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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.
Arjuna Subject : -
Articles 219 Documents
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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.
Network Forensics Against Address Resolution Protocol Spoofing Attacks Using Trigger, Acquire, Analysis, Report, Action Method Wijayanto, Agus; Riadi, Imam; Prayudi, Yudi; Sudinugraha, Tri
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 8 No 2 (2022): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i2.2953

Abstract

This study aims to obtain attack evidence and reconstruct commonly used address resolution protocol attacks as a first step to launch a moderately malicious attack. MiTM and DoS are the initiations of ARP spoofing attacks that are used as a follow-up attack from ARP spoofing. The impact is quite severe, ranging from data theft and denial of service to crippling network infrastructure systems. In this study, data collection was conducted by launching an test attack against a real network infrastructure involving 27 computers, one router, and four switches. This study uses a Mikrotik router by building a firewall to generate log files and uses the Tazmen Sniffer Protocol, which is sent to a syslog-ng computer in a different virtual domain in a local area network. The Trigger, Acquire, Analysis, Report, Action method is used in network forensic investigations by utilising Wireshark and network miners to analyze network traffic during attacks. The results of this network forensics obtain evidence that there have been eight attacks with detailed information on when there was an attack on the media access control address and internet protocol address, both from the attacker and the victim. However, attacks carried out with the KickThemOut tool can provide further information about the attacker’s details through a number of settings, in particular using the Gratuitous ARP and ICMP protocols.
Enhanced PBFT Blockchain based on a Combination of Ripple and PBFT (R-PBFT) to Cryptospatial Coordinate wibowo, Achmad Teguh; Hariadi, Mochamad; Suhartono, Suhartono; Shodiq, Muhammad
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 8 No 2 (2022): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v8i2.3041

Abstract

In this research, we introduce the combination of two Blockchain methods. Ripple Protocol Consensus Algorithm (RPCA) and Practical Byzantine Fault Tolerance (PBFT) are applied to cryptospatial coordinates to support cultural heritage tourism. The PBFT process is still used until the preparation process to ensure a maximum error of 33%, and every node would add a new chain in all nodes, so PBFT has a slower processing speed than other methods. This research cuts the PBFT process. After the preparation process in PBFT, the data was entered into the RPCA node and was calculated using an equation to minimize errors with a maximum limit of 20%. After this process, the was were sent to the commit process to store the data in all connected nodes in the Blockchain network; we call this combination of two methods R-PBFT. Combining the two methods can enhance data processing security and speed because it still uses the PBFT work combined with the speed of RPCA. Furthermore, this method uses a fault tolerance value from the RPCA of 20% to enhance data processing security and speed.
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.
Facemask Detection using the YOLO-v5 Algorithm: Assessing Dataset Variation and R esolutions Kurniawan, Fachrul; Astawa, I Nyoman Gede Arya; Atmaja, I Made Ari Dwi Suta; Wibawa, Aji Prasetya
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 2 (2023): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i2.3249

Abstract

The Covid-19 pandemic has made it imperative to prioritize health standards in companies and public areas with a large number of people. Typically, officers oversee the usage of masks in public spaces; however, computer vision can be employed to facilitate this process. This study focuses on the detection of facemask usage utilizing the YOLO-v5 algorithm across various datasets and resolutions. Three datasets were employed: the face with mask dataset (M dataset), the synthetic dataset (S dataset), and the combined dataset (G dataset), with image resolutions of 320 pixels and 640 pixels, respectively. The objective of this study is to assess the accuracy of the YOLO-v5 algorithm in detecting whether an individual is wearing a mask or not. In addition, the algorithm was tested on a dataset comprising individuals wearing masks and a synthetic dataset. The training results indicate that higher resolutions lead to longer training times, but yield excellent prediction outcomes. The system test results demonstrate that face image detection using the YOLO-v5 method performs exceptionally well at a resolution of 640 pixels, achieving a detection rate of 99.2 percent for the G dataset, 98.5 percent for the S dataset, and 98.9 percent for the M dataset. These test results provide evidence that the YOLO-v5 algorithm is highly recommended for accurate detection of facemask usage.
Journal Editorial Board & Table of Contents Ayunda, Nisa
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 8 No 2 (2022): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Detecting Objects Using Haar Cascade for Human Counting Implemented in OpenMV Mentari, Mustika; Andrie Asmara, Rosa; Arai, Kohei; Sakti Oktafiansyah, Haidar
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 2 (2023): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i2.3175

Abstract

Sight is a fundamental sense for humans, and individuals with visual impairments often rely on assistance from others or tools that promote independence in performing various tasks. One crucial aspect of aiding visually impaired individuals involves the detection and counting of objects. This paper aims to develop a simulation tool designed to assist visually impaired individuals in detecting and counting human objects. The tool's implementation necessitates a synergy of both hardware and software components, with OpenMV serving as a central hardware device in this study. The research software was developed using the Haar Cascade Classifier algorithm. The research process commences with the acquisition of image data through the OpenMV camera. Subsequently, the image data undergoes several stages of processing, including the utilization of the Haar Cascade classifier method within the OpenMV framework. The resulting output consists of bounding boxes delineating the detection areas and the tally of identified human objects. The results of human object detection and counting using OpenMV exhibit an accuracy rate of 71%. Moreover, when applied to video footage, the OpenMV system yields a correct detection rate of 73% for counting human objects. In summary, this study presents a valuable tool that aids visually impaired individuals in the detection and counting of human objects, achieving commendable accuracy rates through the implementation of OpenMV and the Haar Cascade Classifier algorithm.

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