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Ucu Nugraha
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ucu.nugraha@widyatama.ac.id
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Jurnal Sistem Informasi dan Teknologi Informasi
Published by Universitas Widyatama
ISSN : -     EISSN : 30313449     DOI : https://doi.org/10.33197/justinfo
Core Subject : Science,
Computer Science & IT
JUSTINFO (Jurnal Sistem Informasi dan Teknologi Informasi) aims to provide and accommodate research results, specialized scientific literature on applied studies, studies in information systems (IS)/information technology (IT) environments and public reviews of theoretical developments, methods and applied science related to subjects and industry. This journal is not only to facilitate local, national but also international researchers to publish their work exclusively in English.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 27 Documents
 1   2   3 
A Web-Based Student Grade Management Information System for SMP IP YAKIN West Jakarta Ermelinda Angela Amfotis; Embun Fajar Wati
Jurnal Sistem Informasi dan Teknologi Informasi Vol. 3 No. 1 (2025): December 2025
Publisher : LP2M Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/justinfo.v3i1.3216

Abstract

The world of technology is currently developing very rapidly in line with the great need for information. Currenly the computers has taken a very important role in any work related to data processing, assessment is very important in a learning, assessment is carried out by the teachers to determine the ability of students to master the learning objevtives that have been set. At the SMP IP YAKIN West Jakarta where every work on storing grades is stiil done manually. Judging from this working system, the author sees a lot of inefficiencies and effectiveness or inaccuracy. From this research, the author wants to design an information system application processing student grades at SMP IP YAKIN West Jakarta which aims to produce software. The waterfall research method is used in this study. In data collection, there are two types that need to be collected, namely primary data and secondary data, primary data is the result of observations and interviews from relevant sources, while secondary research data uses the technique of collecting learning data or reading experts. This research resulted in a student grade  processing application system, which is designed to help check grades quickly and precisely. Help in the search for student grades because of the grades stored in the database.
Tinjauan Sistematis untuk Mengoptimalisasi Pengalaman Pengguna Chatbot untuk Akses Layanan Mikro dan Keuangan Mikro pada UMKM Fawwaz shabri Muttaqi; Agus Juhana
Jurnal Sistem Informasi dan Teknologi Informasi Vol. 3 No. 1 (2025): December 2025
Publisher : LP2M Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/justinfo.v3i1.3236

Abstract

The objective of this research is to investigate implementation of chatbots in the microfinance and MSME sectors for better user experience and accessibility of public services. Systematic Literature Review (SLR) is applied in this article to review related articles with strict inclusion and exclusion criteria. In this sense, it was identified in an investigation with the aim of finding "chatbot"."conversational AI". "website" and "user satisfaction", restricting that, while chatbots have been studied extensively in other industries, there is limited scale of use Chatbots are not widely used on or by websites. Some of the major challenges observed are low digital literacy, restricted financial access and lack of personalization in user experience. Suggested interventions are enhancing chatbot personalisation, and increasing digital literacy while embedding chatbots with microfinance services. The paper serves to inform on the potential of chatbots for accelerating MSME digitalisation and financial inclusion in Indonesia and other emerging markets.
Optimization of Confidentiality, Integrity, and Availability Through Network Segmentation: A Comparative Simulation Study Maria Rachel Kesya Makarena; Jasmine Alya; Aundrel Aza Sadira; Vorian Gustaf Sumampow; Johannes Hamonangan Siregar
Jurnal Sistem Informasi dan Teknologi Informasi Vol. 3 No. 1 (2025): December 2025
Publisher : LP2M Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/justinfo.v3i1.3358

Abstract

Flat network architectures present significant security and efficiency challenges, exposing organizations to heightened risks of cyberattacks, including data breaches and service disruption, while impeding optimal network performance. This inherent vulnerability directly conflicts with the fundamental information security objectives of Confidentiality, Integrity, and Availability (CIA Triad). To address these critical issues, this research investigates the strategic implementation of Virtual Local Area Network (VLAN) segmentation as a mechanism to concurrently enhance security and operational performance. The study employs an experimental, simulation-based methodology using Cisco Packet Tracer software to design and evaluate a functionally segmented network topology. The model incorporates role-based traffic isolation and enforces precise access policies through the application of Extended Access Control Lists (ACLs) on inter-VLAN routing points. Simulation analysis demonstrates that the proposed architecture yields a dual benefit: a 70% reduction in broadcast domain traffic and up to a 50% decrease in communication latency, substantially improving network efficiency and stability. From a security perspective, the logical isolation of segments successfully contained and mitigated prevalent Layer 2 threats, including packet sniffing and ARP poisoning attacks, thereby strengthening data confidentiality and network integrity. The findings conclusively establish that VLAN segmentation, when integrated with granular ACL policies, serves as a foundational and highly effective strategy. It provides a robust technical framework for enforcing the CIA Triad, transforming network infrastructure from a vulnerable, flat entity into a secure, performant, and resilient organizational asset.
Implementasi Access Control List (ACL) untuk Meningkatkan Keamanan Jaringan pada Lingkungan Organisasi Menggunakan Cisco Packet Tracer Kamal Abrar Ramadhan; Rizky Nathaniel Lukas; Reigan Chenartha; Johannes Hamonangan Siregar
Jurnal Sistem Informasi dan Teknologi Informasi Vol. 3 No. 1 (2025): December 2025
Publisher : LP2M Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/justinfo.v3i1.3360

Abstract

This study investigates the implementation of Access Control Lists (ACLs) as a strategic network security mechanism within organizational environments. The rapid advancement of information systems necessitates effective access control to protect data and network resources from unauthorized intrusion. This research designs and simulates network security using Cisco Packet Tracer to demonstrate how ACLs can restrict access based on predefined security policies. The network topology consists of a router, a switch, two client categories (administrator and general user), and a server. An Extended ACL was deployed on the router to authorize administrator access to the server while restricting access from general users. Simulation results indicate that prior to ACL implementation, all clients maintained unrestricted server access. Following the deployment of the ACL, only the administrator could access the server, whereas user access was successfully blocked. These findings demonstrate that ACLs are effective in enhancing network security by maintaining data confidentiality without compromising the availability of network services.
Implementasi Virtual LAN (VLAN) untuk Isolasi Jaringan Akademik Antara Dosen dan Mahasiswa Nathasa Rowen Frederika Abarua; Ramadhan Alvito Alfian; Rosa Putri Almaira; Johannes Siregar
Jurnal Sistem Informasi dan Teknologi Informasi Vol. 3 No. 1 (2025): December 2025
Publisher : LP2M Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/justinfo.v3i1.3379

Abstract

Network security is a critical aspect in academic environments where multiple user groups with different access privileges coexist within the same infrastructure. Inadequate network segmentation between lecturers and students can increase the risk of unauthorized access, data leakage, and disruption of academic services. This study aims to implement Virtual Local Area Network (VLAN) as a mechanism to isolate academic networks between lecturers and students in order to enhance network security. The research adopts an experimental approach using Cisco Packet Tracer to design and simulate VLAN-based network segmentation. VLAN 10 is assigned to the student network, while VLAN 20 is assigned to the lecturer network, each configured with distinct IP address ranges. Connectivity testing is conducted using ICMP ping to evaluate communication within the same VLAN and across different VLANs. The results show that communication within the same VLAN operates successfully, whereas communication between different VLANs is blocked, indicating effective network isolation. Furthermore, the implementation of VLAN supports the principles of Confidentiality, Integrity, and Availability (CIA Triad) by protecting sensitive academic data, preventing unauthorized data manipulation, and maintaining network service availability for authorized users. These findings demonstrate that VLAN-based segmentation is an effective and scalable solution for securing academic networks in higher education institutions.
An Evaluation of Academic Information System Success at Widyatama University Using the DeLone and McLean Model Isak Ramlan; Muchamad Rusdan
Jurnal Sistem Informasi dan Teknologi Informasi Vol. 3 No. 1 (2025): December 2025
Publisher : LP2M Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/justinfo.v3i1.3412

Abstract

The Academic Information System (AIS) is the backbone of operations and services in modern higher education. Evaluating the quality of AIS is crucial to ensure satisfaction and its success in supporting academic activities. This study aims to evaluate the quality of SIAKAD-UTama  using the DeLone & McLean Model. The DMM identifies six dimensions of information system success System Quality, Information Quality, Service Quality, Use, User Satisfaction, and Net Benefits. The study employed a quantitative approach, using a survey of 200 respondents who were SIAKAD-UTama  users. Data were analyzed using Partial Least Squares Structural Equation Modeling using SmartPLS 4.0. The results of the measurement model analysis indicated that all constructs met the requirements for convergent validity (AVE > 0.50) and reliability (CR > 0.70). The results of the structural model analysis show that Information Quality has the most significant influence on User Satisfaction β = 0.387; p = 0.000 and Use β = 0.298; p = 0.002. System Quality has a significant influence on User Satisfaction β = 0.215; p = 0.014 but not significant on Use β = 0.156; p = 0.069. Service Quality also has a significant influence on User Satisfaction β = 0.178; p = 0.045. There is a significant relationship between Use and User Satisfaction. Both User Satisfaction β = 0.356; p = 0.000 and Use β = 0.289; p = 0.001 significantly influenced Net Benefits. The results of this study provide insight for Widyatama University to optimize AIS by prioritizing improving Information Quality to increase satisfaction, utilization, and benefits for the academic community.
Diabetes Risk Prediction Using Machine Learning Methods: A Case Study of Logistic Regression, Random Forest, and Support Vector Machine Putri Ines Salsabilla; Alicia Stifa Nur Sahra; Davina Intan Aurelya; Cahyono Budy Santoso
Jurnal Sistem Informasi dan Teknologi Informasi Vol. 3 No. 2 (2025): June 2026
Publisher : LP2M Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/justinfo.v3i2.3474

Abstract

Diabetes is a global health problem whose prevalence continues to increase and has the potential to cause serious complications if not detected early. Early detection of diabetes risk is very important to prevent fatal consequences and support more effective clinical decision-making. This study aims to analyze and compare the performance of three machine learning algorithms, namely Logistic Regression, Random Forest, and Support Vector Machine, in predicting diabetes risk based on patient symptom and health condition data. The methods used include data collection from open sources, data pre-processing with imputation and normalization, model training using the three algorithms, and model performance evaluation based on accuracy, precision, recall, and F1-score metrics. The dataset used consisted of 520 samples with 17 attributes, including main symptoms such as frequent urination, excessive thirst, and demographic factors. The results of the study show that the Random Forest algorithm has the best performance with an accuracy of 99%, precision of 1, recall of 0.99, and F1-score of 0.99, surpassing Logistic Regression and Support Vector Machine. These findings confirm that Random Forest is very effective in capturing the complexity of clinical data and can be relied upon as a tool for early detection of diabetes risk. This research contributes to the development of decision support systems in the field of digital health by offering an accurate and efficient machine learning-based prediction approach.

Page 3 of 3 | Total Record : 27

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