Continuous Hopfield network is a recurring network that has shown its ability to solve important optimization problems. Continuous Hopfield network dynamic system is characterized by a differential equation. This equation is difficult to solve, especially for large problems. This led researchers to discretize the differential equation using Euler’s method. However, this method generally does not converge to a good solution because it is sensitive to the step size decision and initial conditions. In this work, we discretize the dynamic system of continuous Hopfield network by a new method of Runge-Kutta. This method is strong in terms of stability and performance in order to converge to a better solution. This new method introduces two phases for better network stability. The first phase targets to solve the dynamic equation by the Euler method, while the second phase allows refining the solution found in the first phase. Experimental results on benchmarks show that the proposed approach can effectively improve Hopfield neural network performance.
{"title":"Improving Continuous Hopfield Network Stability Using Runge-Kutta Method","authors":"Mohammed El Alaoui, M. Ettaouil","doi":"10.47839/ijc.22.1.2876","DOIUrl":"https://doi.org/10.47839/ijc.22.1.2876","url":null,"abstract":"Continuous Hopfield network is a recurring network that has shown its ability to solve important optimization problems. Continuous Hopfield network dynamic system is characterized by a differential equation. This equation is difficult to solve, especially for large problems. This led researchers to discretize the differential equation using Euler’s method. However, this method generally does not converge to a good solution because it is sensitive to the step size decision and initial conditions. In this work, we discretize the dynamic system of continuous Hopfield network by a new method of Runge-Kutta. This method is strong in terms of stability and performance in order to converge to a better solution. This new method introduces two phases for better network stability. The first phase targets to solve the dynamic equation by the Euler method, while the second phase allows refining the solution found in the first phase. Experimental results on benchmarks show that the proposed approach can effectively improve Hopfield neural network performance.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75144807","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}
This paper deals with the development of two symmetric encryption algorithms on the basis of cellular automata: a block cipher, that is based on AES and uses three-dimensional cellular automata; a stream cipher, that exploits a hardware-software entropy generation (tracking of keystrokes and mouse pointer movement), as well as the developed hash function, based on “cryptographic sponge” architecture of SHA-3, modified by cellular automata transformations. The block cipher is designed in architecture of SP-network and uses the AES substitution block. Permutation layer and key generation is designed on the basis of cellular automata rules (rules “22”, “105” and “150”). The optimal number of rounds to achieve maximum crypto resistance is determined. The stream cipher is designed on the basis of hardware-software entropy generation and uses the cryptographic hash-function in the SHA-3 architecture. Permutation function is developed on the basis of cellular automata rules (rules “30” and “146”). The procedures of shift and permutation of rows and columns is used for better permutation. A final permutation of state elements is used to improve the avalanche effect. The received results are analyzed and summarized; the conclusions and justifications about cipher parameters (like number of rounds, where needed) are made.
{"title":"Symmetrical Cryptosystems based on Cellular Automata","authors":"Serhii Ostapov, Bohdan Diakonenko, Maksym Fylypiuk, K. Hazdiuk, Liliia Shumyliak, O.Yu. Tarnovetska","doi":"10.47839/ijc.22.1.2874","DOIUrl":"https://doi.org/10.47839/ijc.22.1.2874","url":null,"abstract":"This paper deals with the development of two symmetric encryption algorithms on the basis of cellular automata: a block cipher, that is based on AES and uses three-dimensional cellular automata; a stream cipher, that exploits a hardware-software entropy generation (tracking of keystrokes and mouse pointer movement), as well as the developed hash function, based on “cryptographic sponge” architecture of SHA-3, modified by cellular automata transformations. The block cipher is designed in architecture of SP-network and uses the AES substitution block. Permutation layer and key generation is designed on the basis of cellular automata rules (rules “22”, “105” and “150”). The optimal number of rounds to achieve maximum crypto resistance is determined. The stream cipher is designed on the basis of hardware-software entropy generation and uses the cryptographic hash-function in the SHA-3 architecture. Permutation function is developed on the basis of cellular automata rules (rules “30” and “146”). The procedures of shift and permutation of rows and columns is used for better permutation. A final permutation of state elements is used to improve the avalanche effect. The received results are analyzed and summarized; the conclusions and justifications about cipher parameters (like number of rounds, where needed) are made.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82014544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this article is to elaborate performance of the hybrid model of Simulated Annealing (SA) and 2 Opt algorithm for solving the traveling salesman problem (TSP). The SA algorithm used in this article is based on the outer and inner loop SA algorithm. The hybrid algorithm has promising results in solving small and medium-scale symmetric traveling salesman problem benchmark tests taken from the TSPLIB reference. Results of the optimal solution and standard deviation indicate that the hybrid algorithm shows good performance in terms of reliability and stability in finding the optimal solution from the TSP benchmark case. Values of average error and standard deviation for all simulations in the medium scale are 0.0267 and 644.12, respectively. Moreover, in some cases namely KroB100, Pr107, and Pr144, the hybrid algorithm finds a better solution compared with the best-known solution mentioned in the reference. Further, the hybrid algorithm is 1.207 – 5.692 times faster than the pure outer and inner loop-based SA algorithm. Additionally, the results show that the hybrid algorithm outperforms other hybrid algorithms such as SA – nearest neighbor (NN) and NN – 2 Opt.
{"title":"Simulated Annealing – 2 Opt Algorithm for Solving Traveling Salesman Problem","authors":"P. H. Gunawan, I. Iryanto","doi":"10.47839/ijc.22.1.2878","DOIUrl":"https://doi.org/10.47839/ijc.22.1.2878","url":null,"abstract":"The purpose of this article is to elaborate performance of the hybrid model of Simulated Annealing (SA) and 2 Opt algorithm for solving the traveling salesman problem (TSP). The SA algorithm used in this article is based on the outer and inner loop SA algorithm. The hybrid algorithm has promising results in solving small and medium-scale symmetric traveling salesman problem benchmark tests taken from the TSPLIB reference. Results of the optimal solution and standard deviation indicate that the hybrid algorithm shows good performance in terms of reliability and stability in finding the optimal solution from the TSP benchmark case. Values of average error and standard deviation for all simulations in the medium scale are 0.0267 and 644.12, respectively. Moreover, in some cases namely KroB100, Pr107, and Pr144, the hybrid algorithm finds a better solution compared with the best-known solution mentioned in the reference. Further, the hybrid algorithm is 1.207 – 5.692 times faster than the pure outer and inner loop-based SA algorithm. Additionally, the results show that the hybrid algorithm outperforms other hybrid algorithms such as SA – nearest neighbor (NN) and NN – 2 Opt.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88106912","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 search for an optimal value of a complex multi-dimensional continuous function is still one of the most pressing problems. The genetic algorithms (GA) and evolution strategies (ES) are methods to solving optimization problems that is based on natural selection, the process that drives biological evolution. Our goal was to use evolutionary optimization methods to find the global optimal value (minimum) of a non-smooth multi-dimensional function with a large number of local minimums. We took several test functions of different levels of complexity and used evolution strategies to solve the problem. The standard evolution strategies, which work well with smooth functions, gave us various points of local minimums as a solution, without finding the global minimum, for the complex function. In our work, we propose a new approach: the cross-selection method, which, in combination with previously developed methods - adaptive evolution strategies, gave a good result for the searth for the global minimum the complex function.
{"title":"Cross-Selection Based Evolution Strategies","authors":"L. Khilkova","doi":"10.47839/ijc.22.1.2881","DOIUrl":"https://doi.org/10.47839/ijc.22.1.2881","url":null,"abstract":"A search for an optimal value of a complex multi-dimensional continuous function is still one of the most pressing problems. The genetic algorithms (GA) and evolution strategies (ES) are methods to solving optimization problems that is based on natural selection, the process that drives biological evolution. Our goal was to use evolutionary optimization methods to find the global optimal value (minimum) of a non-smooth multi-dimensional function with a large number of local minimums. We took several test functions of different levels of complexity and used evolution strategies to solve the problem. The standard evolution strategies, which work well with smooth functions, gave us various points of local minimums as a solution, without finding the global minimum, for the complex function. In our work, we propose a new approach: the cross-selection method, which, in combination with previously developed methods - adaptive evolution strategies, gave a good result for the searth for the global minimum the complex function.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83195310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The fast algorithm to calculate carry signs and borrow signs for implementation of fast multi-digit operations in the parallel computational model is proposed. The proposed algorithm also makes it possible to predict carry signs in the case of an addition operation and predict borrow signs for a subtraction operation. It is shown how the sign prediction algorithm is implemented in operations in which each parallel processor proceeds the separate group of words into which multi-digit numbers are divided. The iterative calculations of carry signs of grouped words are described. The sign calculation algorithm as component of new modifications of multi-digit addition, subtraction, comparison, the sum of three or more numbers in the parallel computational model is presented. The sign calculation algorithm provides general approach to the implementation of multiplication, division, multiplication by modulo, exponentiation by modulo in the parallel computational model. In the form of a table, a general analysis of the complexity of algorithms and an analysis of the complexity by the number of single-word operations per processor are given.
{"title":"Algorithm for Calculation the Carry and Borrow Signs in Multi-digit Operations in the Parallel Computational Model","authors":"A. Tereshchenko, V. Zadiraka","doi":"10.47839/ijc.22.1.2875","DOIUrl":"https://doi.org/10.47839/ijc.22.1.2875","url":null,"abstract":"The fast algorithm to calculate carry signs and borrow signs for implementation of fast multi-digit operations in the parallel computational model is proposed. The proposed algorithm also makes it possible to predict carry signs in the case of an addition operation and predict borrow signs for a subtraction operation. It is shown how the sign prediction algorithm is implemented in operations in which each parallel processor proceeds the separate group of words into which multi-digit numbers are divided. The iterative calculations of carry signs of grouped words are described. The sign calculation algorithm as component of new modifications of multi-digit addition, subtraction, comparison, the sum of three or more numbers in the parallel computational model is presented. The sign calculation algorithm provides general approach to the implementation of multiplication, division, multiplication by modulo, exponentiation by modulo in the parallel computational model. In the form of a table, a general analysis of the complexity of algorithms and an analysis of the complexity by the number of single-word operations per processor are given.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89412082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The quality of specified and modeled requirements is critical for IT project success. A significant number of specialized techniques are used for documenting the requirements. The selection of the appropriate technique considerably influences a project plan and the success of a change as a whole. This paper aims to examine practitioners’ industrial standards and experience in the requirements specification activities and identify factors influencing the choice of specific techniques. To get the data from business analysis practitioners, we carried out a survey involving 328 specialists from Ukrainian IT companies and a series of interviews with experts. A list of specification and modelling techniques is selected based on international standards and bodies of knowledge. Project context and participants’ background influence on the probability of particular technique selection are analyzed. A set of dependencies are identified using the Chi-Square test for association and Cramer’s V. Results can be used as guidelines for building a framework for business analysis techniques selection in IT projects.
{"title":"Practical Study on Software Requirements Specification and Modelling Techniques","authors":"Denys Gobov","doi":"10.47839/ijc.22.1.2882","DOIUrl":"https://doi.org/10.47839/ijc.22.1.2882","url":null,"abstract":"The quality of specified and modeled requirements is critical for IT project success. A significant number of specialized techniques are used for documenting the requirements. The selection of the appropriate technique considerably influences a project plan and the success of a change as a whole. This paper aims to examine practitioners’ industrial standards and experience in the requirements specification activities and identify factors influencing the choice of specific techniques. To get the data from business analysis practitioners, we carried out a survey involving 328 specialists from Ukrainian IT companies and a series of interviews with experts. A list of specification and modelling techniques is selected based on international standards and bodies of knowledge. Project context and participants’ background influence on the probability of particular technique selection are analyzed. A set of dependencies are identified using the Chi-Square test for association and Cramer’s V. Results can be used as guidelines for building a framework for business analysis techniques selection in IT projects.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74059328","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}
An approach to dividing the printed circuit board into parts to increase visibility of defects in a PCB image is considered. The approach is based on a piecewise linear approximation of a cumulative histogram. The last one is calculated for numbers of informative pixels placed in rows and columns of an image matrix. Informative pixels are those indicating contacts and C traces. The histogram demonstrates a distribution of informative pixels along the OX and OY axes. The beginning and ending points of linear lines are taken as coordinates of the divided parts of the PCB board. The flood-fill algorithm is used to color and separate the PCB chains components. The start pixels are taken from a set of informative pixels. To measure defect values, a mean intensity and gradient functions for the template and manufactured images are used. Distributed cumulative histograms are applied to PCB components to detect places and intensity of defects.
{"title":"Chains Defects Detection in a Printed Circuit Board Image by the Plane Partition and Flood-filling of Traces","authors":"R. Melnyk, Tetyana Korotyeyeva, Yevheniya Levus","doi":"10.47839/ijc.22.1.2877","DOIUrl":"https://doi.org/10.47839/ijc.22.1.2877","url":null,"abstract":"An approach to dividing the printed circuit board into parts to increase visibility of defects in a PCB image is considered. The approach is based on a piecewise linear approximation of a cumulative histogram. The last one is calculated for numbers of informative pixels placed in rows and columns of an image matrix. Informative pixels are those indicating contacts and C traces. The histogram demonstrates a distribution of informative pixels along the OX and OY axes. The beginning and ending points of linear lines are taken as coordinates of the divided parts of the PCB board. The flood-fill algorithm is used to color and separate the PCB chains components. The start pixels are taken from a set of informative pixels. To measure defect values, a mean intensity and gradient functions for the template and manufactured images are used. Distributed cumulative histograms are applied to PCB components to detect places and intensity of defects.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79293405","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}
Md Asifuzzaman Jishan, Md. Shahabub Alam, Imran Rashid Mazumder, K. Mahmud, Abul Kalam al Azad
Object detection systems based on deep learning have been immensely successful incomplex object detection tasks images and have shown potential in a wide range of real-life applicationsincluding the COVID-19 pandemic. One of the key challenges in containing and mitigating the infectionamong the population is to ensure and enforce the proper use of face masks. The objective of this paperis to detect the proper use of facial masks among the urban population in a megacity. In this study, wetrained and validated a new dataset to detect images such as ‘with mask’, ‘without mask’, and ‘masknot in position’ using YOLOv5. The dataset is comprised of 6550 images with the three classes. Thedataset attained a commendable performance accuracy of 95% on mAP. This study can be implementedfor automated scanning for monitoring the proper use of face masks in different settings of public spaces.
基于深度学习的目标检测系统在复杂的目标检测任务图像中取得了巨大成功，并在包括COVID-19大流行在内的广泛现实应用中显示出潜力。控制和减轻人群感染的主要挑战之一是确保和强制正确使用口罩。本文的目的是检测超大城市人口中口罩的正确使用情况。在这项研究中，我们训练并验证了一个新的数据集，以检测图像，如“带口罩”，“不带口罩”和“masknot In position”使用YOLOv5。该数据集由6550张具有这三个类的图像组成。该数据集在mAP上达到了值得称赞的95%的性能准确性。本研究可用于自动扫描，以监测在公共场所不同设置下口罩的正确使用情况。
{"title":"An Automated Face-mask Detection System using YOLOv5 for Preventing Spread of COVID-19","authors":"Md Asifuzzaman Jishan, Md. Shahabub Alam, Imran Rashid Mazumder, K. Mahmud, Abul Kalam al Azad","doi":"10.47839/ijc.22.1.2880","DOIUrl":"https://doi.org/10.47839/ijc.22.1.2880","url":null,"abstract":"Object detection systems based on deep learning have been immensely successful incomplex object detection tasks images and have shown potential in a wide range of real-life applicationsincluding the COVID-19 pandemic. One of the key challenges in containing and mitigating the infectionamong the population is to ensure and enforce the proper use of face masks. The objective of this paperis to detect the proper use of facial masks among the urban population in a megacity. In this study, wetrained and validated a new dataset to detect images such as ‘with mask’, ‘without mask’, and ‘masknot in position’ using YOLOv5. The dataset is comprised of 6550 images with the three classes. Thedataset attained a commendable performance accuracy of 95% on mAP. This study can be implementedfor automated scanning for monitoring the proper use of face masks in different settings of public spaces.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84935237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper describes the search for a solution to the image near-duplicate detection problem. We assume that there are only two images to compare and classify whether they are near-duplicates. There are some traditional methods to match pair of images, and the evaluation of the most famous of them in terms of the problem is performed in this research. The effective thresholds to separate near-duplicate classes are found during experimental modeling using the INRIA Holidays dataset. The sequence of methods is proposed to make the joint decision better in terms of accuracy. It is shown also that the accuracy of binary classification of the proposed approach for the combination of the histogram comparison and ORB descriptors matching is about 85% for both near-duplicate and not near-duplicate pairs of images. This is compared to the existing methods, and it is shown, that the accuracy of more powerful methods, based on deep learning, is better, but the speed of the proposed method is higher.
{"title":"Image Pair Comparison for Near-duplicates Detection","authors":"O. Gorokhovatskyi, O. Peredrii","doi":"10.47839/ijc.22.1.2879","DOIUrl":"https://doi.org/10.47839/ijc.22.1.2879","url":null,"abstract":"The paper describes the search for a solution to the image near-duplicate detection problem. We assume that there are only two images to compare and classify whether they are near-duplicates. There are some traditional methods to match pair of images, and the evaluation of the most famous of them in terms of the problem is performed in this research. The effective thresholds to separate near-duplicate classes are found during experimental modeling using the INRIA Holidays dataset. The sequence of methods is proposed to make the joint decision better in terms of accuracy. It is shown also that the accuracy of binary classification of the proposed approach for the combination of the histogram comparison and ORB descriptors matching is about 85% for both near-duplicate and not near-duplicate pairs of images. This is compared to the existing methods, and it is shown, that the accuracy of more powerful methods, based on deep learning, is better, but the speed of the proposed method is higher.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79887060","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}
Sutriawan Sutriawan, P. Andono, Muljono Muljono, R. A. Pramunendar
The majority of the current research on sentiment analysis, which covers topics like political reviews, movie reviews, and product reviews, has developed quickly. The classification and clustering stage of sentiment analysis research involves a number of subjects. Some of them cover text classification comparison research and algorithm performance optimization. An intricate issue in sentiment analysis research is dealing with unstructured or semi-structured data. The sentiment analysis procedure and improving the efficacy of the classifier’s algorithm are both hampered by unstructured data. In order to manage unstructured data successfully and provide accurate and relevant information, unique strategies are required. The proposed classification model performance evaluation using Support Vector Machine, Naive Bayes, K-Nearest Neighbor, and Decision Tree is specifically covered in this paper. According to the study’s findings, SVM has an accuracy rate of 96% and Naive Bayes is 86%. While the decision tree’s gain accuracy is 78 percent and the kNN classification model’s gain accuracy is 78 percent, respectively. The test results demonstrate that SVM is superior to other classification models in terms of accuracy performance.
{"title":"Performance Evaluation of Classification Algorithm for Movie Review Sentiment Analysis","authors":"Sutriawan Sutriawan, P. Andono, Muljono Muljono, R. A. Pramunendar","doi":"10.47839/ijc.22.1.2873","DOIUrl":"https://doi.org/10.47839/ijc.22.1.2873","url":null,"abstract":"The majority of the current research on sentiment analysis, which covers topics like political reviews, movie reviews, and product reviews, has developed quickly. The classification and clustering stage of sentiment analysis research involves a number of subjects. Some of them cover text classification comparison research and algorithm performance optimization. An intricate issue in sentiment analysis research is dealing with unstructured or semi-structured data. The sentiment analysis procedure and improving the efficacy of the classifier’s algorithm are both hampered by unstructured data. In order to manage unstructured data successfully and provide accurate and relevant information, unique strategies are required. The proposed classification model performance evaluation using Support Vector Machine, Naive Bayes, K-Nearest Neighbor, and Decision Tree is specifically covered in this paper. According to the study’s findings, SVM has an accuracy rate of 96% and Naive Bayes is 86%. While the decision tree’s gain accuracy is 78 percent and the kNN classification model’s gain accuracy is 78 percent, respectively. The test results demonstrate that SVM is superior to other classification models in terms of accuracy performance.","PeriodicalId":37669,"journal":{"name":"International Journal of Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90147686","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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