Sularno Sularno, R. Astri, P. Anggraini, Dio Prima Mulya, D. Mulya
Purpose: One of the main objectives of the research is the BFS (Breadth-First Search) algorithm method in the search for nearby bus and travel counters using GPS found on each device used in the search process. Each smartphone produces a different coordinate point with an average distance difference of 30.2 meters to the hardware coordinate point. Each GPS embedded in the smartphone will process the data according to the location conditions of the user's point of existence. The methodology for system development is a standard process for a team of developers to connect all the steps needed in analyzing, designing, implementing, and maintaining information systems. Methods: The methodology becomes a guideline in system development activities in SDLC. The SDLC model used in this study is the WaterFall Model. Result: The results of this study are expected to facilitate the public in booking tickets and to find the nearest location from the bus and travel counters. Novelty: The novelty of this research is the development of GIS as a search for the location of bus and travel counters using the breadth-first search algorithm. This research can help the community find the location of the nearest bus and tourist counter in the city of Padang.
{"title":"Geographical Information System of Bus and Travel Counter in Padang City Using BFS Method Based on Mobile Web","authors":"Sularno Sularno, R. Astri, P. Anggraini, Dio Prima Mulya, D. Mulya","doi":"10.15294/sji.v8i2.33117","DOIUrl":"https://doi.org/10.15294/sji.v8i2.33117","url":null,"abstract":"Purpose: One of the main objectives of the research is the BFS (Breadth-First Search) algorithm method in the search for nearby bus and travel counters using GPS found on each device used in the search process. Each smartphone produces a different coordinate point with an average distance difference of 30.2 meters to the hardware coordinate point. Each GPS embedded in the smartphone will process the data according to the location conditions of the user's point of existence. The methodology for system development is a standard process for a team of developers to connect all the steps needed in analyzing, designing, implementing, and maintaining information systems. Methods: The methodology becomes a guideline in system development activities in SDLC. The SDLC model used in this study is the WaterFall Model. Result: The results of this study are expected to facilitate the public in booking tickets and to find the nearest location from the bus and travel counters. Novelty: The novelty of this research is the development of GIS as a search for the location of bus and travel counters using the breadth-first search algorithm. This research can help the community find the location of the nearest bus and tourist counter in the city of Padang.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42704186","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}
Purpose: Many studies have conducted studies related to automation for image-based plant species identification recently. Types of plants, in general, can be identified by looking at the shape of the leaves, colors, stems, flowers, and others. Not everyone can immediately recognize the types of plants scattered around the environment. In Indonesia, herbal plants thrive and are abundantly found and used as a concoction of traditional medicine known for its medicinal properties from generation to generation. In the current Z-generation era, children lack an understanding of the types of plants that benefit life. This study identifies and predicts the pattern of the leaf shape of herbal plants. Methods: The dataset used in this study used 15 types of herbal plants with 30 leaf data for each plant to obtain 450 data used. The extraction process uses the GLCM algorithm, and classification uses the K-NN algorithm. Result: The results carried out through the testing process in this study showed that the accuracy rate of the leaf pattern prediction process was 74% of the total 15 types of plants used. Value: Process of identifying and predicting leaf patterns of herbal plants can be applied using the K-NN classification algorithm combined with GLCM with the level of accuracy obtained.
{"title":"Model for Identification and Prediction of Leaf Patterns: Preliminary Study for Improvement","authors":"A. Muzakir, U. Ependi","doi":"10.15294/sji.v8i2.30024","DOIUrl":"https://doi.org/10.15294/sji.v8i2.30024","url":null,"abstract":"Purpose: Many studies have conducted studies related to automation for image-based plant species identification recently. Types of plants, in general, can be identified by looking at the shape of the leaves, colors, stems, flowers, and others. Not everyone can immediately recognize the types of plants scattered around the environment. In Indonesia, herbal plants thrive and are abundantly found and used as a concoction of traditional medicine known for its medicinal properties from generation to generation. In the current Z-generation era, children lack an understanding of the types of plants that benefit life. This study identifies and predicts the pattern of the leaf shape of herbal plants. Methods: The dataset used in this study used 15 types of herbal plants with 30 leaf data for each plant to obtain 450 data used. The extraction process uses the GLCM algorithm, and classification uses the K-NN algorithm. Result: The results carried out through the testing process in this study showed that the accuracy rate of the leaf pattern prediction process was 74% of the total 15 types of plants used. Value: Process of identifying and predicting leaf patterns of herbal plants can be applied using the K-NN classification algorithm combined with GLCM with the level of accuracy obtained.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44259308","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}
Malnutrition is characterized as muscle weakening and cognitive disparity caused by social, dietary, political, food security issues. It appears as many underlying symptoms like fatigue, weakness, micronutrient deficiencies, weight loss to apparent symptoms of muscle mass reduction. Every 1 in 5 children is malnourished in developing countries. Purpose: Policies and program formulation require prevalence facts to classify the most prevalent cause. Diagnostic tools and computer modeling have revolutionized the world of health sciences. Much algorithmic formulation can help to predict the prognosis of diseases based on the previous fact sheets. Methods/Study design/approach: Naïve Bayes provides the posterior probability value that gives an analysis of the member with the whole sample set. Forward chaining gives the logistic conclusion with IF and THEN approach. Result/Findings: Naïve Bayes provided high accuracy of 88% as compared to 85% forward chaining. Novelty/Originality/Value: In this study, the Naïve Bayes algorithm approach is coupled with the forward chaining system to provide a highly accurate measurement of the cause of malnutrition.
{"title":"Accuracy Measurements and Decision Making by Naïve Bayes and Forward Chaining Method to Identify the Malnutrition Causes and Symptoms","authors":"Muhammad Ibtasam","doi":"10.15294/sji.v8i2.29317","DOIUrl":"https://doi.org/10.15294/sji.v8i2.29317","url":null,"abstract":"Malnutrition is characterized as muscle weakening and cognitive disparity caused by social, dietary, political, food security issues. It appears as many underlying symptoms like fatigue, weakness, micronutrient deficiencies, weight loss to apparent symptoms of muscle mass reduction. Every 1 in 5 children is malnourished in developing countries. Purpose: Policies and program formulation require prevalence facts to classify the most prevalent cause. Diagnostic tools and computer modeling have revolutionized the world of health sciences. Much algorithmic formulation can help to predict the prognosis of diseases based on the previous fact sheets. Methods/Study design/approach: Naïve Bayes provides the posterior probability value that gives an analysis of the member with the whole sample set. Forward chaining gives the logistic conclusion with IF and THEN approach. Result/Findings: Naïve Bayes provided high accuracy of 88% as compared to 85% forward chaining. Novelty/Originality/Value: In this study, the Naïve Bayes algorithm approach is coupled with the forward chaining system to provide a highly accurate measurement of the cause of malnutrition.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41530411","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}
Tri Mar'ati Nur Utami, D. C. R. Novitasari, F. Setiawan, Nurissaidah Ulinnuha, Yuniar Farida
Purpose: Prigi Beach has the largest fishing port in East Java, but the topography of this beach is quite gentle, so it is prone to disasters such as tidal flooding. The tides of seawater strongly influence the occurrence of this natural event. Therefore, information on tidal level data is essential. This study aims to provide information about tidal predictions.Methods: In this case using the SVE method. Input data and time were examined using PACF autocorrelation plots to form input data patterns. The working principle of SVR is to find the best hyperplane in the form of a function that produces the slightest error.Result: The best SVR model built from the linear kernel, the MAPE value is 0.5510%, the epsilon is 0.0614, and the bias is 0.6015. The results of the tidal prediction on Prigi Beach in September 2020 showed that the highest tide occurred on September 19, 2020, at 10.00 PM, and the lowest tide occurred on September 3, 2020, at 04.00 AM. Value: After conducting experiments on three types of kernels on SVR, it is said that linear kernels can predict improvements better than polynomial and gaussian kernels.
{"title":"Tide Prediction in Prigi Beach using Support Vector Regression (SVR) Method","authors":"Tri Mar'ati Nur Utami, D. C. R. Novitasari, F. Setiawan, Nurissaidah Ulinnuha, Yuniar Farida","doi":"10.15294/sji.v8i2.28906","DOIUrl":"https://doi.org/10.15294/sji.v8i2.28906","url":null,"abstract":"Purpose: Prigi Beach has the largest fishing port in East Java, but the topography of this beach is quite gentle, so it is prone to disasters such as tidal flooding. The tides of seawater strongly influence the occurrence of this natural event. Therefore, information on tidal level data is essential. This study aims to provide information about tidal predictions.Methods: In this case using the SVE method. Input data and time were examined using PACF autocorrelation plots to form input data patterns. The working principle of SVR is to find the best hyperplane in the form of a function that produces the slightest error.Result: The best SVR model built from the linear kernel, the MAPE value is 0.5510%, the epsilon is 0.0614, and the bias is 0.6015. The results of the tidal prediction on Prigi Beach in September 2020 showed that the highest tide occurred on September 19, 2020, at 10.00 PM, and the lowest tide occurred on September 3, 2020, at 04.00 AM. Value: After conducting experiments on three types of kernels on SVR, it is said that linear kernels can predict improvements better than polynomial and gaussian kernels.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49200275","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. Amiruddin, P. Suryani, Shandika Dianaji Santoso, Muhammad Yusuf Bambang Setiadji
Purpose: Malicious software or malware is a real threat to the security of computer systems or networks. Researchers made various attempts to find information and knowledge about malware, including preventing or even eliminating it. One effort to detect it is using a malware dynamic analysis model based on reverse engineering techniques. However, there are many reverse engineering techniques proposed with various stages and requirements in the literature. Methods: This research uses an experimental method. The object of research is a malware analysis model using reverse engineering techniques. The experimental method used is qualitative, collecting data related to the advantages and disadvantages of the reverse engineering-based malware analysis models used as a reference in this study. The data is used as consideration to propose a new model of malware analysis utilizing reverse engineering techniques. Result: In this study an analysis model of malware was proposed by synthesizing several reverse engineering-based malware analysis models. Novelty: The proposed model was then tested in a virtual environment where it is proven to be more effective than previous models for analyzing malware.
{"title":"Utilizing Reverse Engineering Technique for A Malware Analysis Model","authors":"A. Amiruddin, P. Suryani, Shandika Dianaji Santoso, Muhammad Yusuf Bambang Setiadji","doi":"10.15294/sji.v8i2.24755","DOIUrl":"https://doi.org/10.15294/sji.v8i2.24755","url":null,"abstract":"Purpose: Malicious software or malware is a real threat to the security of computer systems or networks. Researchers made various attempts to find information and knowledge about malware, including preventing or even eliminating it. One effort to detect it is using a malware dynamic analysis model based on reverse engineering techniques. However, there are many reverse engineering techniques proposed with various stages and requirements in the literature. Methods: This research uses an experimental method. The object of research is a malware analysis model using reverse engineering techniques. The experimental method used is qualitative, collecting data related to the advantages and disadvantages of the reverse engineering-based malware analysis models used as a reference in this study. The data is used as consideration to propose a new model of malware analysis utilizing reverse engineering techniques. Result: In this study an analysis model of malware was proposed by synthesizing several reverse engineering-based malware analysis models. Novelty: The proposed model was then tested in a virtual environment where it is proven to be more effective than previous models for analyzing malware.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42606011","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}
M. Anam, Torkis Nasution, Susi Erlinda, Lusiana Efrizoni, S. Susanti
Purpose: The IT Blueprint is used as a guideline in achieving organizational goals, such as the built and development of information technology (IT) infrastructure. STMIK Amik Riau is one of the universities vision to become an excellent university in Sumatra by 2030. To achieve this vision, it is necessary to develop various units, one of which is the built and development of IT in student services. To build IT for student services, an enterprise architecture is needed so that the development is more focused. Study design: In this study, TOGAF became the framework used to design, plan, implement, and manage the company's organizational architecture. TOGAF has 8 phases, but this research takes 6 phases: Architecture Vision, Business Architecture, Information System Architectures, Technology Architecture, Opportunities and Solutions, and Migration Planning. Result: The results obtained in this study are the creation of IT blueprints for student business processes. There are several updates in each process, especially in the information system architecture, then in business processes and technology. There are also updates that need to be done. This study also provides several reasons for updating the Opportunity and Solutions. Other than that, this research guides to apply the updates based on priorities that must be applied to migration planning. Novelty: In the information system architecture, 18 applications become service systems for students. After analyzing it into 31 applications, they will later be used to support good services for students.
{"title":"The Analysis and Optimization of Business Processes for Students in Higher Education Based on Togaf 9.2","authors":"M. Anam, Torkis Nasution, Susi Erlinda, Lusiana Efrizoni, S. Susanti","doi":"10.15294/sji.v8i2.29952","DOIUrl":"https://doi.org/10.15294/sji.v8i2.29952","url":null,"abstract":"Purpose: The IT Blueprint is used as a guideline in achieving organizational goals, such as the built and development of information technology (IT) infrastructure. STMIK Amik Riau is one of the universities vision to become an excellent university in Sumatra by 2030. To achieve this vision, it is necessary to develop various units, one of which is the built and development of IT in student services. To build IT for student services, an enterprise architecture is needed so that the development is more focused. Study design: In this study, TOGAF became the framework used to design, plan, implement, and manage the company's organizational architecture. TOGAF has 8 phases, but this research takes 6 phases: Architecture Vision, Business Architecture, Information System Architectures, Technology Architecture, Opportunities and Solutions, and Migration Planning. Result: The results obtained in this study are the creation of IT blueprints for student business processes. There are several updates in each process, especially in the information system architecture, then in business processes and technology. There are also updates that need to be done. This study also provides several reasons for updating the Opportunity and Solutions. Other than that, this research guides to apply the updates based on priorities that must be applied to migration planning. Novelty: In the information system architecture, 18 applications become service systems for students. After analyzing it into 31 applications, they will later be used to support good services for students.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48027660","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}
Purpose: Currently, many fake certificates or diplomas are used to apply for jobs to get a better paying job. With that said, currently certificates cannot prove a person's expertise or skills. However, some students have implemented a Blockchain system in securing their certificates so that data manipulation is minimized, but only partially. Therefore, this research aims to motivate anyone, especially students in this Blockchain system and students will get incentives from all activities that are followed by racing in Blockchain gamification concept 4.0. Study design: This study uses the Pieces method to classify a problem (problem), opportunities (opportunities), and existing directions. Data collection techniques used primary data obtained by distributing questionnaires in the form of google form to respondents by involving students (n = 1129). Conclusions were analyzed with the SUS trial using a Likert scale with the cut and SUS method. Result: The results of this study are expected to Gamification in the system Blockchain can run optimally in implementation. The use of Gamification on the Alphabet Blockchain is included in the acceptable category. Value: The platform can check certificates that are not genuine.
{"title":"Collaboration Blockchain Technology and Gamification in iLearning systems","authors":"Reza Filander Nevizond, U. Rahardja, Nuke Puji Lestari Santoso, Suryari Purnama, Wahyu Yustika Prihastiwi","doi":"10.15294/sji.v8i2.31889","DOIUrl":"https://doi.org/10.15294/sji.v8i2.31889","url":null,"abstract":"Purpose: Currently, many fake certificates or diplomas are used to apply for jobs to get a better paying job. With that said, currently certificates cannot prove a person's expertise or skills. However, some students have implemented a Blockchain system in securing their certificates so that data manipulation is minimized, but only partially. Therefore, this research aims to motivate anyone, especially students in this Blockchain system and students will get incentives from all activities that are followed by racing in Blockchain gamification concept 4.0. Study design: This study uses the Pieces method to classify a problem (problem), opportunities (opportunities), and existing directions. Data collection techniques used primary data obtained by distributing questionnaires in the form of google form to respondents by involving students (n = 1129). Conclusions were analyzed with the SUS trial using a Likert scale with the cut and SUS method. Result: The results of this study are expected to Gamification in the system Blockchain can run optimally in implementation. The use of Gamification on the Alphabet Blockchain is included in the acceptable category. Value: The platform can check certificates that are not genuine.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47908302","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}
Made Sukarsa, I. N. Piarsa, Erlangga Bayu Linggar Sukarta, N. Wisswani
Purpose: Dua Mata is a mobile and website-based community service application intended for residents of South Kuta. Evaluation of existing designs is needed to assess whether the user interface design can provide user satisfaction. The aim this paper to evaluate the UI/UX of Dua Mata using QUIM method. Methods: Research, Modeling, requirement definition, Framework Definition, and Refinements are the step of the GDD method. The QUIM method aims to prioritize indicators that need to be fixed in the old design: Resource Utilization, Minimal Memory Load, and Security. Modeling determined respondents who will do the second test and in requirement definition stage scenarios are chosen. The selected scenario is registering, forgetting passwords, searching directories, ordering, and adding services. The framework definition and refinement is the stage of making a wireframe then prototype and tested. Result: The test results showed a big decrease in the scenario completion time by 39.41 seconds in the register scenario. The score on the Resource Utilization indicator has increased by 8 points, the Minimum Memory Load indicator is 9 points and the Security indicator is 6 points. Novelty: The novelty is that the increasing of the Resource Utilization indicator indicates the new design has a higher level of user satisfaction than the old design
{"title":"Goal Directed Design Method Application on UI/UX of Dua Mata Mobile Apps","authors":"Made Sukarsa, I. N. Piarsa, Erlangga Bayu Linggar Sukarta, N. Wisswani","doi":"10.15294/sji.v8i2.30216","DOIUrl":"https://doi.org/10.15294/sji.v8i2.30216","url":null,"abstract":"Purpose: Dua Mata is a mobile and website-based community service application intended for residents of South Kuta. Evaluation of existing designs is needed to assess whether the user interface design can provide user satisfaction. The aim this paper to evaluate the UI/UX of Dua Mata using QUIM method. Methods: Research, Modeling, requirement definition, Framework Definition, and Refinements are the step of the GDD method. The QUIM method aims to prioritize indicators that need to be fixed in the old design: Resource Utilization, Minimal Memory Load, and Security. Modeling determined respondents who will do the second test and in requirement definition stage scenarios are chosen. The selected scenario is registering, forgetting passwords, searching directories, ordering, and adding services. The framework definition and refinement is the stage of making a wireframe then prototype and tested. Result: The test results showed a big decrease in the scenario completion time by 39.41 seconds in the register scenario. The score on the Resource Utilization indicator has increased by 8 points, the Minimum Memory Load indicator is 9 points and the Security indicator is 6 points. Novelty: The novelty is that the increasing of the Resource Utilization indicator indicates the new design has a higher level of user satisfaction than the old design","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49342379","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}
Purpose: Heart failure is a disease that is still a global threat and plays a major role as the number one cause of death worldwide. Therefore, accurate predictions are needed to determine the survival of heart failure patients. One technique that can be used to predict a decision is classification. Adaptive Neuro-Fuzzy Inference System (ANFIS) is an algorithm that can be used in the classification process in making predictions. Genetic Algorithms can help improve the performance of classification algorithms through the feature selection process. Methods/Study design/approach: In this study, predictions or diagnoses were made on the survival of heart failure patients based on the heart failure clinical record dataset obtained from the UCI Machine Learning Repository. The data used is 299 data with 12 attributes and 1 class. The result of this research is the comparison of the accuracy of the ANFIS algorithm before and after using the Genetic Algorithm. Result/Findings: The ANFIS algorithm produces the highest accuracy of 94.444%. While the ANFIS algorithm after attribute selection using the Genetic Algorithm produces the highest accuracy of 96.667%. This shows that the Genetic Algorithm is able to improve the performance of the ANFIS classification algorithm through the attribute selection process.
{"title":"Implementation of Genetic Algorithm and Adaptive Neuro Fuzzy Inference System in Predicting Survival of Patients with Heart Failure","authors":"Dian Alya Korzhakin, E. Sugiharti","doi":"10.15294/sji.v8i2.32803","DOIUrl":"https://doi.org/10.15294/sji.v8i2.32803","url":null,"abstract":"Purpose: Heart failure is a disease that is still a global threat and plays a major role as the number one cause of death worldwide. Therefore, accurate predictions are needed to determine the survival of heart failure patients. One technique that can be used to predict a decision is classification. Adaptive Neuro-Fuzzy Inference System (ANFIS) is an algorithm that can be used in the classification process in making predictions. Genetic Algorithms can help improve the performance of classification algorithms through the feature selection process. Methods/Study design/approach: In this study, predictions or diagnoses were made on the survival of heart failure patients based on the heart failure clinical record dataset obtained from the UCI Machine Learning Repository. The data used is 299 data with 12 attributes and 1 class. The result of this research is the comparison of the accuracy of the ANFIS algorithm before and after using the Genetic Algorithm. Result/Findings: The ANFIS algorithm produces the highest accuracy of 94.444%. While the ANFIS algorithm after attribute selection using the Genetic Algorithm produces the highest accuracy of 96.667%. This shows that the Genetic Algorithm is able to improve the performance of the ANFIS classification algorithm through the attribute selection process.","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47244334","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}
Purpose: The study aims to reduce the number of irrelevant features in sentiment analysis with large features. Methods/Study design/approach: The Support Vector Machine (SVM) algorithm is used to classify hotel review sentiment analysis because it has advantages in processing large datasets. Term Frequency-Inverse Document Frequency (TF-IDF) is used to give weight values to features in the dataset. Result/Findings: This study's results indicate that the accuracy of the SVM method with TF-IDF produces an accuracy of 93.14%, and the SVM method in the classification of hotel reviews by implementing TFIDF and CFS has increased by 1.18% from 93.14% to 94.32%. Novelty/Originality/Value: Use of Correlation-Based Feature Section (CFS) for the feature selection process, which reduces the number of irrelevant features by ranking the feature subset based on the strong correlation value in each feature
{"title":"Implementation of Support Vector Machine Algorithm with Correlation-Based Feature Selection and Term Frequency Inverse Document Frequency for Sentiment Analysis Review Hotel","authors":"Novia Puji Ririanti, A. Purwinarko","doi":"10.15294/sji.v8i2.29992","DOIUrl":"https://doi.org/10.15294/sji.v8i2.29992","url":null,"abstract":"Purpose: The study aims to reduce the number of irrelevant features in sentiment analysis with large features. Methods/Study design/approach: The Support Vector Machine (SVM) algorithm is used to classify hotel review sentiment analysis because it has advantages in processing large datasets. Term Frequency-Inverse Document Frequency (TF-IDF) is used to give weight values to features in the dataset. Result/Findings: This study's results indicate that the accuracy of the SVM method with TF-IDF produces an accuracy of 93.14%, and the SVM method in the classification of hotel reviews by implementing TFIDF and CFS has increased by 1.18% from 93.14% to 94.32%. Novelty/Originality/Value: Use of Correlation-Based Feature Section (CFS) for the feature selection process, which reduces the number of irrelevant features by ranking the feature subset based on the strong correlation value in each feature","PeriodicalId":30781,"journal":{"name":"Scientific Journal of Informatics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41424379","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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