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Muhammad Wali
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International Journal Software Engineering and Computer Science (IJSECS)
Published by Lembaga Komunitas Informasi Teknologi Aceh
ISSN : 27764869     EISSN : 27763242     DOI : https://doi.org/10.35870/ijsecs
Core Subject : Science,
Computer Science & IT
IJSECS is committed to bridge the theory and practice of information technology and computer science. From innovative ideas to specific algorithms and full system implementations, IJSECS publishes original, peer-reviewed, and high quality articles in the areas of information technology and computer science. IJSECS is a well-indexed scholarly journal and is indispensable reading and references for people working at the cutting edge of information technology and computer science applications..
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 284 Documents
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Internet of Things (IoT) Integration for Real-Time Monitoring in Smart Cities Fajri, T. Irfan; Rahayu, Novi; Wasiran; Budiman, Yusuf Unggul; Hasti, Novrini
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3465

Abstract

The advancement of Internet of Things (IoT) technology has opened great opportunities for the implementation of real-time monitoring systems in supporting smart city management. This research aims to develop an IoT integration model that can monitor various urban aspects, such as traffic management, energy consumption, waste management, and air quality, in an efficient and integrated manner. The model is designed to collect, process, and analyze data from various IoT sensors scattered in urban areas, with a focus on delivering information in an integrated manner. urban areas, with a focus on delivering real-time information to the government and the public. The research methodology includes the development of development of an IoT-based system prototype that integrates hardware and hardware and software with the support of cloud computing architecture for data management. data management.
Enhancing Foreign Language Learning through Educational Technology Phua, Jerri; Aripradono, Heru Wijayanto
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3483

Abstract

Nowadays, the demand for foreign language learning has become a necessity due to globalization but traditional strategies are not free from problems. Educational technologies (EdTech), especially those powered by Artificial Intelligence (AI), augmented reality (AR) and/or virtual VR are following the trend and introducing new ways to enhance the efficiency of foreign language learning. Behavior and 2) This study examine the use of these technologies in foreign language learning through quality education. The study used descriptive qualitative methodology with a systematic review of related literature. The study results show that EdTech enables more interactive, personalized and integrated learning, which significantly enhances foreign language competency. However, there are known obstacles such as lack of infrastructure, inadequate teacher training and inaccessible areas. To overcome this, there is a need for E2E (EdTech to Ends) which aims to achieve maximum in foreign language education by using the power of EdTech.
Chili Type Detection System Using Principal Component Analysis Method Julianda, Rindy; Tundo; Sugeng
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3735

Abstract

Classification of types of chili vegetables is an important aspect in the agricultural industry to increase the efficiency of product management, packaging and distribution. This research aims to implement the Principal Component Analysis (PCA) method in the process of classifying vegetables and types of chilies. PCA is used to reduce the dimensionality of the data and extract the main features that are significant in distinguishing vegetable categories. The research dataset consists of digital images of chili vegetables which are extracted into color, texture and shape attributes. The research results show that PCA is able to significantly improve classification accuracy by minimizing computational complexity. Experiments were carried out with various numbers of principal components in PCA to determine the optimal configuration. In the best configuration, this method achieves classification accuracy of 90%, with PCA effectively reducing data dimensionality by up to 95% without losing important information. In conclusion, this approach has great potential to be implemented in vegetable classification automation systems to support efficiency in agricultural supply chains.
K-Means Clustering Analysis of Poverty Data in Cilacap District Setiawan, Kiki; Kastum; Pratama, Yuliya Putri
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3759

Abstract

Poverty stands as a complex structural obstacle within social development frameworks. The COVID-19 pandemic intensified poverty dynamics in Indonesia which saw poverty rates increase by 9.78% in March and reach 10.19% by September. Local Bureau of Statistics data shows that the poverty rate in Cilacap Regency dropped to 10.99% (around 191,000 people) in March 2024 from 10.68% (186,080 people) in March 2023. The study uses k-means clustering methodology for analysis and maps poverty-prone areas utilizing QGIS software. The analysis revealed 12 sub-districts and 14 neighborhood units (RW) alongside a single community unit (RT) that show unique poverty characteristics. The silhouette coefficient evaluation produced a 0.55 score which showed a moderate cluster structure and acceptable cluster placement. The research provides empirical evidence about poverty distribution which shows how data mining methods can enhance spatial socioeconomic studies. The study presents a detailed analysis of poverty stratification across Cilacap Regency through the application of sophisticated computational methods.
Development of a Prototype for a Product Recommendation System Using Blockchain Technology Setiawan, Adrian Tri; Hindarto, Djarot
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.3855

Abstract

Blockchain technology ensures data security and transparency through decentralization and immutability. Smart contracts facilitate automation and foster trust by reducing dependence on intermediaries. Nevertheless, most existing recommendation systems remain centralized, leaving them susceptible to manipulation and security breaches. Although recommendation algorithms are widely used, their application within blockchain-based systems remains limited. By leveraging the Ethereum blockchain and smart contracts, the proposed system enhances transparency, security, and decision-making reliability. The algorithm ranks products based on price, appearance, quality, size, and availability, with results permanently recorded on the blockchain. Experimental findings indicate that the integration of TOPSIS and PROMETHEE II algorithms improves the recommendation process by systematically evaluating multiple criteria. Each product is assessed according to its proximity to both positive and negative ideal solutions, with the final ranking score calculated as the ratio of the negative distance to the total distance (positive plus negative). For example, Pocari Sweat achieved the highest preference score of 0.9619, indicating it is the top recommendation, while Coca-Cola 390ml scored 0.4182, reflecting a lower ranking. These results demonstrate the algorithms’ capacity to distinguish products objectively, supporting accurate and transparent recommendations. The study advances blockchain-based decision support systems by providing secure and transparent recommendation mechanisms. Additionally, the integration of TOPSIS and PROMETHEE II within a blockchain framework demonstrates both feasibility and effectiveness in decentralized environments.
Development of a Web-Based E-Administration System for the Indralaya Ogan Ilir Police Department Utilizing the System Development Life Cycle (SDLC) Approach Udariansyah, Devi; Sapriyogi, Asta
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.3931

Abstract

Information technology advancement has transformed administrative processes across government institutions, particularly within law enforcement agencies. This research examines the development of a web-based E-Administration application at the Indralaya Ogan Ilir Police Resort, designed to improve efficiency, accuracy, and accessibility in administrative services. The application development follows the System Development Life Cycle (SDLC) methodology, providing a structured approach through planning, analysis, design, implementation, testing, and maintenance phases. The study seeks to optimize administrative workflows, minimize paperwork dependency, and strengthen data security protocols. Results demonstrate that system implementation delivers more effective and efficient administrative processes, enhancing service quality and operational performance within the police department. Future research should focus on integrating advanced security measures and expanding functionality to accommodate broader administrative requirements.
Image Segmentation of East OKU Script Using the Bounding Box Method for Cultural Heritage Digitization Fikri, M; Yadi, Ilman Zuhri; Kunang, Yesi Novaria; Abdillah, Leon Andretti
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4045

Abstract

East Ogan Komering Ulu (OKU) is distinguished by its cultural heritage, which encompasses historical artifacts such as traditional houses, crafts, and ceremonial dances. Among the most significant cultural assets are relics inscribed with ancient scripts, including Pallawa and Ulu, which offer valuable insight into the region’s historical literacy. The present study addresses the segmentation of OKU Timur script images through the Bounding Box method. This approach was selected based on its practicality and efficiency, particularly in the context of datasets where script characters exhibit straightforward forms and the overall data volume remains manageable. The segmentation process utilizes Python within the Google Colaboratory platform, ensuring accessible and reproducible workflows. Accurate segmentation is essential to support ongoing digitization and preservation of cultural scripts. The methodology involves gathering data from local artifacts, converting images to binary format, and isolating characters using Bounding Boxes. The results demonstrate that the method effectively separates individual script characters, laying the groundwork for dataset development and subsequent image classification tasks.
Agile Code Board: An Integrated Task, Planning, and Brainstorming Tool for Agile Teams Vignesh, T.; Johnsonselva, J.V.
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4093

Abstract

Agile methodologies are widely adopted in software development for their effectiveness in team coordination, iterative progress, and comprehensive project oversight. This study analyzes the Agile Code Board, a real-time project management platform designed to assist Agile teams in organizing and executing tasks throughout each sprint. The platform offers multiple workspaces with role-based access, enabling task tracking, immediate team collaboration, and sprint-level planning. Key features include a drag-and-drop Kanban board, a collaborative whiteboard, calendar integration for deadlines and milestones, a filterable task table, and a cross-team program board inspired by SAFe. Agile Code Board is built using Next.js and Hono, with Appwrite for authentication and Liveblocks for real-time collaboration. The system introduces mechanisms that facilitate efficient teamwork and project coordination. This research outlines the system architecture, development practices, and the ways in which the platform enhances Agile workflow management in collaborative environments.
Business Intelligence and Decision Support to Enhance Decision-Making Quality in Higher Education Syamsiah, Syamsiah; Darmawan, Agus; Halimatusa'diah, Halimatusa'diah; Hidayatullah, Reko Syarif; Isnain, Nasrulloh
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4273

Abstract

The availability of accurate and reliable data is essential for organizational sustainability. Business intelligence (BI) enhances an organization's ability to analyze challenges, support decision-making, and improve performance. The term “Business Intelligence System” refers to applications and technologies that facilitate BI activities, including data collection, storage, access, and analysis—thus providing insights into performance and aiding informed decisions. These activities include decision support systems, querying, reporting, OLAP, statistical analysis, forecasting, and data mining. BI applications encompass reporting tools, analytics platforms, dashboards, alerts, and portals, and involve technologies such as data integration, quality management, warehousing, and content analysis. Accordingly, a Business Intelligence System can function as a Decision Support System. This study uses SPSS version 17 for data analysis to evaluate the impact of BI and decision support on decision-making quality in colleges in Jakarta and Bekasi. ANOVA (F-test) results show an F-value of 117.041, exceeding the F-table value of 3.29, with a significance of 0.000 < α = 0.05. Since the calculated F-value surpasses the critical value and the significance level is below 0.05, the null hypothesis is rejected. Thus, BI and decision support significantly and simultaneously influence decision-making quality (Y). These findings highlight the essential role of BI and decision support in improving decision-making within higher education institutions.
Palembang to Indonesian Language Translation Machine Using the No Language Left Behind Approach Finaldo, Muhammad; Kunang, Yesi Novaria
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4105

Abstract

The Palembang language, deeply rooted in the cultural fabric of South Sumatra, continues to serve as a vital means of daily communication for many communities. As globalization accelerates, safeguarding such regional languages has become increasingly urgent, particularly through technological solutions that can bridge communication between local speakers and visitors. This study introduces an automatic translation system designed to convert Palembang text into Indonesian, employing the No Language Left Behind (NLLB) algorithm—a recent development in artificial intelligence for language processing. A dataset containing 7,917 pairs of Palembang and Indonesian sentences was assembled for this purpose. The translation models were trained and assessed using BLEU (Bilingual Evaluation Understudy) and chrF (Character n-gram F-score) metrics. The initial model achieved a BLEU score of 22.55 and a chrF++ score of 43.22. Subsequent improvements raised these scores to 30.72 and 55.39, respectively, reflecting a significant enhancement in translation quality and clarity for Indonesian readers. By focusing on a language with limited digital resources, this research demonstrates the potential of modern translation technologies to support both linguistic preservation and practical communication needs in diverse cultural settings.

Page 22 of 29 | Total Record : 284

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