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Ceddi Journal of Information System and Technology (JST)
Published by Yayasan Cendekiawan Inovasi Digital Indonesia
ISSN : 2829808X     EISSN : 28296575     DOI : https://doi.org/10.56134/jst.v1i1.1
Core Subject : Science,
Computer Science & IT Decision Sciences, Operations Research & Management
Ceddi Journal of Information System and Technology (JST) is a peer-reviewed journal that publishes articles through fair and transparent quality control. We understand that authors need facilities for their papers, whereas readers expect reliable information from these journals. Therefore, our editorial team and reviewers strive to maintain quality and ethics in the authorship and publishing of all articles. In principle, we strive to provide the best service for the research community around the world. We hope this journal can be a new source of insight and inspiration for future research. Ceddi Journal of Information System and Technology (JST) publish the best articles the results of research on issues of concern, the latest and the trend internationally. Submitted papers must be written in English at title and abstract of paper for the initial review stage by editors and further review process by minimum of two reviewers. The scope of the journal includes: - Information Systems - Web Application - Computer Network - Mobile Application - Game Development - Decision Support System - Big Data - E-Commerce - Cloud Computing - Data Mining
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 51 Documents
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Design and Development of a Smart Trash Bin to Minimize Odor from Household Waste Based on the Internet of Things Mohd Abdul Ghaffar; David HL, David; Kim Leah; Mansyur
Ceddi Journal of Information System and Technology (JST) Vol. 3 No. 2 (2024): December
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v3i2.51

Abstract

The problem that occurs is that household waste continues to increase along with the development of population and the number of increasingly dense settlements. The existence of this household waste is of concern to the community and the government because it can cause various negative impacts. Based on the results of observations of the existing trash cans, the accumulation of household waste is the source of this unpleasant odor. Smell is connoted as something that tends to disturb comfort, and gives the impression of being unclean and the like, such as fishy, rotten, urine, rancid, and so on. The smell of burning garbage is also dangerous because it contains H2 which reduces the amount of oxygen in the air. This study aims to prevent the occurrence of unpleasant odors from garbage. The tool will be designed using the NodeMCU microcontroller with website-based monitoring and Whatsapp notifications automatically when the trash can is full and automatic deodorizing powder spraying according to the concentration of gas released by the stench. This study uses the Experimental and Comparative Testing method in designing an IoT-based Smart Trash Bin tool and conducting tests on the built system and comparing the test results with the expected system. The results of this study indicate that the Smart Trash Bin tool can work and function as expected, namely being able to minimize the unpleasant odor emitted by the trash can and being able to monitor the sprinkling of deodorizing powder, the status of the height of the trash can and can provide notifications both automatically and manual to officers through the website.
Public Room Door Locking System Using Wireless Technology and Internet of Things Mahmud Mustapa; Irwan; Ummiati Rahmah; Akbar Iskandar; Ahmed J. Obaid
Ceddi Journal of Information System and Technology (JST) Vol. 3 No. 2 (2024): December
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v3i2.77

Abstract

Enhancing the efficiency and security of public spaces has become increasingly important, leading to the development of an automatic door lock system utilizing wireless technology and the Internet of Things (IoT). This study aims to design and implement a smart door lock system that provides automated control and improves convenience in managing public room access. The research methodology involves programming the ESP32 microcontroller, integrating IoT applications, and conducting various testing methods. These include manual control through physical switches, automated control via the Sinric Pro platform, and Wi-Fi hotspot-based control using the ESP32 module. Comprehensive hardware and software testing was carried out to ensure system reliability and functionality. The results indicate that the proposed system enables seamless control of public room doors through multiple methods, including an Android-based application and Wi-Fi connectivity. By leveraging IoT technology, the system offers a user-friendly, efficient, and secure solution for managing public space access, addressing modern requirements for convenience and safety.
Design of a Web-Based Goods Inventory Information System for an Office Stationery Store Pathak, Vijey North Sandep; Robbi Rahim; Rahmania; Kamaruddin; Erwin Gatot Amiruddin
Ceddi Journal of Information System and Technology (JST) Vol. 3 No. 2 (2024): December
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v3i2.80

Abstract

Hasco Stationery Store, located on Jalan Perintis Kemerdekaan Km 09, is a business specializing in printing and office stationery sales. Effective management of stock availability, purchasing, and sales processes is crucial to meeting customer needs. Prior to implementing an integrated information system, inventory management at the store was performed manually by employees, who relied on estimates and experience to record stock, check inventory, and place purchase orders. This manual approach proved inefficient and prone to errors, including inaccurate stock calculations, recording mistakes, and data loss. To address these challenges, this study employed the waterfall development method to design and implement a web-based inventory information system aimed at enhancing the efficiency and accuracy of inventory management processes. Data were collected through interviews with the store owner, direct observations, and analysis of relevant documents, supplemented by a literature review on stock management principles and information system development. The resulting system simplifies stock management, reduces errors, and improves overall operational efficiency, providing a robust solution for inventory management at the Hasco Stationery Store.
Implementation of a Rule-Based Decision Support System in Determining the Level of Customer Satisfaction with Services Kerry Buck Manulak; Shaiful; Wisda; Mandeine Resyi
Ceddi Journal of Information System and Technology (JST) Vol. 3 No. 2 (2024): December
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v3i2.85

Abstract

Sarmi Car Wash is a car and motorbike washing service located at Jalan Sultan Hasanuddin No. 52, offering pick-up and drop-off services within a specified range. To enhance employee performance and customer service, the business seeks to implement a decision support system (DSS) to monitor employee performance and assess customer satisfaction effectively. This research aims to design a web-based DSS application that utilizes rule-based assessments of employee performance, integrating data such as employee names and tenure as references for developing the system. The study employed data collection methods including observation, interviews, documentation, and literature review. The system was tested using the black-box method, confirming that it functions as intended. Additionally, based on a user assessment questionnaire, the application achieved an average score of 80.4%, indicating its suitability and effectiveness for implementation. The developed system provides an efficient solution for improving service quality and employee performance monitoring at Sarmi Car Wash.
Evaluating Deep Learning Models for Website Phishing Attack Detection: A Comparative Analysis Raji Egigogo, Abdullahi; Ismaila Idris; Olalere, Morufu; Opeyemi Aderiike, Abisoye
Ceddi Journal of Information System and Technology (JST) Vol. 3 No. 2 (2024): December
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v3i2.100

Abstract

Phishing attacks remain a significant security threat in cyberspace, targeting individuals and businesses to steal confidential information. Traditional detection methods often struggle to identify newly created or altered phishing sites, highlighting the need for more adaptive solutions. This study evaluates the performance of various deep learning (DL) models for detecting online phishing attacks. A comparative analysis of single and hybrid DL models, including CNN, LSTM, BiGRU, and their combinations, is conducted. The evaluation is based on metrics such as accuracy, precision, recall, and F1-score, derived from 17 peer-reviewed publications published between 2019 and 2024. Results indicate that hybrid models, particularly ODAE-WPDC, exhibit superior performance, achieving accuracy rates of up to 99.28% and robust results across all metrics. Single models, such as CNN and BiGRU, also demonstrate strong performance, with accuracy ranging from 97% to 99.5%. This research underscores the efficacy of deep learning architectures in phishing detection and offers practical guidance for selecting optimal models based on specific requirements.
Digital Receipts for a Greener Future: Web-Based Innovation in Toll Payment Systems Asriani; Mashuri Said; Ahmed H. Arnous
Ceddi Journal of Information System and Technology (JST) Vol. 4 No. 1 (2025): April
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v4i1.79

Abstract

This study presents the implementation of a web-based digital receipt system in the transaction processes of PT. Makassar Metro Network and PT. Jalan Tol is a strategic response to operational challenges during the COVID-19 pandemic. The reliance on printed receipts led to increased operational expenses and issues in receipt management, including frequent loss and negative environmental impact. To address these issues, a web-based application was developed to facilitate access to digital receipts, aiming to reduce the use of thermal paper and improve cost efficiency. The research adopts the System Development Life Cycle (SDLC) methodology using the Waterfall model, which encompasses stages of planning, requirements analysis, system design, implementation, and maintenance. Testing results indicate that all application features functioned as intended, enhancing both accessibility and transaction efficiency. These outcomes suggest that digital receipts can significantly reduce environmental footprints and streamline operational workflows. Furthermore, the developed model offers potential for broader adoption across various industries seeking sustainable and digital transaction solutions. The integration of digital receipts thus emerges as a viable, eco-friendly alternative in the modernization of toll payment systems.
E-Learning Application Based on Learning Management System for Online Teaching Adaptation at State Vocational School Saltanat Meiramova; Imran, Andi Ahmad Ali; Mansyur; Syahrul; Mahmud Mustapa; Ahmed J. Obaid
Ceddi Journal of Information System and Technology (JST) Vol. 4 No. 1 (2025): April
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v4i1.99

Abstract

The learning process at SMK Negeri 1 Bone (State Vocational High School 1 Bone) remains predominantly conventional, requiring physical interactions between teachers and students in the classroom. This limitation highlights the need for technological integration to enhance accessibility and flexibility in education. This study aims to design and implement an e-learning application based on a Learning Management System (LMS) to facilitate online learning adaptation at SMKN 1 Bone. The development follows the UML model, while system testing employs the black-box method. Data were collected through field research and literature reviews from various academic sources. The results of this study led to the development of an LMS-based e-learning application that significantly supports online learning implementation. A user effectiveness test involving 30 respondents yielded a 71.57% feasibility score, categorizing the system as viable. Furthermore, black-box testing confirmed the system's functional reliability. This research contributes to the global discourse on digital education by demonstrating the practical application of LMS technology in vocational education, offering insights into scalable solutions for enhancing learning accessibility and effectiveness worldwide.
Smart Office Implementation System for Electrical Energy Consumption Efficiency Using IoT-Based Fuzzy Algorithm M. Ikhsan U; Andani Achmad; Supriadi Sahibu; Nim Von-Lind
Ceddi Journal of Information System and Technology (JST) Vol. 4 No. 1 (2025): April
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v4i1.110

Abstract

Increased electricity consumption in office environments often results in waste and inefficient costs. This study aims to develop an Internet of Things (IoT)-based Smart Office system using a fuzzy algorithm to improve electricity efficiency. The method used is the Research and Development (R&D) approach with the Continuous Improvement Spiral model. This system is designed by utilizing a DHT11 sensor for temperature and an LDR for light intensity, which is connected to an Arduino Nano as the main data processor. Data is processed using a fuzzy algorithm to control electronic devices, such as lights and fans, and monitored through the Blynk application. The results showed that the system was able to reduce electricity consumption from 63.57 kWh to 41.32 kWh, with significant savings in monthly electricity costs. The average sensor accuracy reached 99.40% for DHT11 and 96.36% for LDR. This system makes a positive contribution to energy efficiency and is a sustainable solution for office environments.
Internet of Things (IoT) Based Air Pollution Detector for Baby Rooms Najmawatih; Imran Taufik; Supriadi; Anders Christensen
Ceddi Journal of Information System and Technology (JST) Vol. 4 No. 1 (2025): April
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v4i1.111

Abstract

Indoor air pollution is a leading cause of respiratory illnesses in infants and children, potentially resulting in severe health outcomes, including death. Common sources include dust, cigarette smoke, cleaning chemicals, and hazardous gases such as carbon monoxide (CO) and nitrogen dioxide (NO₂), particularly in enclosed, air-conditioned (AC) environments. Due to the difficulty of detecting pollutants like fine particulate matter (PM2.5) and CO, an effective, real-time monitoring solution is crucial. This study aims to design and develop an Internet of Things (IoT)-based device capable of monitoring PM2.5, CO, temperature, and humidity, specifically in infant rooms. The system integrates an ESP32 microcontroller with DSM501a, MQ-7, and DHT22 sensors and features automated alerts via a Telegram bot when pollutant levels exceed predefined thresholds. The device was evaluated through a comparative 24/7 testing method over seven days against commercially available standard instruments. Results show a relative error of 25% for PM2.5, 30% for CO, and significantly lower errors for temperature (2%) and humidity (0%). Sensor data is processed and transmitted to the Thingspeak server for real-time graphical monitoring. The Telegram alert feature demonstrated an average response time of 1.84 seconds across 20 tests. The findings suggest that the proposed device offers a viable, accessible, and responsive solution for indoor pollutant detection, contributing to improved air quality monitoring and early warning systems to protect vulnerable populations, especially infants.
A Review of Deep Belief Networks in Intrusion Detection Systems: Applications, Optimization Techniques, and Dataset Utilization Sule Aishat A.; Alhassan John K.; Ismaila Idris; Alabi Isiaq O.; Subairu Sikiru O.
Ceddi Journal of Information System and Technology (JST) Vol. 4 No. 1 (2025): April
Publisher : Yayasan Cendekiawan Digital Indonesia (CEDDI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56134/jst.v4i1.114

Abstract

As reliance on the Internet and interconnected systems for essential services continues to grow, the need for strong cybersecurity defenses has become more pressing. Intrusion Detection Systems (IDS) are crucial in safeguarding these digital infrastructures. This paper investigates how Deep Belief Networks (DBNs) can enhance IDS capabilities, particularly in identifying advanced and dynamic threats such as Distributed Denial of Service (DDoS) attacks, SQL injections, and zero-day vulnerabilities. By reviewing recent research, we explore how DBNs have been applied in IDS contexts, examine optimization methods like layer-wise pre-training and dropout regularization that contribute to better detection performance, and evaluate commonly used benchmark datasets including UNSW-NB15, NSL-KDD, and CSE-CIC-IDS2018. This study compiles empirical evidence to assess DBNs' performance across varied network conditions and traffic types. Findings suggest that DBNs are effective in learning complex data patterns and improving the detection of anomalies. Nonetheless, challenges such as interpretability, high computational requirements, and the limitations of existing datasets continue to hinder widespread adoption. This work adds to the ongoing cybersecurity discourse by outlining major developments, constraints, and future directions for DBN-powered IDS. It ends by proposing strategic improvements, including the development of more efficient models, broader dataset coverage, and real-time, adaptive integration to support smarter and more responsive IDS solutions.

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