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Register: Jurnal Ilmiah Teknologi Sistem Informasi
Published by Universitas Pesantren Tinggi Darul ulum
ISSN : 25030477     EISSN : 25023357     DOI : https://doi.org/10.26594/register
Core Subject : Science,
Computer Science & IT
Register: Scientific Journals of Information System Technology is an international, peer-reviewed journal that publishes the latest research results in Information and Communication Technology (ICT). The journal covers a wide range of topics, including Enterprise Systems, Information Systems Management, Data Acquisition and Information Dissemination, Data Engineering and Business Intelligence, and IT Infrastructure and Security. The journal has been indexed on Scopus (reputated international indexed) and accredited with grade “SINTA 1” by the Director Decree (1438/E5/DT.05.00/2024) as a recognition of its excellent quality in management and publication for international indexed journal.
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Articles 7 Documents
 1 
Search results for , issue "Vol 9 No 1 (2023): January" : 7 Documents clear
Drowsy Eyes and Face Mask Detection for Car Drivers using the Embedded System Budiarti, Rizqi Putri Nourma; Nugroho, Bagoes Wahyu; Ayunda, Nisa; Sukaridhoto, Sritrusta
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 1 (2023): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i1.2612

Abstract

Efforts to prevent the spread of the COVID-19 virus have underscored the critical importance of mask-wearing as a preventive measure. Concurrently, road traffic accidents, often resulting from human error, have emerged as a significant contributor to global mortality rates. This study endeavors to address these pressing issues by employing advanced Deep Learning techniques to detect mask usage and identify drowsy eyes, thus contributing to the prevention of COVID-19 and accidents due to driver fatigue. To achieve this objective, an embedded system was developed, utilizing the integration of hardware and software components. The system effectively utilizes MobileNetV2 for face mask detection and employs HOG and SVM algorithms for drowsy eye detection. By seamlessly integrating these detection systems into a single embedded device, the simultaneous detection of both mask usage and drowsy eyes is made possible. The results demonstrates a commendable accuracy rate of 80% for face mask detection and 75% for drowsy eye detection. Furthermore, the mask detection component exhibits a remarkable training accuracy of 99%, while the drowsy eye detection component demonstrates an 80% training accuracy, affirming the system's efficacy in precisely identifying masks and drowsy eyes. The proposed embedded system offers potential applications in enhancing road safety. Its capability to effectively detect drowsy eyes and mask usage in car drivers contributes significantly to preventing accidents due to driver fatigue. Additionally, it plays a vital role in mitigating COVID-19 transmission by promoting widespread mask-wearing among individuals. This study exemplifies the potential of integrating Deep Learning methodologies with embedded systems, thus paving the way for future research and development in the realm of driver safety and virus prevention.
A Bibliometric Analysis of Metaheuristic Research and Its Applications Hendy, Hendy; Irawan, Mohammad Isa; Mukhlash, Imam; Setumin, Samsul
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 1 (2023): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i1.2675

Abstract

Metaheuristic algorithms are generic optimization tools to solve complex problems with extensive search spaces. This algorithm minimizes the size of the search space by using effective search strategies. Research on metaheuristic algorithms continues to grow and is widely applied to solve big data problems. This study aims to provide an analysis of the performance of metaheuristic research and to map a description of the themes of the metaheuristic research method. Using bibliometric analysis, we examined the performance of scientific articles and described the available opportunities for metaheuristic research methods. This study presents the performance analysis and bibliometric review of metaheuristic research documents indexed in the Scopus database between the period of 2016-2021. The overall number of papers published at the global level was 3846. At global optimization, heuristic methods, scheduling, genetic algorithms, evolutionary algorithms, and benchmarking dominate metaheuristic research. Meanwhile, the discussion on adaptive neuro-fuzzy inference, forecasting, feature selection, biomimetics, exploration, and exploitation, are growing hot issues for research in this field. The current research reveals a unique overview of metaheuristic research at the global level from 2016-2021, and this could be valuable for conducting future research.
The Application of Modified K-Nearest Neighbor Algorithm for Classification of Groundwater Quality Based on Image Processing and pH, TDS, and Temperature Sensors Amalia, Hasna Shafa; Athiyah, Ummi; Muhammad, Arif Wirawan
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 1 (2023): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i1.2827

Abstract

The limited availability of water in remote areas makes rural communities pay less attention to the water quality they use. Water quality analysis is needed to determine the level of groundwater quality used using the Modified K-Nearest Neighbor Algorithm to minimize exposure to a disease. The data used in this study was images combined with sensor data obtained from pH (Potential of Hydrogen), TDS (Total Dissolved Solids) sensors and Temperature Sensors. The test used the Weight voting value as the highest class majority determination and was evaluated using the K-Fold Cross Validation and Multi Class Confusion Matrix algorithms, obtaining the highest accuracy value of 78% at K-Fold = 2, K-Fold = 9, and K- Fold = 10. Meanwhile, the results of testing the effect of the K value obtained the highest accuracy value at K = 5 of 67.90% with a precision value of 0.32, 0.37 recall, and 0.33 F1-Score. From the results of the tests carried out, it can be concluded that most of the water conditions are suitable for use.
Designing Halal Product Traceability System using UML and Integration of Blockchain with ERP Kusnadi, Adhi; Arkeman, Yandra; Syamsu , Khaswar; Wijaya, Sony Hartono
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 1 (2023): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i1.3045

Abstract

Consuming halal food is mandatory for Muslims, but meeting the growing demand for halal products has been a challenge for Muslim producers. Importing halal products from non-Muslim countries can raise doubts about their halal status. Therefore, a traceability system is needed to ensure the halalness of products. This research proposes a new traceability system by utilizing ERP, Blockchain, and smart contract technologies based on HAS 23000. This study is the first to combine these technologies. Using the System Development Life Cycle (SDLC) method, the design diagram has been successfully developed into an application system prototype. The use of ERP can help companies reduce operational costs, while the combination with blockchain technology ensures more transparent information, data protection, and system security. The system also uses smart contracts to make automated decisions. By managing the procurement of halal products, companies can ensure that products with halal assurance reach consumers.
Credit Risk Assessment in P2P Lending Using LightGBM and Particle Swarm Optimization Dasril, Yosza; Muslim, Much Aziz; Hakim, M. Faris Al; Jumanto , Jumanto; Prasetiyo, Budi
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 1 (2023): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i1.3060

Abstract

The credit risk evaluation is a vital task in the P2P Lending platform. An effective credit risk assessment method in a P2P lending platform can significantly influence investors' decisions. The machine learning algorithm that can be used to evaluate credit risk as LightGBM, however, the results in evaluating P2P lending need to be improved. The aim of this research is to improve the accuracy of the LightGBM algorithm by combining the Particle Swarm Optimization (PSO) algorithm. The novelty developed in this research is combining LightGBM with PSO for large data from the Lending Club Dataset which can be accessed on Kaggle.com. The highest accuracy also presented satisfactory results with 98.094% of accuracy, 90.514% of Recall, and 97.754% of NPV respectively. The combination of LightGBM and PSO shows better results.
Designing a Mobile Application to Assist Micro-Entrepreneurs in Understanding the Food Business Legality Process Umami, Izzatul; Ahmad Naim Bin Che Pee; Hamzah Asyrani Bin Sulaiman; Ariy Khaerudin
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 1 (2023): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i1.3061

Abstract

Micro-entrepreneurs are considered crucial by the government and stakeholders in economic development. However, the coaching and development opportunities for microenterprises have been limited, leading to a lack of technological advancements and self-competence among business actors. This research aims to address this gap by presenting the design and development of a mobile-based learning application called the Food Business System App (FBS App). The FBS App serves as a valuable resource for micro-entrepreneurs to acquire business knowledge related to government policies and enhance the value of their products. Developed using the Smart Apps Creator app on the Mobile App digital platform, the FBS App includes a collection of papers and videos covering various aspects of business and product legality. The learning content is divided into five parts: licensing, product branding, product manufacturing examples, and feedback. The FBS App is designed to minimize internet data usage, provide user-friendly experience, ensure fast technology access, and offer reliable technology performance for users with limited technological proficiency. The User-Centred System Design (UCSD) approach was employed in the application's design process, and the System Usability Scale (SUS) method was used for testing, resulting in a score of 77.2. It is anticipated that the FBS App will serve as a valuable reference tool for micro-entrepreneurs, enabling them to enhance the quality and competitiveness of their products.
Business-IT Alignment through Enterprise Architecture in a Strategic Alignment Dimension: A Review Yoppy Mirza Maulana; Azmi, Zafril Rizal M; Phon, Danakorn Nincarean Eh
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 1 (2023): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i1.3084

Abstract

Business-IT Alignment (BITA) refers to the fit between business and IT strategy. BITA is important for realizing the achievement of organizational goals, enhancing performance, and gaining competitive advantage in an organization. BITA is a crucial concern for organizations and remains a top topic from the perspective of business executives. BITA can be realized through Enterprise Architecture (EA), which is a comprehensive and holistic instrument for managing and maintaining BITA. However, despite numerous literature studies on the BITA model or framework through EA, the research is currently more focused on technology planning than strategic planning. Meanwhile, strategic planning is the most crucial challenge of the EA framework because it is the embodiment of BITA in the strategic alignment dimension. The current study aims to conduct a literature review of BITA through EA in the strategic alignment dimension. This literature study resulted in 25 out of 100 papers and classified into five strategic alignments. The review identified 25 relevant papers out of 100 and categorized them into five strategic alignments. The study's contributions include solutions in the form of stages for developing strategic alignment through EA based on business strategy models. The five stages are as follows: 1) Identification of vision, mission, and goals; 2) SWOT-based strategy analysis; 3) BSC-based strategy mapping; 4) BPMN-based business process mapping; and 5) Determination of IS/IT. This study's impact on further research is that it can be used as a basis for developing BITA through EA, based on the five stages identified.

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