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The student admission process in many educational institutions is still conducted manually, leading to issues such as data duplication, input errors, and delays in reporting. This study designs and implements a desktop-based student registration information system using VB.NET and MySQL, equipped with an admission-status checking feature and an automated quota-management module. The system was developed using the waterfall model, consisting of requirement analysis, system design using UML, implementation, and black-box testing. Two user roles are supported: admin and student. Admin users can manage applicant data, configure program quotas, open or close the registration period, and generate reports, while student users can create accounts, complete registration forms, and independently check their admission results. The implementation results show that all core functions operate validly based on testing involving two respondents. The quota-management feature successfully restricts the number of applicants according to predetermined capacities, and the admission-status module automatically displays pass or fail results. The system improves administrative efficiency, enhances data accuracy, and reduces reliance on manual record-keeping. Therefore, this desktop application serves as an effective solution for schools requiring a reliable and efficient admission management system without depending on stable internet connectivity.

Power transformer theft, a pervasive issue disrupting critical infrastructure, necessitates the development of cost-effective and energy-autonomous security solutions. This paper presents the design and implementation of a detection-focused anti-theft framework that integrates a Raspberry Pi Zero W, camera module, and passive infrared (PIR) motion sensors powered by a solar system for continuous monitoring. The system is designed for remote, off-grid deployment, utilizing a headless Raspberry Pi powered by a 5V solar panel and power bank to ensure energy autonomy. Upon motion detection, captured images are processed on the edge device using OpenCV’s Haar Cascade classifier, optimized for upper-body detection to minimize false positives and verify human presence. Captured images are processed locally on the edge device using OpenCV’s Haar Cascade classifier to confirm human presence before an alert is sent to the mobile application, emphasizing real-time operation and low latency. Once an intrusion is confirmed, the images are saved locally and uploaded via the Secure File Transfer Protocol to a custom-developed Android application. The app provides a dedicated remote monitoring interface, enabling secure file transfer and system access, while providing users with immediate notifications and image management capabilities. The system emphasizes low power consumption, real-time operation, and low deployment cost. Tests over 200 triggered events under varied environmental conditions achieved 90% detection accuracy with an average latency of 4.5 s. Solar autonomy was maintained for approximately 24 h under normal operation. It is concluded that the integration of solar power, edge computing of images, and mobile monitoring provides a feasible, scalable, and financially viable framework for securing transformers, especially in resource-constrained environments.

Administrative services for civil servants (ASN) play a crucial role in ensuring the rights and obligations of government employees. One of these services is the submission process for the Wife Card (KARIS) and Husband Card (KARSU), which serve as official proof of marital status for civil servants. At the BKPSDM of Sumba Barat Daya, the current submission process for KARIS and KARSU is still carried out manually by filling out paper forms and attaching physical documents. This manual method is time-consuming, prone to data errors, and complicates the monitoring process. Therefore, this study aims to develop a digital information system to simplify the submission, verification, and issuance process of KARIS and KARSU online. This research applies a Research and Development (R&D) approach using the Waterfall model, consisting of requirement analysis, system design, implementation, testing, and evaluation stages. The system is developed using the Python (Streamlit) programming framework and a SQLite3 database, designed to be easily accessible to both ASN users and BKPSDM officers through local networks or the internet. The results show that the developed system successfully reduces processing time by up to 60%, improves data accuracy by 90%, and significantly decreases the use of physical documents. The implementation of this digital information system makes the KARIS and KARSU administrative service more efficient, transparent, and accountable, supporting the ongoing digital transformation within the local government of Sumba Barat Daya Regency.

This study aims to analyze the efficiency of issuing tax invoices and reporting Value Added Tax (VAT) Periodic Tax Returns (SPT Masa PPN) by comparing the DJP Online system and the Coretax Administration System at CV XYZ. The research focuses on comparing the reporting process before and after the use of the Coretax digital system, as well as evaluating its direct impact on the efficiency of VAT reporting for Taxable Entrepreneurs (PKP). A descriptive qualitative method was used, with data collected through observation and documentation. The results show that prior to using Coretax, tax reporting was conducted through two separate applications, e-Faktur and e-SPT, which led to inefficiencies, input errors, and longer processing times. After the implementation of Coretax, the reporting process became more integrated, automated, and time-efficient. The system also supports digital document archiving and offers automatic validation and notifications, thereby reducing the risk of delays and reporting errors. Although technical issues such as internet dependency, system errors, and user adaptation remain, Coretax overall has a positive impact on improving tax administration efficiency and compliance at CV XYZ.

Waste management remains a major challenge, particularly due to the lack of public awareness and habits in sorting waste from its source. Innovative technology-based solutions are needed to support more effective waste management systems. This study aims to design and develop an Internet of Things (IoT)-based smart trash bin capable of automatically sorting metal and non-metal waste. The system utilizes an ESP32 microcontroller as the main controller, an LJ12A3-4-Z/BY sensor to detect metal materials, an E18 sensor to detect non-metal materials, and an ultrasonic sensor to monitor bin capacity. The waste separation mechanism is operated by a servo motor controlled by the system, while the Blynk application is integrated for real-time monitoring and full-capacity notifications sent directly to the user’s smartphone. The research stages included hardware design, microcontroller programming, IoT platform integration, and functionality testing to ensure system performance and reliability. The results showed that the smart trash bin operated as expected, successfully identifying and separating metal and non-metal waste automatically, while also sending real-time notifications to the user when the bin approached full capacity. The implementation of this technology has the potential to modernize waste management processes, improve the efficiency of waste sorting, and reduce dependency on manual labor. Furthermore, this research opens opportunities for future development by integrating additional sensors and cloud-based data management systems to support smart city initiatives and sustainable waste management practices.

In the digital era, the demand for practical and efficient security systems has significantly increased, particularly in the context of access control for restricted rooms or buildings. This research aims to develop an automatic door locking system utilizing an RFID card and a NodeMCU ESP32 microcontroller integrated with Internet of Things (IoT) technology through real-time notifications using the Telegram application. The system is designed to replace conventional locking methods that often present various weaknesses, such as key loss, physical duplication, and lack of remote access capabilities. The development method employed is the Research and Development (R&D) approach, consisting of needs analysis, system design, hardware and software implementation, followed by testing and evaluation. The main components used in the system include the RC522 RFID reader for user identification, Espressif manufactures the ESP-32 microcontroller, which is equipped with Wi-Fi and Bluetooth modules to enable wireless internet connections. NodeMCU ESP32 as the control center and internet connector, a relay module as an electronic switch, and a solenoid door lock as the actuator. The results show that the system is capable of accurately reading RFID card UIDs, granting access to registered cards, activating the solenoid to unlock the door, and sending access status notifications to Telegram in an average of less than three seconds. The system also effectively denies access to unregistered cards and sends warning messages accordingly. Therefore, this system enhances the security and efficiency of room access control and has the potential to be adopted as a prototype solution in the development of smart homes or modern access control systems.

The use of technological resources, especially the internet, has a very important role in supporting the effectiveness of the implementation of the flipped classroom model. Through internet access, students can prepare before face-to-face learning by watching learning videos, reading materials, or doing exercises independently. This allows the classroom teaching and learning process to be more interactive, where face-to-face time can be focused on discussion, problem-solving, and application of concepts. Based on survey data collected from students of SMK Dewata Bali Denpasar, it is known that optimal use of the internet helps increase students' understanding and interest in learning science subjects. However, as time went by, it was found that some of the material was still difficult for students to understand and remember. Therefore, educators need to choose the learning platform that is most effective in supporting the implementation of this model. Using the ELECTRE (Elimination and Choice Expressing Reality) method, this study assessed various platforms such as features, price, ease of use, and user survey results. The results show that Google Classroom is the most suitable and efficient platform to support reverse learning because of its ability to integrate various learning media, ease of access, and support for interaction between teachers and students.

This study aims to analyze oppurtunities, threats, and sales strategies through the Tiktok Shop and Tokopedua applications in the Tangerang area. Tiktok Shop and Tokopedia are two major E-Commerce platforms in Indonesia. Tiktok Shop utilizies short video trends and live streaming features to attract young consumers, while Tokopedia offers a strong E-Commerce infrastructure to support online transactions. E-Commerce is a process whereby buyers and sellers exchange information, money, and goods using electronic media. Data collection techniques were carried out through surveys targeting the community in the Tangerang area by distributing questionnaires and using documentation and literature studies that compiled secondary data from official documents published by the Ministry of Cooperatives and Small and Medium Enterprises, APJII, Data Reportal, and the Tangerang City Communication and Information Agency. The result of this study show that the collaboration between Tiktok Shop and Tokopedia opens up enormous growth opportunities, especially for businesses in the Tangerang area. Tangerang is a region with rapid growth in internet users. The younger generation, who actively use tiktok for both entertainment and shopping, is a highly potential consumer segment. Through this collaboration, businesses can reach markets that were previously difficult to penetrate through traditional marketing methods.

This research presents the design, development, and implementation of a mini smart car prototype that operates using Internet of Things (IoT) technology. The system is built around the ESP8266 microcontroller (Amica version), which functions as the core processing unit responsible for handling Wi-Fi communication and data processing. The motion of the car is controlled by an L298 motor driver module that regulates the operation of DC motors. The entire system is powered by a 3.7-volt rechargeable battery, ensuring portability and energy efficiency. The study discusses in detail the hardware configuration, software programming, and integration of IoT-based control through a web or mobile interface. Functional testing of the prototype, named MINIOT, focuses on evaluating the responsiveness, stability, and reliability of remote control operations. The results are expected to show that the system can effectively receive and execute user commands while transmitting real-time telemetry data, such as motor status and connection indicators. This project demonstrates the feasibility of low-cost IoT-based automation for small-scale robotic applications.

This research presents the design, development, and implementation of a mini smart car prototype that operates using Internet of Things (IoT) technology. The system is built around the ESP8266 microcontroller (Amica version), which functions as the core processing unit responsible for handling Wi-Fi communication and data processing. The motion of the car is controlled by an L298 motor driver module that regulates the operation of DC motors. The entire system is powered by a 3.7-volt rechargeable battery, ensuring portability and energy efficiency. The study discusses in detail the hardware configuration, software programming, and integration of IoT-based control through a web or mobile interface. Functional testing of the prototype, named MINIOT, focuses on evaluating the responsiveness, stability, and reliability of remote control operations. The results are expected to show that the system can effectively receive and execute user commands while transmitting real-time telemetry data, such as motor status and connection indicators. This project demonstrates the feasibility of low-cost IoT-based automation for small-scale robotic applications.

In recent years, the Indonesian government has actively promoted digital transformation in public service delivery, including in rural and remote areas. However, digital adoption among communities in these regions remains inconsistent and often hindered by infrastructural and socio-cultural constraints. This study aims to assess the digital readiness of rural communities in adopting mobile-based public service information systems, with a specific focus on understanding the social and technological dynamics that shape their engagement. Employing a mixed methods approach with an explanatory sequential design, the research began with a structured survey involving 150-200 respondents per location, followed by in-depth interviews with key informants such as village officials, service operators, and local users. The quantitative data were analyzed using SPSS to identify general patterns in digital readiness based on the Technology Readiness Index and the Digital Readiness Framework, while qualitative insights were thematically analyzed using NVivo to uncover contextual factors. The findings reveal that while some respondents exhibit a moderate level of digital optimism, barriers such as unstable internet access, limited digital literacy, and fear of misusing technology significantly affect adoption rates. Furthermore, social support from family members emerged as a critical facilitator in overcoming these challenges. This study contributes to the discourse on inclusive digital transformation by highlighting the importance of integrating community-based support mechanisms into system design and policy planning. The implications suggest that successful digitalization efforts in rural areas must go beyond infrastructure development and address the social readiness of users through culturally sensitive and participatory approaches.

The daily exchange of informatics over the Internet has both eased the widespread proliferation of resources to ease accessibility, availability and interoperability of accompanying devices. In addition, the recent widespread proliferation of smartphones alongside other computing devices has continued to advance features such as miniaturization, portability, data access ease, mobility, and other merits. It has also birthed adversarial attacks targeted at network infrastructures and aimed at exploiting interconnected cum shared resources. These exploits seek to compromise an unsuspecting user device cum unit. Increased susceptibility and success rate of these attacks have been traced to user's personality traits and behaviours, which renders them repeatedly vulnerable to such exploits especially those rippled across spoofed websites as malicious contents. Our study posits a stacked, transfer learning approach that seeks to classify malicious contents as explored by adversaries over a spoofed, phishing websites. Our stacked approach explores 3-base classifiers namely Cultural Genetic Algorithm, Random Forest, and Korhonen Modular Neural Network – whose output is utilized as input for XGBoost meta-learner. A major challenge with learning scheme(s) is the flexibility with the selection of appropriate features for estimation, and the imbalanced nature of the explored dataset for which the target class often lags behind. Our study resolved dataset imbalance challenge using the SMOTE-Tomek mode; while, the selected predictors was resolved using the relief rank feature selection. Results shows that our hybrid yields F1 0.995, Accuracy 0.997, Recall 0.998, Precision 1.000, AUC-ROC 0.997, and Specificity 1.000 – to accurately classify all 2,764 cases of its held-out test dataset. Results affirm that it outperformed bench-mark ensembles. Result shows the proposed model explored UCI Phishing Website dataset, and effectively classified phishing (cues and lures) contents on websites.

This study analyzes the role of millennials and Gen Z in driving the growth of halal e-commerce in Indonesia. The global halal industry is projected to reach US$3.36 trillion by 2028, underscoring the importance of strengthening halal e-commerce in Indonesia, which has the largest Muslim population in the world (Kawsar, 2025). Millennials and Gen Z are the dominant users of the internet and digital marketplaces, thus playing a strategic role in expanding the digital halal economic ecosystem. This study uses a qualitative approach with literature studies and in-depth interviews with consumers and halal digital business actors. The analysis focuses on digital behavior, halal product preferences, and awareness of sharia economic principles. The results show that millennials and Gen Z contribute through three main roles. First, as smart consumers who show high preference and loyalty to certified halal products. Second, as creative business actors who create sharia startups and marketplaces with innovative digital marketing strategies. Third, as agents of change who promote digital halal literacy and strengthen public awareness of the importance of halal products and services. In conclusion, the role of these two generations is not only in consumption, but also in creating a sustainable digital halal business ecosystem, strengthening Indonesia's competitiveness in the global halal industry, and supporting national sharia economic development.

The reliability of power distribution systems is a crucial factor in ensuring stable electricity supply for industrial, commercial, and household users. Conventional protection systems often face limitations in terms of real-time monitoring, remote control, and adaptive responses to fault conditions, which can result in longer outage durations and higher operational costs. This research aims to develop a smart protection system for power distribution using Internet of Things (IoT) technology to enhance system reliability. The proposed method integrates IoT-enabled sensors, microcontrollers, and communication modules to monitor critical parameters such as voltage, current, and frequency in real time. Data are transmitted to a cloud-based platform for analysis and decision-making, enabling rapid detection of abnormalities and remote tripping of circuit breakers. The prototype was tested under various fault scenarios, including short circuits and overloads, and demonstrated faster response times compared to conventional systems. Results show that the IoT-based protection system improved fault detection accuracy, reduced downtime, and provided predictive maintenance insights through data analytics. The synthesis of these findings highlights that integrating IoT into protection mechanisms not only increases operational reliability but also supports the transition toward smart grids. In conclusion, the developed system proves effective in addressing the limitations of traditional protection systems by offering real-time monitoring, automation, and enhanced decision-making for modern power distribution networks.

The DH Building of the Electrical Engineering Study Program at Udayana University faces significant challenges in energy efficiency, as it still relies on conventional electrical systems. User negligence, such as forgetting to switch off lights and air conditioners (AC) after use, often results in unnecessary energy waste and increased operational costs. This issue highlights the urgent need for smart solutions capable of automating energy management, reducing waste caused by human error, and supporting the creation of a more efficient and sustainable campus environment. To address this problem, this study designs and implements a smart building system based on the Internet of Things (IoT). The system employs a NodeMCU ESP32 microcontroller as the main processing unit, integrated with a series of sensors including a DHT22 sensor for monitoring temperature and humidity, an MQ2 sensor for smoke detection, a PIR sensor for motion detection, and a PZEM-004T sensor for monitoring energy consumption. Control of electronic devices such as lights and AC units is carried out both automatically and manually through relay modules connected to the system. All sensor data and control functions are accessed via a web interface developed using the Laravel framework and a MySQL database. The testing results indicate that the designed system was successfully implemented and functions as expected. Sensor testing demonstrated high accuracy compared to standard measuring instruments, while the electronic device control system achieved an average response time of approximately 3.6 seconds, proving its reliability. Overall, the system provides a comprehensive solution for energy consumption monitoring and control, while also enhancing comfort and safety in the DH Building, in line with the goals of energy efficiency and facility modernization.

The development of the internet in Indonesia has opened up numerous opportunities, including in the field of online commerce. One widely used feature in online transactions is the "Paylater" system, as implemented by Shopee through its Shopee Paylater service. This feature allows users to purchase goods now and pay for them later, with relatively low interest rates. This study aims to examine the regulations and implementation of Shopee Paylater, as well as the legal protection available to consumers in cases of default or issues with the service. The study refers to the Indonesian Civil Code, Law No. 8 of 1999 on Consumer Protection, and the Financial Services Authority Regulation (POJK) No. 77/POJK.01/2016 on Information Technology-Based Lending Services. The research findings indicate that Shopee Paylater users are bound by a standard agreement with PT. Commerce Finance during the purchasing process. Shopee is responsible for protecting consumers in accordance with applicable regulations, but breaches related to network security can pose risks to consumers. In addition, while the service facilitates easier access to goods and services for users, it is crucial that consumers fully understand the terms and conditions of the service, including the consequences of late payments. The study also emphasizes the need for clearer and more comprehensive consumer protection regulations, especially in light of the rapid growth of digital financial services. This research highlights the importance of adequate legal protection for users of Paylater services to ensure their rights are safeguarded in the evolving digital economy.

This study aims to analyze the satisfaction level of Generation Z visitors at the Serang City Regional Library using Expectation Confirmation Theory (ECT). This theory explains that satisfaction is formed when the actual service meets or exceeds user expectations. The research employed a descriptive quantitative approach with a survey technique, involving 89 respondents aged 17–28 years, selected purposively. The data were collected using a questionnaire with a 1–4 Likert scale and analyzed univariately. The results show that the majority of Generation Z visitors are satisfied with the library services, with 85.4% expressing satisfaction, while 14.6% expressed dissatisfaction. The factors contributing the most to satisfaction were staff friendliness (58.4% reported being very satisfied), room comfort (59.6% reported being very satisfied), and the availability of basic facilities such as tables, chairs, and adequate lighting. However, dissatisfaction mainly stemmed from digital facilities. About 45% of respondents stated that the Wi-Fi connection was unstable, disrupting online information access. Additionally, 60% of respondents felt that the collection of the latest books was still limited, failing to meet the academic and current trends of Generation Z. These findings highlight the importance of improving digital services, enhancing internet network quality, and expanding the collection of up-to-date and popular books. Furthermore, staff competence in digital literacy needs to be enhanced to support the increasing digital needs of users. With these measures, the library is expected to not only maintain visitor satisfaction but also improve its relevance and loyalty in the digital era.

E-learning has become a vital pillar in higher education, especially since the COVID-19 pandemic forced a sudden shift towards digital learning methods. This article examines the effectiveness of e-learning platforms through a comparative literature review (2020–2025), focusing on Moodle, Google Classroom, Microsoft Teams, Zoom, and CIDOS 4.0 as the local platform. The study evaluates aspects of student engagement, accessibility, assessment, and technological innovation. Findings reveal that although e-learning enhances flexibility, challenges remain in terms of the digital divide, system usability, and reliability of assessment. This review highlights that Moodle provides strong interactive and assessment features, while Google Classroom offers simplicity and accessibility but lacks advanced analytics. Microsoft Teams supports collaboration and integration with Office 365, yet requires stable internet. Zoom is highly effective for synchronous interaction but less suitable for task management. CIDOS 4.0 addresses Malaysia’s TVET context but continues to face issues with server stability and user interface design. Beyond platform-specific strengths and weaknesses, the analysis emphasizes that student engagement, fair access, and reliable evaluation methods are central to e-learning effectiveness. Hybrid approaches that combine face-to-face and online learning are identified as the most effective strategy within the Malaysian higher education context. The study concludes that institutions must not only choose appropriate platforms but also enhance digital literacy, invest in infrastructure, and explore innovations such as AI and gamification. These measures can maximize e-learning’s potential to improve teaching, learning quality, and the broader digital transformation of higher education.

Floods are the most frequent natural disasters and cause material and non-material losses. One of the problems faced is the lack of early warning when floods occur. This problem can be overcome with a flood early warning system. This paper discusses the solution to this problem, namely by designing and implementing a real-time flood early warning system using IoT-based Internet of Things (IoT) technology ESP32 MQTT and APK Kodular. The objective of this research, compared to previous studies, shows a gap in the methods used. While previous studies used an IoT-based flood warning system that sends data via SMS or an HTTP server, this study applies real-time monitoring with the MQTT protocol, which allows sending water level data with low latency to the Kodular application for faster and more responsive warnings. The method used is to connect hardware with IoT where ESP32 is a client that sends data to MQTT and will display it in the Kodular APK. This flood early warning system consists of: ultrasonic sensors, ESP32, MQTT cloud, OLED, buzzer, LED, and APK on the phone to receive notifications through a mobile application created using Kodular. This IoT-based system is installed in the Kudu Regency river and can monitor water levels in real-time. Based on a predetermined threshold, the system can activate the LED indicator or buzzer and send an early warning message to the user via the APK on the phone. Test results show that this system functions effectively in providing flood warnings with an accuracy of 1-2 cm and in a timely manner, making it suitable for community-based flood monitoring solutions

Liquefied Petroleum Gas (LPG) leakage remains one of the leading causes of fires in both household and industrial environments, highlighting the urgent need for early detection systems that provide fast and accurate warnings. This study aims to design and implement an LPG leakage detection device based on the ESP8266 microcontroller, utilizing the MQ-6 gas sensor and a real-time notification system through Telegram Bot integration. The system operates by reading LPG gas concentration via the MQ-6 sensor, which is then processed by the ESP8266 to automatically activate a buzzer alarm and a DC fan when gas levels exceed the threshold of 200 ppm. Additionally, the system sends instant alert notifications to the user through the Telegram application, allowing remote monitoring of gas conditions. Real-time gas concentration data are also displayed using a 16x2 LCD for direct visualization. System testing was carried out through controlled gas leakage simulations, and the results showed that the device is capable of responding rapidly, with a reaction time of less than 2 seconds after detection, while consistently providing accurate warnings. The integration of Internet of Things (IoT) technology significantly enhances the effectiveness and efficiency of the system, enabling practical and accessible monitoring. Overall, the developed device demonstrates strong potential as an innovative solution to improve safety, minimize fire risks, and raise public awareness regarding the hazards of LPG leakage, making it suitable for practical application in households and small industries.