium level of consciousness (66.5%). Based on the results obtained, diverse strategies in terms of technology and human resources are required to supervise and raise the level of information security awareness at XYZ Polytechnic.
{"title":"Measurement of Employee Information Security Awareness on Data Security: A Case Study at XYZ Polytechnic","authors":"Vina Ardelia Effendy, Y. Ruldeviyani, Muhammad Muslim Rifa’i, Vien Aulia Rahmatika, Wiwin Nur’Aini, Yosua Pangihutan Sagala","doi":"10.1109/ICISIT54091.2022.9873077","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9873077","url":null,"abstract":"Information security is a critical national policy issue. Cyber-attacks and information security breaches are becoming more and more common. Fears of a growing attack could occur far outnumber the recorded cases. This is felt at the XYZ Polytechnic, there were 926 cases of Brute Password Attacks in the third quarter of 2021. Efforts for information security have not been fully carried out. Therefore, it is necessary to know the level of information security awareness, especially among XYZ Polytechnic employees, and develop strategies to improve information security. The measurement uses HAIS-Q with seven areas of information security. An information security assessment is processed using AHP method. This study pointed out that the value of focus area was at the medium level of consciousness (66.5%). Based on the results obtained, diverse strategies in terms of technology and human resources are required to supervise and raise the level of information security awareness at XYZ Polytechnic.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"23 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":"115314432","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/ICISIT54091.2022.9872994
A. Wibawa, Yuri Pamungkas, Muhammad Ilham Perdana, Ratih Rachmatika
Biometrics is a measurement of a person's physical and behavioral characteristics. Iris image is one of many biometrics data such as fingerprint, voice, face, and gait that can be used as an identifier. Iris is the colored part of the eye that helps the pupil see clearly and regulates light entry. Iris recognition is one of the important topics in biometric systems because of its unique pattern. Several related studies have been carried out to automatically obtain the most efficient method to understand and recognize the iris for human verification. This study proposes an analysis of iris images for biometrics systems with effective image processing techniques for system recognition. CVBL Iris image dataset was used in this study with 4320 iris images. After converting the iris image into a rectangle form, the Grid iris image experiment was implemented to find the highest accuracy. Several iris image grid-size were simulated to find the best accuracy. Multinomial Naive Bayes is used as a classifier. The Naive Bayes method is a machine learning method that uses probability calculations (rules-based). This algorithm uses probability and statistical methods, which predict future probabilities based on the previous data. The study results indicate that the proposed method can recognize the iris by identifying its fibers and encoding the fibers data using a grid image approach, with a classification accuracy of 92.37%, using an iris grid size of 70x50 pixels. This research can be useful for developing human biometric systems based on iris with a simple preprocessing approach.
{"title":"Iris Grid Image Classification using Naive Bayes for Human Biometric System","authors":"A. Wibawa, Yuri Pamungkas, Muhammad Ilham Perdana, Ratih Rachmatika","doi":"10.1109/ICISIT54091.2022.9872994","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872994","url":null,"abstract":"Biometrics is a measurement of a person's physical and behavioral characteristics. Iris image is one of many biometrics data such as fingerprint, voice, face, and gait that can be used as an identifier. Iris is the colored part of the eye that helps the pupil see clearly and regulates light entry. Iris recognition is one of the important topics in biometric systems because of its unique pattern. Several related studies have been carried out to automatically obtain the most efficient method to understand and recognize the iris for human verification. This study proposes an analysis of iris images for biometrics systems with effective image processing techniques for system recognition. CVBL Iris image dataset was used in this study with 4320 iris images. After converting the iris image into a rectangle form, the Grid iris image experiment was implemented to find the highest accuracy. Several iris image grid-size were simulated to find the best accuracy. Multinomial Naive Bayes is used as a classifier. The Naive Bayes method is a machine learning method that uses probability calculations (rules-based). This algorithm uses probability and statistical methods, which predict future probabilities based on the previous data. The study results indicate that the proposed method can recognize the iris by identifying its fibers and encoding the fibers data using a grid image approach, with a classification accuracy of 92.37%, using an iris grid size of 70x50 pixels. This research can be useful for developing human biometric systems based on iris with a simple preprocessing approach.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"51 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":"122644452","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/ICISIT54091.2022.9872751
H. Palit, Indar Sugiarto, D. Prayogo, Alexander T.K. Pratomo
Genetic Algorithm (GA) is one of the most popular optimization techniques. Inspired by the theory of evolution and natural selection, it is also famous for its simplicity and versatility. Hence, it has been applied in diverse fields and domains. However, since it involves iterative and evolutionary processes, it takes a long time to obtain optimal solutions. To improve its performance, in this research work, we had parallelized GA processes to enable searching through the solution space with concurrent efforts. We had experimented with both CPU and GPU architectures. Speedups of GA solutions on CPU architecture range from 7.2 to 22.2, depending on the number of processing cores in the CPU. By contrast, speed-ups of GA solutions on GPU architecture can reach up to 172.4.
{"title":"Performance Analysis of a Parallel Genetic Algorithm: A Case Study of the Traveling Salesman Problem","authors":"H. Palit, Indar Sugiarto, D. Prayogo, Alexander T.K. Pratomo","doi":"10.1109/ICISIT54091.2022.9872751","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872751","url":null,"abstract":"Genetic Algorithm (GA) is one of the most popular optimization techniques. Inspired by the theory of evolution and natural selection, it is also famous for its simplicity and versatility. Hence, it has been applied in diverse fields and domains. However, since it involves iterative and evolutionary processes, it takes a long time to obtain optimal solutions. To improve its performance, in this research work, we had parallelized GA processes to enable searching through the solution space with concurrent efforts. We had experimented with both CPU and GPU architectures. Speedups of GA solutions on CPU architecture range from 7.2 to 22.2, depending on the number of processing cores in the CPU. By contrast, speed-ups of GA solutions on GPU architecture can reach up to 172.4.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"40 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":"125823688","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/ICISIT54091.2022.9872550
Muhammad Fadhurrahman, A. H. Saputro
Peatlands have an important role as global climate regulators because they store global amounts of carbon which, if degraded, will result in increased concentrations of greenhouse gases in the atmosphere. Peatland mapping using satellite imagery is considered effective for classifying a land cover area. Previous studies concluded that satellite imagery can be used to classify a peat area and a non-peat area. In this study, we use satellite imagery with a mounted MODIS sensor from 2015-2019 and calculate the index from MODIS bands. The Machine Learning (ML) method was used for generating a peat depth in Pulang Pisau, Kalimantan. Random Forest (RF), Support Vector Machine (SVM), Support Vector Regressor (SVR), Gradient Boosting (GB), and Ada Boost (AB) models were used to generate a peat depth map. The best performance was achieved by RF Classifier with accuracy 0.93 and RF Regressor with ${R}^{2}=0.88$
{"title":"Peat Depth Prediction System Using Long-Term MODIS Data And Random Forest Algorithm: A Case Study in Pulang Pisau, Kalimantan","authors":"Muhammad Fadhurrahman, A. H. Saputro","doi":"10.1109/ICISIT54091.2022.9872550","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872550","url":null,"abstract":"Peatlands have an important role as global climate regulators because they store global amounts of carbon which, if degraded, will result in increased concentrations of greenhouse gases in the atmosphere. Peatland mapping using satellite imagery is considered effective for classifying a land cover area. Previous studies concluded that satellite imagery can be used to classify a peat area and a non-peat area. In this study, we use satellite imagery with a mounted MODIS sensor from 2015-2019 and calculate the index from MODIS bands. The Machine Learning (ML) method was used for generating a peat depth in Pulang Pisau, Kalimantan. Random Forest (RF), Support Vector Machine (SVM), Support Vector Regressor (SVR), Gradient Boosting (GB), and Ada Boost (AB) models were used to generate a peat depth map. The best performance was achieved by RF Classifier with accuracy 0.93 and RF Regressor with ${R}^{2}=0.88$","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":"126690009","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/ICISIT54091.2022.9872851
M. A. Pramudito, Y. Fu’adah, R. Magdalena, Achmad Rizal, F. F. Taliningsih
Heart disease is one of the leading causes of death in the world. Congestive Heart Failure (CHF) is one type of heart disease that needs attention. CHF is a condition in which the heart cannot pump blood adequately throughout the body. This disease usually affects patients over the age of 60 years. An EKG can be used to diagnose this condition. However, doctors need to diagnose manually, namely, reading the ECG signal directly. Therefore, this study aims to create a system that can diagnose CHF automatically using the 1D convolutional neural network (CNN) method. This CNN 1D method uses normalization as preprocessing, three hidden layers with 16 output channels, a fully connected layer, and sigmoid activation. The research dataset comes from MIT-BIH and BIDMC. Based on this study, 100% accuracy results were obtained with recall, precision, and 1 F1-Score, respectively, so this study can assist medical staff in identifying CHF conditions and providing appropriate therapy to patients.
{"title":"ECG signal processing using 1-D Convolutional Neural Network for Congestive Heart Failure Identification","authors":"M. A. Pramudito, Y. Fu’adah, R. Magdalena, Achmad Rizal, F. F. Taliningsih","doi":"10.1109/ICISIT54091.2022.9872851","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872851","url":null,"abstract":"Heart disease is one of the leading causes of death in the world. Congestive Heart Failure (CHF) is one type of heart disease that needs attention. CHF is a condition in which the heart cannot pump blood adequately throughout the body. This disease usually affects patients over the age of 60 years. An EKG can be used to diagnose this condition. However, doctors need to diagnose manually, namely, reading the ECG signal directly. Therefore, this study aims to create a system that can diagnose CHF automatically using the 1D convolutional neural network (CNN) method. This CNN 1D method uses normalization as preprocessing, three hidden layers with 16 output channels, a fully connected layer, and sigmoid activation. The research dataset comes from MIT-BIH and BIDMC. Based on this study, 100% accuracy results were obtained with recall, precision, and 1 F1-Score, respectively, so this study can assist medical staff in identifying CHF conditions and providing appropriate therapy to patients.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"4 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":"132659011","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/ICISIT54091.2022.9872939
Anastassya Gustirani, M. Saputra, Warih Puspitasari
PT. XYZ is a state-owned fast-growing enterprise that runs in telecommunication and technology industry that use activity-based costing as their cost allocation method using SAP S/4 HANA as a platform to perform the process. However, the user currently through a repetitive activity in the cost driver mapping process. The user has to repetitively adjust the template to input the cost driver data to page KB31N and has to repetitively check which cost driver has already inputted to the system to make sure that there is no redundance. Unfortunately, the current SAP system does not provide the user with the accessible template to input the cost driver information and the information of the cost driver that haven’t been posted. To solve the user’s current needs and problems, two ALV reports were made to provide the desire information for the user of PT. XYZ which are called SKF posted report and SKF non posted report.
PT. XYZ是一家快速发展的国有企业，经营电信和技术行业，使用作业成本法作为成本分配方法，使用SAP S/4 HANA作为执行流程的平台。然而，用户目前在成本驱动映射过程中经历了重复的活动。用户必须反复调整模板以将成本驱动程序数据输入到KB31N页，并且必须反复检查哪些成本驱动程序已经输入到系统中，以确保没有冗余。遗憾的是，目前的SAP系统没有为用户提供可访问的模板来输入成本动因信息和尚未发布的成本动因信息。为了解决用户当前的需求和问题，我们制作了两个ALV报告，为PT. XYZ的用户提供所需的信息，这两个报告分别是SKF已发布报告和SKF未发布报告。
{"title":"Cost Driver Mapping for Budget Allocation Reporting in SAP FI-CO","authors":"Anastassya Gustirani, M. Saputra, Warih Puspitasari","doi":"10.1109/ICISIT54091.2022.9872939","DOIUrl":"https://doi.org/10.1109/ICISIT54091.2022.9872939","url":null,"abstract":"PT. XYZ is a state-owned fast-growing enterprise that runs in telecommunication and technology industry that use activity-based costing as their cost allocation method using SAP S/4 HANA as a platform to perform the process. However, the user currently through a repetitive activity in the cost driver mapping process. The user has to repetitively adjust the template to input the cost driver data to page KB31N and has to repetitively check which cost driver has already inputted to the system to make sure that there is no redundance. Unfortunately, the current SAP system does not provide the user with the accessible template to input the cost driver information and the information of the cost driver that haven’t been posted. To solve the user’s current needs and problems, two ALV reports were made to provide the desire information for the user of PT. XYZ which are called SKF posted report and SKF non posted report.","PeriodicalId":214014,"journal":{"name":"2022 1st International Conference on Information System & Information Technology (ICISIT)","volume":"18 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":"122215836","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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