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Rizki Wahyudi
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INDONESIA
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 4, No 2: August (2023)" : 5 Documents clear
An Integrated Approach for Diabetes Detection Using Fisher Score Feature Selection and Capsule Network Tahsin, Mohammad Sadman; Karim, Musaddiq Al; Ahmed, Minhaz Uddin; Tafannum, Faiza; Firoz, Neda
Journal of Computer Science and Engineering (JCSE) Vol 4, No 2: August (2023)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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Abstract

This paper investigates how the Fisher score feature selection approach can be used with capsule networks for diabetes detection. It also evaluates how well this algorithm works based on a number of evaluation parameters. The selected features using Fisher score method was then employed to train a capsule network model. Accuracy (94%), precision (94%0, recall (94%), F1 score (94%), and other performance evaluation metrics were thoroughly analyzed to determine the algorithm's efficacy. The results demonstrated that the combination of Fisher score feature selection and capsule networks yielded promising performance in diabetes detection. The selected features effectively captured the relevant information necessary for accurate classification The capsule network model was very accurate, which shows that it could be a good tool for diagnosing diabetes. Also, the accuracy and recall values showed that the algorithm could correctly place both positive and negative cases of diabetes, minimizing the risk of misdiagnosis. By merging the Fisher score feature selection approach with capsule networks, this research study contributes to advancing diabetes detection.
Enhancing Privacy in Graph Algorithms: Data-Oblivious Approaches to DFS and Dijkstra's Algorithm CH, Koteswararao; Singh, Kunwar; Kumar, Anoop
Journal of Computer Science and Engineering (JCSE) Vol 4, No 2: August (2023)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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Abstract

Data obliviousness is characterized by a consistent sequence of operations irrespective of input data and data-independent memory accesses, making it a suitable solution for users utilizing outsourced storage data services who aim to conceal their data access patterns. In ACM SIGSAC 2013, data-oblivious algorithms were introduced for breadth-first search, single-source single-destination (SSSD) algorithms, maximum flow, and minimum spanning tree. In this study, we present novel data-oblivious algorithms designed for depth-first search and single-source shortest path (Dijkstra’s algorithm). Our proposed data-oblivious algorithms demonstrate efficiency comparable to non-data-oblivious counterparts, particularly for graphs containing fewer than 1000 nodes. This research contributes to advancing data privacy in outsourced storage services by providing effective data-oblivious solutions for common graph algorithms.
TikTok Shop: Unveiling the Evolution from Social Media to Social Commerce and its Computational Impact on Digital Marketing Nur, Zinda Rud Faiza; Rabbiana, Intan Nas Nas; Diba, Tiara; Fitroh, Fitroh
Journal of Computer Science and Engineering (JCSE) Vol 4, No 2: August (2023)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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Abstract

Social media application platforms such as TikTok have become social commerce platforms. TikTok provides the TikTok Shop feature, which is designed for business actors to make sales and users to make transactions on the TikTok application. This study used the method of studying literature from published journals available on open-source sites. It aims to present the potential of TikTok Shop as a digital marketing medium in the future. Therefore, the discussion of this literature review is only focused on the TikTok Shop feature as social commerce. TikTok Shop promoted efforts to provide improvements for MSMEs during the pandemic through an SEO marketing strategy and influencers providing interesting content according to the interests of the audience. TikTok also provides Live TikTok for business people, which is in the form of streaming video that can interact with users as potential buyers. Our research found that TikTok Shop can be one of the platforms with great potential for promoting products, supported by several TikTok Shop features for transactions.
Aircraft Recognition in Remote Sensing Images Based on Artificial Neural Networks Abrar, Muhammad Fauzan; Ayumi, Vina
Journal of Computer Science and Engineering (JCSE) Vol 4, No 2: August (2023)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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Abstract

Computer Vision (CV) is a field of Artificial Intelligence (AI) that enables computers and systems to obtain data from images, recordings and other visual information sources. Image Recognition, a subcategory of Computer Vision, addresses a bunch of strategies for perceiving and taking apart pictures to engage the automation of a specific task. It is fit for perceiving places, people, objects and various types of parts inside an image, and reaching deductions from them by analyzing them. With these kinds of utilities it is a no-brainer that Computer Vision has its use cases in the military world. Computer Vision can be immensely useful for Intelligence, Surveillance and Reconnaissance (ISR) work. This paper provides on how Computer Vision might be used in ISR work.  This paper utilises Artificial Neural Network (ANN) such as Convolutional Neural Network (CNN) and Residual Neural Network (ResNet) for demonstration purposes. In the end, the ResNet model managed to edge out the CNN model with a final validation accuracy of 90.9% compared to a validation accuracy of 86% on the CNN model. With this, Computer Vision can help enhance the efficiency of human operators in image and video data related work.
Managing Student Mobility in Cameroon’s University Ecosystem: A FORM/BCS Approach Ngoumou, Amougou; Roger, Atsa Etoundi; Ndjodo, Marcel Fouda
Journal of Computer Science and Engineering (JCSE) Vol 4, No 2: August (2023)
Publisher : ICSE (Institute of Computer Sciences and Engineering)

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Abstract

Nowadays, student mobility cannot be avoided in Cameroon university ecosystem. This phenomenon has many causes. Certain students live with their parents who are civil servants and they have to move with them when they are sending to a different region; another situation is link to universities newly created in cities where the cost of the live is better than in the home university city and students prefer move to these new universities. Since student circuit is not the same in each university, it is difficult to find his level in the new university and which courses he has to follow in order to complete his training. This problem is crucial in Cameroon university ecosystem and we tackle it in this paper. The Feature Oriented Reuse Method with Business Component Semantics (FORM/BCS) is a software domain engineering method that has been proposed to design an adaptable architecture for systems belonging in a same business domain. In this work, we apply the FORM/BCS method to manage student mobility in Cameroon university ecosystem. The result of this work is a management model that allows once a student gets an enrolment in a new university, to transfer credit from the student home university to the host one.

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