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The internship registration process at the Communication and Information Office of Tegal Regency is still carried out manually, resulting in several problems, such as lengthy registration procedures, difficulties in managing and retrieving data, and the risk of document loss. This study aims to design and develop a web-based internship registration information system that supports the registration, verification, selection, and information delivery processes in an integrated manner. The system was developed using the Waterfall method, which consists of requirements analysis, system design, implementation, and testing stages. The application was developed using the Laravel framework and MySQL database. System testing was conducted using the Black Box Testing method to ensure that all system functions operate according to user requirements.The results indicate that the developed system can simplify the internship registration process, improve data management efficiency, accelerate the selection process, and provide real-time registration status information to applicants. Based on the testing results, all system features function properly and meet the predetermined functional requirements.

Asset inventory management is vital for enhancing the operational efficiency of an organization. At the Communication and Informatics Office of Tegal Regency, the process for managing asset inventory is still performed manually, leading to various issues including challenges in asset documentation, data retrieval, management of borrowing, reporting damage, and overseeing the condition of assets. This research intends to create a web-based asset inventory management solution that leverages Quick Response (QR) Code technology to boost the effectiveness, efficiency, and precision of inventory management. The methodology employed for the system's development was Agile Development, which includes stages such as planning, analyzing requirements, designing the system, developing, testing, and conducting iterative evaluations. Data gathering was conducted through observation, interviews, and reviewing existing literature. The completed system offers several key features, such as inventory management, the ability to generate and scan QR Codes, processes for borrowing and returning assets, damage reporting, a monitoring dashboard, and management of user access based on roles.  The findings reveal that the implemented system enhances asset identification through QR Codes, delivers real-time inventory data, and enables more efficient monitoring of assets. According to Black Box Testing results, all functionalities of the system performed in alignment with the identified functional requirements. Consequently, the web-based asset inventory management system utilizing QR Code technology can act as a useful solution to enhance the asset inventory management quality at the Communication and Informatics Office of Tegal Regency.

Advancements in information technology encourage MSMEs to utilize information systems to enhance the effectiveness of their business management. Es Teh Arjuna, an MSME in Tegal City, faces challenges in monitoring partner sales and managing revenue because transactions are recorded manually using disparate methods; this results in slow data recapitulation, a risk of recording errors, and difficulty for the business owner in quickly accessing sales information. This study aims to analyze requirements, design, develop, and test a web-based information system for partner sales and revenue that provides information in  real-time. The Waterfall model was used for system development, while data collection involved observation, interviews, and a literature review. The system was developed using PHP and MySQL and tested via Black Box Testing. The results demonstrate that the system successfully integrates sales data from all outlets into a centralized database, streamlining the management of products, outlets, employees, cashiers, and sales transactions, as well as facilitating the generation of revenue reports for specific periods. Furthermore, the system enables the business owner to monitor sales performance more quickly, accurately, and systematically, thereby supporting decision-making and improving the operational efficiency of Es Teh Arjuna.

Manual server administration introduces operational inefficiencies and elevated risks of human error. This study evaluated the effectiveness of server administration automation utilizing Shell scripting and Cron Job scheduling within a virtualized Linux Debian 12 environment. An experimental method compared manual execution against automated procesases based on execution duration, resource consumption, and error reduction. The findings indicated that the automated system executed backup routines within 0.043 seconds, demonstrating a 95.16% time efficiency increase compared to the manual baseline of 0.89 seconds. Automated monitoring maintained a stable resource allocation, utilizing 275 megabytes of memory and low central processing unit usage between 0.0% and 1.3%. Furthermore, automation reduced operational failures to 0%. In conclusion, this integration significantly optimizes server reliability.

The emergence of Internet of Things (IoT) technology has opened up considerable possibilities for automation systems aimed at enhancing energy efficiency in both home and office settings. This study focuses on the creation and deployment of an IoT-driven Smart Home system utilizing ESP32 for the automatic and manual supervision and regulation of electrical appliances within the Employee Dormitory of the Institute for Lecturer Performance Development (LPKD). The established system employs a Passive Infrared (PIR) sensor for detecting human presence and a Light Dependent Resistor (LDR) sensor to assess the intensity of light in the room. The data from these sensors is analyzed by the ESP32 microcontroller, which controls lights and fans automatically through relay modules based on the surrounding conditions. Furthermore, the system is linked to the Blynk application and the Telegram Bot API to enable remote operation and immediate notifications. The methodological approach taken in this research is Research and Development (R&D) employing a prototyping method. The assessment outcomes show that the system functions reliably, with success rates for sensor detection and appliance management exceeding 95%. The introduction of this system aims to boost electrical energy efficiency, improve user experience, and facilitate the adoption of IoT-centered smart facility management within the LPKD framework.

Changes in work patterns driven by digital technology development and post-pandemic dynamics have encouraged organizations to implement Work From Home (WFH) as an alternative working system. This policy has attracted considerable attention because it affects employee productivity and well-being, which are essential for organizational performance. However, previous studies have reported inconsistent findings regarding the effectiveness of WFH. Therefore, this study aims to analyze the impact of WFH on employee productivity and well-being. A qualitative approach was employee using the Systematic Literature Review (SLR) method by reviewing 19 scientific articles related to productivity, job satisfaction, work-life balance, and mental health. The findings show that 89,5% of articles reported positive effects of WFH through greater flexibility, work comfort, time efficiency, and improved work-life balance, wich contribute to higher productivity and well-being. Meanwhile, 10,5% identified negative effects due to inadequate work facilities, internet disruptions, burnout, and coordination difficulties. These findings indicate that WFH effectiveness is influenced by technological support, job characteristics, and organizational culture. The study implies that organizations should adopt adaptive work policies, strengthen digital infrastructure, and provide mental health support to optimize employee productivity and well-being.

This research was conducted to examine the implementation of the Accurate system in recording cement purchase transactions at PT. XYZ and to evaluate its effectiveness in supporting the company's operational activities. A qualitative approach was employed, emphasizing the analysis of descriptive data in the form of words and documents. The study was carried out using a case study method to obtain an in-depth understanding of the phenomenon being investigated. During the internship period, data were collected through interviews, observations, and documentation techniques. Research shows that the Accurate system helps companies record purchases in a more organised, faster and more accurate way than the manual method using Microsoft Excel. The Accurate system can automatically record purchase invoices, business debts, suppliers and the inventory of goods. This makes the accounting department more efficient. Accurate helps to reduce the risk of recording errors and makes it easier to find transaction data. However, when it is being used, there are still several problems, such as delays in entering transaction data, mistakes when entering names or account numbers, and being unable to change invoices after a certain amount of time. To get around these problems, the company checks the transaction data again and makes sure that the recording process is more consistent. Research results show that the Accurate system is effective in PT. XYZ can help make sure that the process of recording cement purchases is effective and efficient. It can also help make sure that financial information is more accurate and joined up.

The rapid development of information and communication technology has encouraged military organizations to adopt modern systems capable of supporting operational effectiveness. One of the challenges faced by the Indonesian Marine Corps is the limitation of conventional monitoring methods that still rely on voice reports through tactical radios and manual communication systems. This condition often causes delays in information delivery, inaccuracies in troop positioning data, and difficulties in controlling personnel and logistics in dynamic operational environments. This study aims to formulate a conceptual model for the utilization of a GPS Tracking System integrated with Marine Corps communication equipment to improve troop and material movement monitoring. The study employed a Research and Development (R&D) method with a descriptive qualitative approach. Data were collected through literature review, observation, interviews, questionnaires, and documentation involving operational personnel and military communication experts. The results indicate that integrating GPS Tracking Systems with communication equipment can provide real-time location information, improve command and control effectiveness, accelerate reporting processes, enhance logistics supervision, and support operational evaluations through recorded movement data. The proposed concept is expected to strengthen situational awareness, increase operational efficiency, and support mission success in future Marine Corps operations.

This study investigates the integration of digital twin technology and machine learning for predictive analysis in smart mechanical systems. The research emphasizes the role of intelligent computational frameworks in improving industrial monitoring, predictive maintenance, and operational efficiency within Industry 4.0 environments. A qualitative content analysis approach was employed by reviewing scientific literature, industrial reports, and previous studies related to digital twins, artificial intelligence, and predictive analytics. The findings indicate that digital twin architectures supported by machine learning algorithms can significantly enhance real-time monitoring, fault prediction accuracy, and maintenance optimization. The integration of IoT devices, cloud computing, and intelligent analytics also improves industrial sustainability, reduces operational downtime, and supports data-driven decision-making processes. Furthermore, the study identifies several technological challenges, including cybersecurity risks, data integration complexity, and computational limitations. Overall, the proposed intelligent digital twin framework provides a promising approach for future industrial innovation and sustainable smart mechanical system management

Lead (Pb²⁺) contamination in wastewater is a major environmental concern due to its toxicity, persistence, and ability to accumulate in living organisms. Adsorption using biomass-based materials has been developed as an alternative treatment method because it is efficient, economical, and environmentally friendly. This study aimed to analyze the effect of bioadsorbent dosage and contact time on Pb²⁺ removal efficiency and evaluate Pb²⁺ mass distribution using mass balance analysis in a batch adsorption system. Ramie leaf (Boehmeria nivea) was utilized as a bioadsorbent due to its lignocellulosic content, which provides active sites for metal ion adsorption. The research was conducted experimentally through bioadsorbent preparation, chemical activation, and batch adsorption using artificial Pb²⁺ solutions with variations in bioadsorbent dosage and contact time. Pb²⁺ concentrations before and after adsorption were analyzed using Atomic Absorption Spectroscopy (AAS). The obtained data were used to determine removal efficiency and Pb²⁺ distribution between the liquid phase and bioadsorbent. The results showed that ramie leaf bioadsorbent effectively reduced Pb²⁺ concentration, with the optimum condition obtained at 4 g/L bioadsorbent dosage and 90 minutes contact time, achieving 98.46% removal efficiency. Mass balance analysis indicated that Pb²⁺ ions were successfully transferred from the solution phase onto the bioadsorbent surface. These findings demonstrate that ramie leaf bioadsorbent has potential as a sustainable alternative material for heavy metal removal in wastewater treatment.

The implementation of web-based archive digitalization can help improve performance in the field of archive recording, which was previously still manual at the Naval Academy. Some of the obstacles include archiving that is still manual, many files lost due to piled-up storage systems, and human resources in the field of archiving that are still lacking. This study aims to increase time and cost efficiency in archive processing, reduce the risk of loss and damage to archives, and improve the abilities and skills of human resources in the process of using digital archives. This type of research is descriptive qualitative. The data collection techniques are interviews, observation, and documentation with respondents as well as appropriate documentation. The data analysis was carried out through the processes of data reduction, data display, as well as verification or drawing conclusions. The research results can help improve the efficiency and security of archiving by minimizing risks, so that archive management can enhance efficiency and effectiveness, focusing on the implementation of web-based applications.


Digital transformation in public services has encouraged government institutions to develop technology-based services, including the Online Police Record Certificate (SKCK) service at Kupang City Regional Police Resort. This study aims to analyze the effectiveness of the Online SKCK service as an administrative requirement at the Kupang City Regional Police Resort. The research employed a qualitative approach with a descriptive method. Data were collected through observation, interviews, and document analysis involving service officers and users of the Online SKCK service. Data were analyzed using an interactive model consisting of data reduction, data display, and conclusion drawing. The findings indicate that the Online SKCK service has improved accessibility, service efficiency, and transparency through the implementation of the PRESISI POLRI application. Based on the effectiveness indicators, namely program understanding, target accuracy, timeliness, goal achievement, and real change, the service can be categorized as moderately effective. Target accuracy and real change emerged as the strongest indicators, while program understanding and timeliness still face several challenges, including limited digital literacy among users, application system disruptions, and data verification issues. Nevertheless, the Online SKCK service has provided significant benefits in supporting the modernization of public services. The study concludes that improving system quality, strengthening public outreach, and developing a more integrated service system are necessary to optimize the effectiveness of the Online SKCK service at the Kupang City Regional Police Resort.

This study aims to design and implement a simple solar panel-based battery charging system equipped with protection and voltage limiting circuits. The study was conducted to address the limitations of a direct solar panel-to-battery connection, which may cause short-circuit risk, reverse current, unstable charging voltage, and excessive battery charging. This research used a design-based experimental approach. The system was developed by preparing a block diagram, dividing it into several functional sub-blocks, and implementing the design into an electronic circuit. The main circuit sections consisted of solar panel protection, voltage limiter, interlocking circuit breaker, power regulator, and voltage divider. The assembled circuit was tested through real-time measurement by observing solar panel output voltage under different time and sky conditions and measuring battery charging time from different initial voltage levels. The results show that the solar panel output voltage varied according to time and weather condition. The lowest measured voltage was 15.0 V under cloudy conditions, while the highest measured voltage was 25.2 V under clear sky conditions around midday. The battery charging test showed that lower initial battery voltage required longer charging time, while voltage closer to the target level required shorter charging time. The evaluation was limited to voltage measurement and charging time; charging current, battery temperature, solar irradiance, and charging efficiency were not measured in detail. The proposed system can be applied for small-scale solar charging, educational practice, and basic renewable energy experiments. The study offers a practical circuit model that integrates protection, interlocking, voltage limiting, and regulation functions using simple and accessible electronic components.

The road project serving as access to Lambo Dam in Rendubutowe Village, South Aesesa District, Nagekeo Regency, East Nusa Tenggara, uses various types of heavy equipment. The analysis method was carried out by recalculating productivity based on field data and references. Productivity calculations were related to the work volume in order to obtain daily productivity and the required duration. Therefore, theoretical calculation knowledge derived from previous studies was needed. Heavy equipment productivity was then analyzed to determine time efficiency. The subgrade work and pavement layer work on the road project to Lambo Dam, located in Rendubutowe Village, South Aesesa District, Nagekeo Regency, East Nusa Tenggara, had a road length of 6.3 km and a road width of 6 m. However, the observation was limited to a 1 km section from Station (Sta) 0+500 to Sta 1+500. The results obtained were productivity and duration for excavation work using an excavator and dump truck, each at 1785.6 m³/day in 4.52 days. Embankment work using an excavator and dump truck each had a productivity of 892.8 m³/day for 3.82 days, a bulldozer of 43,200 m³/day in 0.07 days, and a Vibro Roller of 168 m³/day in 20.27 days. Base course work used an excavator and dump truck with a productivity of 892.8 m³/day in 2.02 days, a motor grader of 23,372.8 m2/day, and a Vibro Roller of 168 m³/day for 10.71 days. Surface course work used a concrete Mixer truck with a productivity of 43.4 m³/day for 36.72 days. Heavy equipment productivity is influenced by the number of units used; the insufficient use of excavators causes dump truck productivity to be less than optimal in transporting excavation and embankment materials. Likewise, Vibro Rollers are needed in more than one unit so that the project can be completed faster

The growth of the nickel mining industry in Indonesia, particularly in Southeast Sulawesi Province, has made this sector one of the main contributors to the Regional Gross Domestic Product (RGDP). However, the development of supporting infrastructure—especially mining haulage roads—still faces various risks that could potentially cause project delays and disrupt operational efficiency. Therefore, a systematic risk identification process is necessary to ensure that project implementation proceeds in accordance with established time, cost, and quality targets. This study aims to identify and assess risks in mining infrastructure development projects using a stakeholder-based approach. This approach is employed to gain an understanding of the risks that arise from the perspectives of the parties involved in the project. The results of this study describe the dominant risks that could potentially occur in nickel mining projects, namely opposition from the local community surrounding the project, conflicts with community organizations, denial of access to project roads, and disruption of project security due to inadequate security measures by authorities. It is hoped that these dominant risks can serve as a basis for developing effective risk mitigation strategies to support the successful and sustainable development of mining infrastructure.

Diesel engines are widely used in the transportation and industrial sectors due to their high thermal efficiency and good operational durability. However, increased fuel consumption due to inefficiency of the injection system remains a common problem. Injector characteristics, particularly nozzle diameter and injection pressure, are important factors that affect the quality of fuel atomization, air-fuel mixing, and combustion efficiency. An inappropriate combination of parameters can cause suboptimal combustion and increase fuel consumption. This study aims to analyze the effect of variations in nozzle diameter and injection pressure on fuel consumption efficiency in diesel engines. The method used is an experiment with variations in nozzle diameter of 0.150 mm, 0.152 mm, and 0.154 mm and injection pressures of 400 bar, 420 bar, and 440 bar. Tests were conducted at engine speeds of 500 rpm, 1000 rpm, and 1500 rpm with a fuel consumption measurement time of one minute for each parameter combination. Fuel consumption was measured using the volumetric method and analyzed through the fuel volumetric flow rate, fuel mass flow rate, Brake Power (BP), and Brake Specific Fuel Consumption (BSFC). The results showed that the combination of a nozzle diameter of 0.150 mm and an injection pressure of 400 bar produced the lowest BSFC value, thus providing the best fuel consumption efficiency. Meanwhile, the combination of a nozzle diameter of 0.152 mm and an injection pressure of 420 bar showed the closest condition to optimal because it was able to provide a balance between atomization quality and the amount of fuel injected, resulting in efficient and stable combustion. Thus, the efficiency of a diesel engine is influenced by the balance of nozzle size and injection pressure, not solely by the lowest fuel consumption.

The area and distance between buildings at POLINELA Campus make the presence of adequate connector roads an important necessity to support the mobility of the academic community. This study aims to optimize the scheduling of flexible pavement construction for the POLINELA Connector Road using the Critical Path Method (CPM) based on Microsoft Project 2021. The research method used is descriptive quantitative by processing the Budget Plan (RAB) data into a project schedule consisting of 11 main activities. CPM analysis is used to determine the sequence of work, dependencies between activities, the critical path, and project completion time. The results show that the total project duration is 23 calendar days (May 11–June 6, 2026). CPM analysis identified 10 activities on the critical path with zero float, while embankment work is a non-critical activity with time flexibility. Applying a Start-to-Start (SS) relationship with a 3-day lag between excavation and embankment work allows parallel implementation, reducing the project duration by 4 days (14.8%) compared to the conventional Finish-to-Start (FS) scenario. These results indicate that implementing CPM through Microsoft Project 2021 can increase execution time efficiency, simplify schedule control, and support decision-making in road construction project management.

The rapid development of information technology drives various business sectors, including the beauty and health industry, to adopt digital systems in their operational management. A Beauty Clinic, a medium-scale aesthetic clinic, faces significant operational challenges in managing human resources, finance, and digital marketing in an integrated manner. This study aims to analyze the existing manual operational system of A Beauty Clinic using the PIECES framework (Performance, Information, Economy, Control, Efficiency, Service), design and configure an Odoo ERP Community Edition implementation integrating the HR, Invoicing/Point of Sale, and Social Marketing modules, and evaluate the operational efficiency improvements achieved. The research employed a qualitative descriptive approach with a case study method and Rapid Application Development (RAD) as the system development methodology. Data was collected through direct observation and semi-structured interviews. The results show that the manual system experienced critical problems across all six PIECES dimensions. Post-implementation evaluation indicates an estimated 80% reduction in the secretary's administrative workload (from 20–25 hours to 3–5 hours per month), over 90% reduction in payroll error frequency, and an 87% reduction in transaction processing time per cashier transaction. The implementation of role-based access control and complete audit trails fundamentally addressed the security vulnerabilities identified in the as-is analysis. This study demonstrates that Odoo Community Edition is an effective, comprehensive, and cost-efficient ERP solution for small and medium-scale beauty clinics seeking to transform from fragmented manual systems to integrated, data-driven information systems.

The thesis supervision process in higher education institutions is still frequently conducted manually, which may lead to inefficiencies in recording supervision data. This study focuses on the development and implementation of a web-based thesis supervision attendance application designed to facilitate attendance documentation, supervision session administration, and systematic monitoring of thesis supervision history. The methodology applied in this study is the Waterfall model, which includes the phases of requirements analysis, system design, implementation, and testing. The application was developed using the Laravel framework and a MySQL database. The system design was modeled using Unified Modeling Language (UML), while the validation process was conducted through Black Box Testing techniques. The research findings indicate that the developed application is capable of performing real-time supervision attendance recording, managing supervision information, and generating attendance reports effectively and efficiently. It can be concluded that the web-based thesis supervision attendance application improves the efficiency and accuracy of supervision record management and supports a more effective thesis supervision monitoring process..

Malware represents an evolving cybersecurity threat that demands more effective detection methods. Conventional signature-based detection systems have limitations in identifying new variants, driving the development of deep learning-based approaches. This research implements and evaluates four variants of the YOLOv11 algorithm (n, s, m, l) for malware classification based on visual image representation. The dataset consists of 22,056 malware and benign images, divided into 70% training, 15% validation, and 15% testing across 8 classes (adware, backdoor, benign, downloader, spyware, trojan, virus, worm). Each model was trained for 100 epochs with batch size 32 using Google Colab with GPU support. Results demonstrate that all variants achieve high accuracy (97.8%-98.1%) with YOLOv11m as the best performer (98.1%). YOLOv11n offers optimal balance between accuracy (97.9%) and efficiency (1.5M parameters, 0.3 ms/img inference) ideal for real-time applications. This research surpasses previous methods such as K-NN (97.18%) and hybrid CNN (96.55%) with superior inference speed (0.3-0.9 ms/img vs tens to hundreds of ms/img), proving the effectiveness of YOLOv11 for fast, accurate, and scalable malware detection.