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Rizki Wahyudi
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Journal of Computer Science and Engineering (JCSE)
Published by Institute of Computer Science and Engineering
ISSN : -     EISSN : 27210251     DOI : https://doi.org/10.36596/jcse
Core Subject : Science,
Computer Science & IT
Computer Architecture, Processor design, operating systems, high-performance computing, parallel processing, computer networks, embedded systems, theory of computation, design and analysis of algorithms, data structures and database systems, theory of computation, design and analysis of algorithms, data structures and database systems, artificial intelligence, machine learning, data science, Information System
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol 3, No 2: August (2022)" : 5 Documents clear
Perkembangan Evaluasi Tata Kelola Teknologi Informasi: Literature Review Khansa, Shafa Salsabila; Ramadhan, Della Novia; Alfarisy, Ahmad Fadil; Fitroh, Fitroh
Journal of Computer Science and Engineering (JCSE) Vol 3, No 2: August (2022)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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Abstract

Information technology is an important organizational asset to be managed and maximized so that its use can be aligned with business needs, thus helping to improve the achievement of the organization's vision and mission. Therefore, the implementation of information technology governance in every organization needs to be monitored for its implementation, this makes the organization more mature and immediately makes improvements to its management of its IT assets. Various studies have been conducted to evaluate IT governance in organizations using various frameworks. This study aims to conduct a review of previous studies related to the development of IT governance evaluation in reviewing research activities carried out in a certain period, analyzing the framework used and why the framework is used. The results show that research to evaluate IT governance peaked in 2014 which was dominated by the institutional sector using the COBIT 5 framework and the various reasons for using COBIT 5 are discussed further in this study.
Big Data Indexing: Taxonomy, Performance Evaluation, Challenges and Research Opportunities Othman, Abubakar Usman; Moses, Timothy; Aisha, Umar Yahaya; Gital, Abdulsalam Ya’u; Souley, Boukari; Adeleke, Badmos Tajudeen
Journal of Computer Science and Engineering (JCSE) Vol 3, No 2: August (2022)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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Abstract

In order to efficiently retrieve information from highly huge and complicated datasets with dispersed storage in cloud computing, indexing methods are continually used on big data. Big data has grown quickly due to the accessibility of internet connection, mobile devices like smartphones and tablets, body-sensor devices, and cloud applications. Big data indexing has a variety of problems as a result of the expansion of big data, which is seen in the healthcare industry, manufacturing, sciences, commerce, social networks, and agriculture. Due to their high storage and processing requirements, current indexing approaches fall short of meeting the needs of large data in cloud computing. To fulfil the indexing requirements for large data, an effective index strategy is necessary. This paper presents the state-of-the-art indexing techniques for big data currently being proposed, identifies the problems these techniques and big data are currently facing, and outlines some future directions for research on big data indexing in cloud computing. It also compares the performance taxonomy of these techniques based on mean average precision and precision-recall rate.
Novel approach of Predicting Human Sentiment using Deep Learning Shadadi, Ebtesam; Kouser, Shama; Alamer, Latifah; Whig, Pawan
Journal of Computer Science and Engineering (JCSE) Vol 3, No 2: August (2022)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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Abstract

Due to its interactive and real-time character, gathering public opinion through the analysis of massive social data has garnered considerable attention. Recent research have used sentiment analysis and social media to do this in order to follow major events by monitoring people's behavior. In this article, we provide a flexible approach to sentiment analysis that instantly pulls user opinions from social media postings and evaluates them. As time passed, an increasing number of people shared their opinions on social media. More individuals can now communicate with one another as a result. Along with these advantages, it also has certain drawbacks that cause resentment in some people. Hate speech is another possibility. Hate speech impacts the community when it contains insulting or threatening language. Before it spreads, this kind of speech has to be identified and deleted from social media platforms. The process of determining whether a text's feelings reflect hatred or not involves sentiment analysis. Python language was used to analyze the Twitter dataset. There were 5000 Tweets in total in this dataset, and we used deep learning to improve the machine learning model's accuracy. The experimental outcome in both cases of the Twitter dataset uses the Random Forest approach, which has a 99 percent accuracy rate.
Measuring Computational Psychometrics Analysis Motivational Level in Learner’s using Different Parameters through Deep Learning Algorithm Bhatia, Ashima Bhatnagar; Mittal, Kavita
Journal of Computer Science and Engineering (JCSE) Vol 3, No 2: August (2022)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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Abstract

Learning is an ongoing process irrespective of age, gender and geographical location of acquiring new understanding, knowledge, behaviours, skills, values, attitudes, and preferences. Formative assessment methods have emerged and evolved to integrate learning, evaluation and education models. Not only is it critical to understand a learner's skills and how to improve and enhance them, but we also need to consider what the learner is doing; we need to consider navigational patterns. The extended learning and assessment system, a paradigm for doing research, captures this entire view of learning and evaluation systems. The function of computational psychometrics is to facilitating the translation from raw data to meaningful concepts. In this research study, several factors are considered for psychometric analysis of different kinds of learners, and based on a motivational level, many interesting conclusions have been drawn and presented in the result section at the end of the paper. Deep learning model Ludwig Classifier used to calculate, motivational Level is obtained for 100 number of epochs and it is found that the loss is decreasing and in other words, the accuracy of the machine goes on increasing. Each of the categories discussed here has new capabilities, or at the very least expansions of current ones.
Enhance Facial Biometric Template Security using Advance Encryption Standard with Least Significant Bit D, Gbolagade Morufat; Hambali, Moshood Abiola; Abdulganiyu, Oluwadamilare H.; Lawrence, E
Journal of Computer Science and Engineering (JCSE) Vol 3, No 2: August (2022)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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Abstract

Security of data has been a major issue for many years which has lead to several challenges; loss of data and also allure hackers to where data are been stored. Biometric system to some extend has helped in combating these security issues, the major issues with the biometric system is how to properly secure the template been generated from hackers and unauthorized users. In this paper we combine cryptography and steganography to enhance security of biometric templates using the advance encryption standard (AES) and the least significant bit (LSB) technique to encrypt these templates and secure it from hackers, Cryptography and Steganography are the two widely employed techniques for securing and hiding data. The center of attention of this paper is the potency of combining cryptography and stenography techniques to improve the security of biometric templates.

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