Digital System and Computing

Yurimasanti Rachman, Deden Ardiansyah

Gate security systems in residential areas often rely on manual controls or simple remotes, which limit flexibility, real-time monitoring, and secure access. This study developed an IoT-based automated gate control system using RFID authentication and a web-based interface. The system integrated Arduino Uno, an ESP8266 Wi-Fi module, an RC522 RFID reader, a relay, and a DC motor to automate gate operation, while user activity was monitored through a local web server built on Apache and MySQL. Testing was conducted under controlled indoor conditions with an average Wi-Fi signal strength of -62 dBm, an ambient temperature of 27°C, and a local network latency of 8 to 12 ms. Across 50 trials using five different RFID cards, the system achieved 100 percent reading accuracy, an average response time of 1.42 seconds from tag detection to motor activation, and stable communication with no packet loss. Mechanical implementation using 8.25 kg of galvanized steel and a dual-rail support system ensured stable and smooth gate movement. These results confirm that the system provides secure, contactless, and remotely accessible automated gate control. Future improvements should focus on cloud-based integration and enhanced network stability for real-world deployment.

Digital System and Computing

Lailatul Maulida

Public institutions increasingly depend on IT assets to sustain essential operations, yet many still lack structured risk management frameworks. At TVRI East Java, the absence of a dedicated IT division underscores the need to evaluate asset vulnerabilities and threat exposures systematically. This study identifies and prioritizes critical IT assets and their associated risks using the Quantitative Risk Analysis (QRA) method. Data were gathered through interviews, document analysis, and expert validation. Thirteen IT assets were assessed against fifteen potential threats, and quantitative metrics such as Single Loss Expectancy (SLE) and Annualized Loss Expectancy (ALE) were used to estimate financial impacts. The analysis showed that personal computers are the most critical assets, primarily threatened by computer viruses, while minor peripherals pose minimal risk. Expert verification confirmed that the findings reflect real operational conditions. However, the study’s scope was limited by the reliance on a single expert for data validation, which may constrain the broader applicability of the findings. The results provide a structured basis for risk mitigation strategies and can guide similar institutions in strengthening IT asset management.

Digital System and Computing

Anisatul Mukaramah, Syahiduz Zaman

Organizations are increasingly adopting open-source Human Resource Information Systems (HRIS) due to their cost-efficiency, configurability, and scalability. However, selecting the most suitable platform remains a major challenge due to diverse functional requirements. This study aims to determine the most appropriate Free and Open Source Software (FOSS) HRIS based on key decision-making criteria. A comparative evaluation was conducted on three platforms, IceHRM, OrangeHRM, and Sentrifugo, using the Analytic Hierarchy Process (AHP) to calculate criterion weights and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank the alternatives. Seven HR functional domains, including employee management, attendance, recruitment, and payroll, formed the evaluation framework. The results indicate that IceHRM achieved the highest relative closeness score (RC = 0.7892), followed by OrangeHRM (RC = 0.7428), and Sentrifugo (RC = 0.0133). Based on the evaluation model, IceHRM is identified as the most suitable option due to its alignment with prioritized functional criteria. The proposed AHP-TOPSIS approach provides an objective and replicable decision-support model for organizations undertaking HRIS selection as part of digital transformation initiatives.

Digital System and Computing

Muhammad Rifaldi, Apri Siswanto

The growing demand for smart home automation calls for affordable, efficient, and user-friendly systems that reduce energy consumption and enhance remote accessibility. This study presents the development and evaluation of a voice-controlled smart home prototype utilizing NodeMCU and IoT technologies. The system integrates Google Assistant, IFTTT, and Adafruit IO to process voice commands, support real-time monitoring, and enable cloud-based control of household devices. A prototyping method was applied, focusing on controlling an LED lamp and a 12V DC fan. Black-box testing was conducted using six voice profiles and a total of 60 command scenarios under both stable and unstable network conditions. Results indicated a 93.3% accuracy with stable internet and 86.7% under weak signals. The system achieved average response times of 1.8 seconds (stable) and 3.4 seconds (unstable), operating without critical failures. However, performance was influenced by internet quality and third-party dependencies. Unlike previous studies that relied solely on single-platform control, this research highlights a low-cost, multi-service integration approach for smart home automation, addressing the gap between affordability and real-time cloud-based functionality. The prototype demonstrates the feasibility of accessible voice-activated automation and lays the foundation for future offline-capable smart systems.

Digital System and Computing

Fadlurrohman Agil, Nur Cahyo Hendro Wibowo, Hery Mustofa

The increasing demand for accurate and affordable household electricity monitoring has driven the development of Internet of Things (IoT)–based systems. This study designed and evaluated a real-time energy monitoring system using a NodeMCU microcontroller integrated with a PZEM-004T sensor module. The system was tested on three household appliances, an electric iron, a fan, and a refrigerator, and its measurements were compared with a calibrated reference wattmeter and manual energy calculations. The results showed that the system’s readings closely matched those of the reference device, demonstrating reliable accuracy in capturing real-time energy consumption. Higher deviations were observed against manual calculations, mainly due to the inability of manual methods to capture dynamic load fluctuations, particularly from the refrigerator’s compressor. Overall, the system achieved an average error of 1.19% compared with the reference measurements, confirming its technical feasibility for practical household energy monitoring. Future work should improve accuracy for fluctuating loads through adaptive sampling and expand system scalability via cloud-based integration.

Digital System and Computing