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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 149 Documents
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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.
GrainBot: An Android-Controlled Rice Grain Collector Robot Masiado , Sunshine L.; Constantino , Anna D.; Cajurao , Jaelord F.; Valenciano , Jayboy V.; Lagayao , Joe Vincent; Dasmariñas , John Sharwin S.; Laud , Renly Jade S.
International Journal of Advanced Science Computing and Engineering Vol. 7 No. 2 (2025)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.7.2.258

Abstract

Rice, a fundamental dietary staple for over three billion people around the globe, remains subject to significant postharvest losses, even as advancements in production techniques continue to evolve. Traditional sun drying, although cost-effective and environmentally friendly, presents a range of challenges. It requires considerable labor, exposes farmers to potential health hazards, and often results in uneven drying, which adversely affects grain quality. In response to these pressing issues, this research unveils "GrainBot: An Android Controlled Rice Grain Collector Robot," an innovative solution designed to revolutionize rice collection. This agile, two-wheeled robot employs a sophisticated suction mechanism to efficiently collect sun-dried rice, while being wirelessly controlled via a custom-designed Android application. The functionality, usability, efficiency, compatibility, maintainability, reliability, and portability of this system were rigorously assessed against ISO 25010, with input from a diverse group of users, including farmers, agricultural specialists, and IT professionals. The findings from this comprehensive evaluation revealed a grand mean score of 4.61, indicating an "excellent" rating. This indicates not only a high level of user satisfaction but also underscores the system’s effectiveness in automating and refining the rice grain collection process. Ultimately, the proposed GrainBot represents a promising technological advancement, poised to significantly reduce manual labor, minimize health risks for farmers, and enhance the overall efficiency of postharvest rice handling.
Beykoz Honor a Robust Online Exam Platform System Elkhodary, Abdullah I.; Erkan , Feyza; Aburas , Abdurazzag A.
International Journal of Advanced Science Computing and Engineering Vol. 7 No. 2 (2025)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.7.2.259

Abstract

In today’s digital landscape, online assessments have emerged as a pivotal element of educational systems worldwide. However, the rise of online examinations has also been accompanied by a troubling increase in cheating incidents. Research highlights that the most prevalent forms of online exam fraud include unauthorized access, screen sharing among students, and impersonation of test-takers. In response to these challenges, we introduce "Beykoz Honor," an innovative online exam platform meticulously engineered to incorporate a suite of advanced anti-cheating features. This platform employs multi-factor authentication (MFA) to ensure that only legitimate users can access assessments. Additionally, a browser lockdown mechanism restricts navigation away from the exam interface, while IP and device tracking enable monitoring of candidates to prevent fraudulent activity. Furthermore, question randomization adds another layer of integrity by altering the order and selection of exam questions for each student. Research has consistently shown that these comprehensive measures significantly mitigate the risks associated with academic dishonesty. This paper examines the architecture of the Beykoz Honor system, outlines its phased implementation strategy, and conducts a thorough market analysis with a particular focus on Turkish universities. Looking toward the future, we discuss ambitious plans to integrate artificial intelligence to detect irregularities during assessments. Real-time monitoring solutions are also on the horizon, adding yet another dimension to the platform's capability to uphold academic integrity. These innovations represent ongoing efforts to enhance the efficacy and reliability of online examinations, ensuring a fair and equitable assessment environment for all students.
Accuracy Comparison Between Easy Qibla and Total Station Kasim , M. I. S.; Shariff , N. N. M.; Hamidi , Z. S.
International Journal of Advanced Science Computing and Engineering Vol. 7 No. 2 (2025)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.7.2.260

Abstract

Easy Qibla is a mobile app developed by ESERI, UniSZA which provides, other than direction of qibla, azimuth and altitude of the Sun and the Moon on actual time. This data is regularly used by falak or astronomy researchers, therefore the accuracy is critical. This study aims to compare azimuthal data accuracy provided by Easy Qibla and total station by measuring actual azimuth of the Sun and the Moon. A total station is erected on station 1 with station 2 set as the reference object (RO). The azimuth of station 2 from station 1 is pre-determined by GPS device. Sixty-nine readings were taken by observing both the Sun and the Moon. In each observation, screenshots of Easy Qibla were taken, thus capturing the actual time azimuth. The corresponding azimuth of the Sun or the Moon shown on the total station display was recorded. Both readings are tabulated and subtracted to obtain the errors. Results after sixty-nine readings show that the lowest error is 0.0002°, while highest error is 0.26°, with an average of 0.06°. Data collected on another day may give different results due to the differences in the declination of the Sun. The errors are inclusive of, but limited to, human error and total station error. In conclusion, the result shows that the errors are insignificant in considerably low accuracy field of studies like determining qibla or new moon observation.
Fuzzy Logic and IoT-Based Monitoring for Solar-Powered Precision Mist Irrigation Hidayat, Imam; Dani , Akhmad Wahyu; Amin , Mawardi; Hermala , Irvan; Abdurohman
International Journal of Advanced Science Computing and Engineering Vol. 7 No. 2 (2025)
Publisher : SOTVI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/ijasce.7.2.261

Abstract

The increasing unpredictability of environmental conditions, such as temperature fluctuations, humidity variations, seasonal shifts, and changing water availability, presents a significant challenge for sustainable food production. The increasing unpredictability of environmental conditions, including temperature fluctuations, humidity variations, seasonal shifts, and changing water availability, poses a significant challenge for sustainable food production. Although they are suitable for simple decision-making, conventional Type-1 Fuzzy Logic-based irrigation systems struggle to manage sensor noise, environmental uncertainty, and changing field conditions, resulting in sometimes ineffective water use and uneven irrigation management. This work presents a solar-powered mist irrigation system that integrates Interval Type-2 Fuzzy Logic (IT2FLS) and Internet of Things (IoT) technologies to improve precision irrigation management and address these issues. The proposed system employs IoT-based real-time environmental monitoring via Blynk and ThingSpeak to enable dynamic irrigation adjustments in response to temperature and soil moisture fluctuations. Type-2 Fuzzy Logic offers more reliable relay activation choices and greater robustness to sensor noise by incorporating Upper and Lower Membership Functions (UMF & LMF) and a Footprint of Uncertainty (FoU) than conventional Type-1 FIS. Experimental data demonstrate that the Type-2 Fuzzy model significantly reduces erroneous irrigation activations, maximizes water distribution, and increases system flexibility in response to environmental changes. Using solar power further improves energy efficiency, thereby reducing dependence on grid electricity and supporting environmentally friendly irrigation practices. This work demonstrates that, for contemporary agriculture, Type-2 Fuzzy Logic-based smart irrigation offers a scalable, flexible, and cost-effective alternative. This study shows how integrating renewable energy, advanced Type-2 fuzzy control, and IoT can create resource-efficient, adaptive irrigation systems supporting sustainable farming amid environmental challenges.
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.

Page 15 of 15 | Total Record : 149

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