cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
register@ft.unipdu.ac.id
Editorial Address
Kompleks Pondok Pesantren Darul Ulum, Rejoso, Peterongan, Jombang, East Java, Indonesia, 61481
Location
Kab. jombang,
Jawa timur
INDONESIA
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 7 Documents
 1 
Search results for , issue "Vol 8 No 2 (2022): July" : 7 Documents clear
The Impact of Personal, Environmental, and Information Platform Factors on Disaster Information Sharing on Twitter Amriza, Rona Nisa Sofia; Ngafidin, Khairun Nisa Meiah; Ratnasari, Wiwit
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.v8i2.2540

Abstract

Twitter has become a major platform for disseminating disaster news, providing people with disaster information quickly and precisely. A lot of essential and valuable information can be obtained from this online platform. Twitter users might be able to help with warnings and submit specific and accurate information in a disaster situation. This research attempts to examine factors that affect disaster information-sharing behavior. Furthermore, this study aims to integrate personal, environmental, and information platform factors to gain more insight into the factors influencing Twitter users' willingness to share disaster information. The hypotheses were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The result showed that Altruism, Self-efficacy, Community Identity, and Information Platforms significantly influence people's decisions to share disaster information on Twitter.
Detecting violent scenes in movies using Gated Recurrent Units and Discrete Wavelet Transform Imah, Elly Matul; Laksono, Ivan Kurnia; Karisma, Karisma; Wintarti, Atik
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.v8i2.2541

Abstract

The easiness of accessing video on various platforms can negatively impact if not done wisely, especially for children. Parental supervision is needed so that movies platforms avoid inappropriate displays such as violence. Violent scenes in movies can trigger children to commit acts of violence, which is not desired. Unfortunately, it is not easy to supervise them fully. This study proposed a method for automatic detection of violent scenes in movies. Automatic violence detection assists the parents and censorship institutions in detecting violence easily. This study uses Gated Recurrent Units (GRU) algorithm and wavelet as feature extraction to detect violent scenes. This paper shows comparative studies on the variation of the mother wavelet. The experimental results show that GRU is robust and deliver the best performance accuracy of 0.96 while combining with mother wavelet Symlet and Coiflets8. The combination of GRU with wavelet Coiflets8 shows better results than the predecessor.
Predicting the Number of Passengers of MRT Jakarta Based on the Use of the QR-Code Payment Method during the Covid-19 Pandemic Using Long Short-Term Memory Jayadi, Riyanto; Indriasari, Taskia Fira; Chrisna, Charis; Fanuel, Putri Natasya; Afita, Rayhana
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.v8i2.2546

Abstract

The trend of using public transportation has been rising over the last several decades. Because of increased mobility, public transportation has now become more crucial. In modern environments, public transportation is not only used to carry people and products from one location to another but has also evolved into a service company. In Jakarta, Mass Rapid Transit Jakarta (MRTJ) started to operate in late 2019. Recently, they updated their payment gateway system with QR codes. In this study, we predicted the hourly influx of passengers who used QR codes as their preferred payment method. This research applied machine learning to perform a prediction methodology, which is proposed to predict the number of passengers using time-series analysis. The dataset contained 7760 instances across different hours and days in June 2020 and was reshaped to display the total number of passengers each hour. Next, we incorporated time-series regression alongside LSTM frameworks with variations in architecture. One architecture, the 1D CNN-LSTM, yielded a promising prediction error of only one to two passengers for every hour.
Student Satisfaction with Online Learning: A Multigroup Analysis Santosa, Paulus Insap
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.v8i2.2804

Abstract

The Coronavirus disease 2019 pandemic “forced” students to attend online classes roughly from mid-March 2020. This situation, which caused universities, among other institutions, to deal with an overnight change in course delivery from traditional face-to-face to online mode, has resulted in many students facing difficulties. They must cope with the available infrastructure, unstable and limited Internet connection, course delivery, and their self-discipline. Male and female students may have different preferences regarding technology use. This study focused on student satisfaction with the above situation and determined whether a difference exists between male and female students using Technology Acceptance Model as the main theoretical background. Seven hypotheses were proposed and tested with the whole dataset and comparisons between the two groups. Due to the strict health protocol, an online survey was employed using Google Form to collect data. Respondents were 327 undergraduate students from one higher institution in Yogyakarta, comprising 140 male and 187 female students. The population consisted of undergraduate students who have been attending online classes since March 2022. A multigroup analysis was performed using SmartPLS 3.3.3. Results indicated no gender difference in all hypothesized relationships. The theoretical contribution can be seen from the use of Internet Quality, User Interface Quality, and Delivery Quality as the three exogenous variables of the proposed model. The practical contribution is that technology designers must pay attention to the different preferences of user groups.
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.
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

Page 1 of 1 | Total Record : 7

 1 

Filter by Year

2022 2022


Reset
Filter By Issues
All Issue Vol 11 No 2 (2025): July (In Progress) Vol 11 No 1 (2025): January Vol 10 No 2 (2024): July Vol 10 No 1 (2024): January Vol 9 No 2 (2023): July Vol 9 No 1 (2023): January Vol 8 No 2 (2022): July Vol 8, No 1 (2022): In progress (January) Vol 8 No 1 (2022): January Vol 7, No 2 (2021): July Vol 7, No 1 (2021): January Vol 6, No 1 (2020): January-June (Articles In progress 4/7) Vol 6, No 1 (2020): January-June (Articles in press 2/7) Vol 6, No 2 (2020): July Vol 6, No 1 (2020): January Vol 6, No 1 (2020): January-June Vol 5, No 1 (2019): January-June (In progress: 1/7) Vol 5, No 2 (2019): July-December Vol 5, No 2 (2019): July Vol 5, No 1 (2019): January-June Vol 5, No 1 (2019): January Vol. 5 No. 1 (2019): January Vol 4, No 2 (2018): July Vol 4, No 2 (2018): July-December Vol 4, No 1 (2018): January-June Vol 4, No 1 (2018): January Vol 3, No 1 (2017): Januari-Juni (3/7) Vol 3, No 2 (2017): July Vol 3, No 2 (2017): July-December Vol 3, No 1 (2017): January Vol 2, No 2 (2016): Juli-Desember Vol 2, No 2 (2016): July Vol 2, No 1 (2016): January Vol 2, No 1 (2016): Januari-Juni Vol 1, No 1 (2015): Januari-Juni Vol 1, No 1 (2015): January More Issue