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Alde Alanda
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Kampus Limau Manis
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International Journal of Advanced Science Computing and Engineering
Published by Society of Visual Informatics
ISSN : 27147533     EISSN : 27147533     DOI : https://doi.org/10.30630/ijasce
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
The journal scopes include (but not limited to) the followings: Computer Science : Artificial Intelligence, Data Mining, Database, Data Warehouse, Big Data, Machine Learning, Operating System, Algorithm Computer Engineering : Computer Architecture, Computer Network, Computer Security, Embedded system, Coud Computing, Internet of Thing, Robotics, Computer Hardware Information Technology : Information System, Internet & Mobile Computing, Geographical Information System Visualization : Virtual Reality, Augmented Reality, Multimedia, Computer Vision, Computer Graphics, Pattern & Speech Recognition, image processing Social Informatics: ICT interaction with society, ICT application in social science, ICT as a social research tool, ICT education
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 7 Documents
 1 
Search results for , issue "Vol. 7 No. 3 (2025)" : 7 Documents clear
Improving the Performance of Rank Regression Using Fast Minimum Covariance Determinant in Estimating Weibull Distribution Parameters Abduljabar Ibrahim Hasawy, Mohammed; Hussein Ali , Taha; Samad Sedeeq , Bekhal
International Journal of Advanced Science Computing and Engineering Vol. 7 No. 3 (2025)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.7.3.229

Abstract

Outliers hurt the accuracy of life distribution parameters, including the Weibull distribution. Therefore, researchers have suggested employing the fast minimum covariance determinant method in rank regression estimators (which are robust but not efficient) to obtain robust estimators for the shape and scale parameters of the Weibull distribution. The proposed method is based on the robust means vector and the robust covariance matrix obtained from the fast minimum covariance determinant method, and it employs the rank regression estimation method, which depends on the ordinary least squares estimators of the simple linear regression model. The estimated parameters of the Weibull distribution obtained using the proposed technique have been compared with those derived from conventional maximum likelihood estimation and rank regression, using mean square error as the comparison metric, via both simulation and real data. The study's findings demonstrated the efficacy of the proposed strategy in addressing outliers and yielding highly effective estimators for the shape and scale parameters of the Weibull distribution.
Evaluating the Effectiveness of Drone Technology in Fish Feeding Operations Diamante, Ram Eujohn J.
International Journal of Advanced Science Computing and Engineering Vol. 7 No. 3 (2025)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.7.3.250

Abstract

Interest has been shown in drone technology's potential to improve the efficiency and sustainability of aquaculture practices, with increased adoption in fish feeding operations. This study examines the effectiveness of drone-based feeding systems in fish farms, particularly in optimizing feed distribution and reducing waste, thereby improving water quality. This implies that drone technology can significantly increase the accuracy and speed of feed delivery, thereby reducing feed waste by 25% and increasing farmed fish growth rates by 15% above their mean rates. This study will also compare the economic and environmental benefits of drone-based feeding. Some of these benefits include a significant reduction in labor costs and lessened water pollution. Our results show that drone application will reduce labor costs by 30% and water pollution by 20%. Drones may emerge as a viable option for future aquaculture fish farming, improving sustainability and efficiency. The present research adds to the emerging body of work on drone technology applications in aquaculture and indicates a bright future in changing the industry's feeding practice. Overall, the findings from this study raise awareness not only of the potential of drone technology to improve the efficient operation of systems but also underscore drones as promoters of sustainability in aquaculture.
Zonation of Soil Bearing Capacity from Cone Penetration Test Data: Case Study in Padang Liliwarti; Silvianengsih; Mahardika, Tiara; Hartati; Stiyanto, Eri
International Journal of Advanced Science Computing and Engineering Vol. 7 No. 3 (2025)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.7.3.255

Abstract

This study aims to map the zonation of soil bearing capacity in Padang City, covering five districts —Koto Tangah, Padang Barat, Nanggalo, Padang Timur, and Padang Selatan —comprising a total of 12 test points. The data were obtained from Cone Penetration Test (CPT) results, which were subsequently analysed to determine the ultimate bearing capacity of the soil, the safety factor of foundations against load eccentricity, and settlement at several test points. The analytical approach focused on assessing vertical bearing capacities, comparing estimated working loads with calculated ultimate bearing capacities, and determining settlement under representative design load conditions. From 12 test points distributed across the five districts, the results indicate that all locations exhibit safety factors significantly above the minimum requirement (FS > 3), suggesting that the ground has excellent capacity to sustain structural loads. In addition, the observed settlements are small, ranging from 0.8 mm to 6.4 mm, and remain well below the commonly accepted tolerance for foundation settlement (25–50 mm). These results support the notion that the subsurface layers in these areas are stable and do not pose a significant risk of foundation settlement. Therefore, the soil conditions at all test points can be categorised as safe, stable, and suitable to support the assumed design load of 100 kN, regardless of whether pile foundations or shallow foundations are used. The resulting soil bearing capacity zonation map is expected to serve as a practical reference for foundation planning, assisting engineers and planners in selecting appropriate foundation systems, and supporting sustainable infrastructure development in Padang City in a safer, more effective, and efficient manner.
The Architecture of Digital Deception: Mapping Fake News Typologies, Bot Behaviors, and Platform Vulnerabilities Afansyah, Muhammad Fikri; Ahmad Nawi , Haslinda Sutan
International Journal of Advanced Science Computing and Engineering Vol. 7 No. 3 (2025)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.7.3.257

Abstract

The emergence of social media has radically changed the nature of information production, dissemination, and consumption. Alongside its advantages, the diffusion of misinformation has become a major threat to debate, democratic processes, and social cohesion. The following paper presents an extensive review of typologies of fake news, drawing on existing scholarship that categorizes fake news as satire, propaganda, disinformation, misinformation, manipulation, rumor, crowdturfing, hate speech, spam, trolls, and cyberbullying. The two categories are discussed with respect to their purpose, precision, and influence on users. The role of bots and computational propaganda, which automate and amplify the spread of misleading content on the internet, particularly during sensitive periods when politics is salient, is also examined. The paper identifies several shortcomings of existing platform moderation systems, which largely fail to block the real-time dissemination of dangerous content. In a reaction, the paper highlights the important work of information professionals, i.e., journalists, teachers, educators, librarians, and specialists in digital media, being able to reduce the dissemination of false information. They are tasked with fact-checking, source validation, media literacy, and citizen empowerment in the assessment of online information. In addition, the paper promotes the development of more resilient AI-based detection mechanisms that can respond quickly to the proliferation of harmful content. Finally, the research is expected to foster a more aware and less vulnerable world, prepared to meet the challenges of the digital information era through technological devices and human knowledge.
Image Caption Generator Using Bahdanau Attention Mechanism Gowda , Nikhita B; Vaishnavi; Skanda B N , Avin; Rohan M; Raikar , Pratheek V
International Journal of Advanced Science Computing and Engineering Vol. 7 No. 3 (2025)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.7.3.264

Abstract

This project proposes a sophisticated image captioning system developed using an encoder-decoder framework bolstered with an attention mechanism. The system generates contextually appropriate text descriptions by dynamically weighting relevant image regions with CNNs for feature extraction and RNNs with attention layers. The model shows significant improvement on the Flickr8k dataset, as measured by BLEU. The study examines the use of such systems across domains, including assistive devices and automated indexing, and proposes employing transformer-based attention methods in future upgrades. The development of an image captioning system with an attention mechanism is a key advancement in computer vision and natural language processing. This mechanism helps the model focus on relevant image parts when generating words, improving contextual relevance and semantic accuracy. It aligns visual features with language more effectively, producing captions similar to human descriptions. The model employs teacher forcing during training to accelerate learning and improve fluency. Standard metrics like BLEU evaluate performance and compare models. Inspired by works like “Show, Attend and Tell,” attention bridges image features and language. Attention-based captioning can aid visually impaired users, enable content indexing, and improve human–computer interaction. Future research will likely scale models to larger datasets and enhance generalization across diverse scenes.
Named Entity Recognition on Islamic Texts: A Systematic Review Tarmizi , Shasha Arzila; Saad , Saidah
International Journal of Advanced Science Computing and Engineering Vol. 7 No. 3 (2025)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.7.3.265

Abstract

This systematic literature review aims to comprehensively analyze Named Entity Recognition (NER) applications in Islamic texts, particularly the Quran and Hadith, across Arabic, Indonesian, English, and Malay languages. Materials comprised studies from major academic databases (2017-2024) implementing various NER approaches on Islamic textual datasets. The majority of studies reviewed focused on Hadith texts, with fewer examining Quranic texts and general Islamic literature. The methodology employed a PRISMA-based systematic review examining architectural components, diverse methodologies, comparative model performance, and extraction challenges in Islamic discourse. Traditional rule-based and statistical machine learning methods remain relevant, particularly in hybrid frameworks. However, the analysis reveals that transformer-based deep learning models consistently achieve superior performance, with the highest F1 Scores. Hadith datasets showed better NER performance than Quranic texts due to Hadith's structured and repetitive nature versus the Quran's greater linguistic diversity and complex syntactic structures. Most studies employed lexical and linguistic features to address distinctive characteristics of religious texts, with significant progress in handling specialized Islamic concepts and multilingual considerations. Despite these advancements, significant challenges persist, including the linguistic complexity of Classical Arabic, the scarcity of high-quality annotated corpora, and the difficulties of domain-specific entity identification. This review provides comprehensive guidance for researchers developing Islamic NER systems by identifying optimal methodological approaches and highlighting performance benchmarks across different text types, thereby enabling the development of more effective, culturally aware NLP systems for Islamic content.
Acceptance and Implications of Holography Technology for Presenting Minangkabau Traditional Clothing in Museums: A Technology Acceptance Model (TAM) Afyenni, Rita; Erianda, Aldo; Firosha, Ardian; Hidayat, Rahmat; Gusman, Taufik
International Journal of Advanced Science Computing and Engineering Vol. 7 No. 3 (2025)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.7.3.267

Abstract

This study investigates the use of holography technology to present Minangkabau traditional clothing in museums, applying the Technology Acceptance Model (TAM) to assess public response. Survey results show high acceptance, with strong ratings for cultural authenticity and educational value. Perceived ease of use and usefulness significantly influence positive attitudes and behavioral intention, with higher acceptance among females, younger age groups, and those with higher education. Despite these positive outcomes, technical challenges remain, including high implementation costs, limitations in visual clarity, and concerns about digital authenticity. The findings imply that holography can effectively bridge traditional heritage with modern, interactive experiences, making museums more engaging and accessible. The study recommends further research to address technical improvements, cost efficiency, and broader implementation, supporting holography as a strategic tool for cultural preservation and educational innovation.

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