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Energy efficiency in water heaters is a crucial factor in ship operational environments due to limited electricity resources that rely on generators. This study aims to design and build an IoT-based water heater monitoring system with an innovative heat storage medium in the form of a mixture of silica sand and paraffin wax to improve thermal efficiency. Although previous studies have developed temperature monitoring and control systems in IoT-based water heaters, this study specifically fills this gap by analyzing the performance of adding silica sand to overcome the low thermal conductivity of paraffin wax. Using the Research and Development (R&D) method, this system was built with an ESP32 microcontroller as the control center, a DS18B20 temperature sensor for accurate measurements, and the Blynk and Google Sheets platforms for real-time monitoring and data recording. Performance testing was conducted by comparing the water heating rate between pure paraffin wax media and the mixed media. The results showed that the monitoring system functioned reliably, and the main finding proved that the addition of silica sand to paraffin wax significantly increased heating efficiency. This was clearly seen from the reduction in time required to raise the water temperature to 40°C, from 2.5 hours to only 1 hour in the second heating cycle. The results of this study indicate that the integration of silica sand and paraffin wax media with IoT technology can increase the efficiency of water heaters and provide an innovative solution for energy-efficient and environmentally friendly temperature control.

The advancement of information technology today has provided great benefits in the world of education. The construction of computer-based academic information system websites is part of the use of information technology. With information technology, it is possible for academic databases to be processed quickly and easily, so that in the presentation of the required academic information reports can be obtained precisely, quickly, and efficiently. SMP Negeri 2 Wewewa Utara already has sufficient information technology infrastructure, but it has not been used optimally in academic management. The school already has a computer lab and internet access, but academic data management is still carried out manually using a ledger and Microsoft Excel application. To address issues such as unintegrated student data, complex and time-consuming grade management processes, delivering academic information, and monitoring student learning progress, an academic information system is needed. The purpose of developing this system is to solve the problems contained in the previous system by creating an academic information system at SMP N 2 Wewewa Utara. With the implementation of the new system at SMP N 2 Wewewa Utara, the knowledge and skills of employees, teachers, and principals in the field of web-based academic information systems can be improved. In the development of the academic information system that will be included in the system, it includes information about students, subjects, student classes, classrooms, teachers, homeroom teachers, and student score reports. The software used is DBMS (Database Management System), while the data storage medium is MySQL and PHP as a Programming Language.

Penelitian ini mengevaluasi efisiensi tiga algoritma sorting hybrid, yaitu TimSort, IntroSort, dan Merge-Insertion Sort, pada dataset skala menengah yang memiliki jumlah elemen antara 10.000 hingga 1.000.000. Tujuan utama penelitian adalah untuk menganalisis performa algoritma berdasarkan waktu eksekusi, konsumsi memori, dan stabilitas, dengan pengujian dilakukan pada berbagai jenis dataset, termasuk data acak, terurut, hampir terurut, dan data dengan banyak elemen duplikat. Pengujian dilakukan melalui simulasi komputasi menggunakan bahasa pemrograman Python dalam lingkungan terkontrol untuk memastikan hasil yang konsisten. Dataset sintetis dibuat untuk mencerminkan kasus dunia nyata, seperti pengolahan log sistem, pengurutan data pelanggan dalam aplikasi e-commerce, atau pengolahan data sensor dalam sistem Internet of Things (IoT). Hasil pengujian menunjukkan bahwa TimSort memiliki performa unggul pada dataset hampir terurut dengan waktu eksekusi rata-rata 0,12 detik untuk 1.000.000 elemen, sedangkan IntroSort lebih cepat pada dataset acak dengan waktu 0,09 detik dan konsumsi memori rendah sekitar 120 MB. Merge-Insertion Sort menonjol dalam hal stabilitas, tetapi memerlukan memori lebih besar, yaitu sekitar 180 MB untuk dataset yang sama. Analisis mendalam menunjukkan bahwa pemilihan algoritma yang optimal sangat bergantung pada karakteristik dataset dan kebutuhan aplikasi, seperti kecepatan untuk data acak atau stabilitas untuk pengurutan data berurutan. Penelitian ini merekomendasikan TimSort untuk aplikasi yang memerlukan stabilitas tinggi, seperti pengolahan data transaksi keuangan, dan IntroSort untuk aplikasi yang mengutamakan kecepatan pada data acak, seperti analitik data real-time. Untuk pengembangan lebih lanjut, penelitian ini menyarankan eksplorasi optimasi paralel atau implementasi algoritma pada perangkat dengan sumber daya terbatas guna meningkatkan skalabilitas dan efisiensi.

Since 2022, the application of the Internet of Things (IoT) in the healthcare sector has grown significantly, marked by the increasing adoption of wearable technology, artificial intelligence (AI), machine learning (ML), and blockchain integration. Research highlights India and China as leading contributors in this domain. IoT enables real-time monitoring of chronic diseases, tracking of patient vital signs, and detection of health protocol compliance. Integrated systems such as Monit4Healthy and RADAR-IoT support personalized medical recommendations and cross-platform interoperability. However, key challenges persist, including patient data privacy and security, system interoperability issues, data fragmentation, and barriers to user acceptance due to cost, digital literacy, and device comfort. Proposed solutions include blockchain for secure data sharing, adaptive congestion control for network performance, and user training to improve technology adoption. Therefore, successful IoT deployment in healthcare requires a comprehensive approach that addresses technological, social, ethical, and sustainability aspects to achieve an effective and inclusive transformation of health services.

The economic empowerment of the congregation is also part of the church's duties and callings, the church is not limited to spiritual strengthening but also about the real life of the congregation. For this reason, this study aims to find strategies that can be carried out by the Toraja church, the Banula congregation, in increasing the potential for economic empowerment within the congregation. To achieve this purpose, the author uses a qualitative research method with a literature study and social analysis model. The literature study was obtained from secondary data originating from books, articles/journals and relevant internet sources. Meanwhile, data obtained from the field is primary data based on observation and interviews. The theory used in this study is about empowerment, the theory of strategy and the theory of leadership. The results of the study are that the church has begun the foundation in economic empowerment and will continue to be improved to the next stage. Considering the natural potential and individual potential in the Toraja church, the Banula congregation is quite important to be developed.

This study examines the implementation of the Coretax system in preparing electronic withholding tax slips (e-Bupot) and submitting Monthly Income Tax Article 21 (PPh 21) Returns at PT RSA. Coretax, launched by the Directorate General of Taxes (DGT) and officially implemented on January 1, 2025, is part of the government’s effort to modernize tax administration and improve taxpayer compliance. The research uses a qualitative descriptive method with a case study approach. Data were obtained through interviews with personnel responsible for PPh 21 administration, direct observation of e-Bupot preparation and monthly tax return filing through Coretax, and documentation review of tax reports and withholding slips. The analysis compares PT RSA’s practices with applicable tax regulations and identifies technical challenges during system use. The results show that PT RSA has complied with prevailing regulations, including the application of the Average Effective Rate (TER) and the utilization of Coretax for tax administration. However, technical constraints remain, particularly unstable internet connections and slow Coretax server performance during peak reporting periods, leading to data entry delays and upload failures. Therefore, improvements in system stability and performance are needed to support timely reporting and optimal tax compliance.

This study examines the implementation of RoRo ship services in Indonesia, highlighting the implementation of RoRo ships and the current national logistics framework potential strategies, particularly in the 3T region. This research employs a qualitative descriptive methodology that includes a literature review. It utilizes secondary data from previous studies, comprising books and original scientific reports published in articles or journals. The findings indicated 1) The use of RoRo ships has gone through progressive developments, like the government's initiative on “Sea Toll” designed to support the logistics sector, particularly in 3T regions. 2) Enhancing the logistics framework through the integration of National Logistic EcosIstem (NLE) alongside the Internet of Things (IoT) to increase logistics efficiency that is rapid, effective, and clear. Nevertheless, these initiatives faces challenges. Consequently. The proposed strategies focus on improving growth center development through logistics integration (shipping, port management, and intermodal) and implementing digitalization in logistics document processing.

Effective communication is a key competency for medical professionals, but traditional classroom-based methods in Indonesia face challenges such as limited practice, geographical barriers, and insufficient exposure to diverse patient scenarios. Mobile-assisted learning (MAL) offers a promising solution to enhance medical communication training outside traditional settings. This study investigates the effectiveness of MAL interventions in developing communication skills among Indonesian medical students and healthcare professionals. A mixed-methods approach was used, involving a quasi-experimental design with pre- and post-assessments of communication competence among 180 participants from three Indonesian medical schools. The MAL intervention included a mobile app with video demonstrations, interactive case scenarios, peer feedback, and microlearning modules. Quantitative data showed a significant improvement in communication competence (mean increase of 23.4%, p<0.001), with notable gains in information gathering (28%), relationship building (26%), and patient education (21%). The mobile platform saw high engagement (average of 4.3 sessions/week) and 87% module completion. Qualitative data revealed increased confidence in consultations, improved cultural sensitivity, and better time management. Challenges included inconsistent internet access, varying digital literacy, and resistance from traditional educators. MAL shows potential for improving medical communication in Indonesia, offering flexible, accessible training. Successful implementation requires addressing infrastructure issues, integrating MAL into existing curricula, and training faculty. This study adds to the growing evidence supporting technology-enhanced medical education in resource-limited settings.

Background: The increasing complexity of industrial production systems requires machine condition monitoring solutions that are capable of operating in real time with high accuracy and responsiveness to support predictive maintenance strategies. Conventional cloud based monitoring systems often experience limitations such as high latency and dependence on stable network connectivity, which can delay decision making processes in critical industrial operations. Objective: This study aims to design and evaluate an Industrial Internet of Things (IIoT) architecture based on edge computing to improve the efficiency of industrial sensor data processing and accelerate anomaly detection in industrial machines. Method: The research adopts an experimental approach by designing a system architecture consisting of a sensor layer, edge computing layer, and cloud layer. Industrial sensors, including vibration, temperature, and current sensors, continuously collect machine operational data, which are then processed locally at the edge node using a machine learning based anomaly detection algorithm. System testing is conducted in a simulated manufacturing environment to evaluate performance based on latency, reliability, and detection accuracy. Results: The results indicate that edge based data processing significantly reduces latency compared with cloud-based processing and enables faster responses to machine condition changes. Additionally, the implemented anomaly detection algorithm achieves high accuracy in identifying abnormal sensor data patterns.

This study examines students’ perceptions of the use of online platforms for English listening practice. The research employs a mixed-methods approach involving 150 undergraduate students through questionnaires and semi-structured interviews. The findings indicate that the majority of students hold positive attitudes toward the use of online platforms, primarily due to time flexibility, diverse content, and the ability to learn independently. Nevertheless, several challenges were identified, including internet connectivity issues that disrupt the learning experience, a lack of personalized feedback, and difficulties in maintaining learning motivation. Features such as adjustable playback speed, the availability of transcripts, and interactive exercises received high levels of satisfaction. Overall, the study concludes that although online platforms have great potential to enhance English listening skills, their effectiveness largely depends on proper implementation, adequate technical infrastructure, and active support from educators. Therefore, this study recommends improvements in technical aspects and the development of more effective learning methods to achieve more optimal outcomes.

This study analyzes the effectiveness of using BNI Bank’s QRIS in improving transaction convenience and efficiency at the canteen of Universitas 17 Agustus 1945 (UNTAG) Surabaya. The research was conducted by a team led by Ida Ayu Nuh Kartini, S.E., M.M., together with students of the Management Study Program, during November–December 2025. The rapid development of digital banking has encouraged the adoption of QRIS as a standardized non-cash payment system regulated by Bank Indonesia. This study aims to examine the level of QRIS BNI utilization, assess ease of use (application access and QR code scanning), and evaluate transaction efficiency, including time savings, queue reduction, and error minimization. A descriptive quantitative approach was employed using a survey method with a five-point Likert scale questionnaire distributed to 36 respondents consisting of students, lecturers, and administrative staff who had used QRIS at the canteen. Primary data were analyzed descriptively using averages and percentages, supported by relevant literature. The results show that QRIS is perceived as highly effective, with scores above 90% for ease of use (95%), transaction speed (92.78%), reduction of change-related issues (97.78%), support for digitalization (97.22%), and security (91.11%). The main limitation identified is dependence on internet connectivity (85%). Overall, respondents strongly support the full implementation of non-cash payment systems at the campus canteen.

This community service activity aims to improve digital literacy among children and adolescents in Telang Sari Village through basic computer training and networking introduction. The main problem faced by the community is the low level of technological literacy caused by limited facilities and lack of access to structured computer education. This program was implemented during the Thematic Community Service Program (KKNT) by applying participatory and practical training methods. The activities included introduction to computer hardware and software, basic typing skills, document creation, internet literacy, and simple LAN configuration practices for junior high school students. The results show a significant improvement in participants’ understanding and confidence in using computers and basic networking concepts. Children and adolescents who previously had minimal exposure to technology were able to operate computers, create simple documents, and understand responsible internet usage. The program also contributed to increasing students’ motivation to learn technology and preparing them to face digital challenges. Overall, this activity demonstrates that basic computer training with hands-on practice can effectively enhance digital literacy in rural communities.

The massive adoption of Internet of Things (IoT) devices is expanding the cyberattacks surface, particularly by the Mirai botnet, which exploits the dynamic characteristics of data traffic. This research proposes a Mirai detection approach based on a Recurrent Neural Network (RNN) optimized using Bayesian Optimization to improve prediction accuracy on sequential data. Unlike previous studies, this research utilizes the latest CIC IoT-DIAD 2024 dataset and applies probabilistic optimization to the hyperparameter space, including RNN units, dropout, and learning rate. The experiment was conducted on 201,021 valid data points, with dimensionality reduction using PCA as the optimal point to represent essential features without redundancy. The results show a significant increase in accuracy from 97.95% to 99.69%, accompanied by an 84% decrease in False Negatives, an 86% decrease in False Positives, and an AUC value of 0.9999. These findings confirm that integrating RNN and Bayesian Optimization not only improves numerical performance but also strengthens the reliability of the intrusion detection system for modern IoT ecosystems with controlled computational loads.

This study examines the administrative problems in managing the Education Data Sistem (Dapodik) as a key instrument for strengthening the institutional capacity of Early Childhood Education (PAUD) in West Sumatra. Using a literature review approach, data were collected from various sources, including reports from the Ministry of Education, Culture, Research, and Technology (Kemendikbudristek), BAN PAUD and PNF, and previous studies. The findings reveal that although Dapodik reporting in West Sumatra has reached 97.8%, several challenges persist, such as limited internet access, low operator competence, insufficient technical supervision, and a lack of institutional awareness of data accuracy. These issues have led to delays in accreditation, misallocation of operational assistance funds (BOP), and ineffective educational planning. Therefore, innovative solutions such as Dapodik gamification, digital inter-institutional mentoring, and operator certification are recommended to improve data management effectiveness and sustainably strengthen PAUD institutional governance.

The implementation of industrial engineering technologies, such as automation, the Internet of Things (IoT), artificial intelligence (AI), and lean manufacturing, has significantly transformed human resource (HR) capabilities in the production sector, particularly in response to the Industry 4.0 paradigm. This study aims to examine the relatively low level of technology adoption in Indonesia, estimated at only 6–20% of manufacturing companies, and its impact on the development of HR competencies. The analysis focuses on changes in technical skill requirements, including digital literacy, data analytics, and technology-based decision-making, as well as the shift in job roles from manual tasks to more strategic functions. This research employs a qualitative descriptive approach grounded in sociotechnical systems theory and the strategic alignment model. The findings indicate that existing skill gaps can be addressed through continuous upskilling and reskilling programs, supported by strengthened triple helix collaboration among government, industry, and educational institutions. The implementation of these strategies has been shown to increase productivity by approximately 30–72% and enhance the competitiveness of the national production sector in the global industrial landscape.  

The rapid development of the Internet of Vehicles (IoV) has introduced new security challenges, particularly in protecting Controller Area Network (CAN Bus) communications from cyberattacks such as Denial of Service (DoS) and spoofing attacks. This study proposes the implementation of the Extreme Gradient Boosting (XGBoost) algorithm combined with Information Gain feature selection to improve intrusion detection performance in IoV environments. The CICIoV2024 dataset, which represents both benign and malicious traffic, is used as the primary data source. The research process includes data integration, preprocessing, feature selection, data splitting, and model training using a 5-fold cross-validation approach. Experimental results demonstrate that the proposed model achieves outstanding performance, with accuracy, precision, recall, and F1-score exceeding 99.99%, and an Area Under Curve (AUC) value approaching 1.00. Furthermore, Information Gain successfully identifies the most influential CAN payload features, enhancing model efficiency without sacrificing accuracy. These findings confirm that the combination of Information Gain and XGBoost is highly effective for developing a fast, accurate, and efficient intrusion detection system in IoV networks.

ARP spoofing attacks are a serious threat to network security, particularly in vulnerable Internet of Things (IoT) environments. This final project aims to detect ARP spoofing attacks on IoT net-works using a combination of Random Forest (RF) and Robust PCA methods. RF is chosen for its classification capabilities and handling of non-linear data, while Robust PCA is used for di-mensionality reduction and handling outliers in the data. The dataset used is "MITMArpSpoof-ing.pcap.csv," which contains network traffic data. The data is processed by performing prepro-cessing, feature scaling, and converting labels to binary (0 for benign, 1 for ARP spoofing). Subsequently, Robust PCA is applied to reduce data dimensions, and then the data is trained using the RF model. The test results show that the RF model with Robust PCA achieves an accu-racy of 96.02% in detecting ARP spoofing attacks. This method has proven effective in identify-ing and classifying ARP spoofing attacks on IoT networks.

The JKN Mobile application is an electronic-based service innovation introduced by BPJS Health to facilitate JKN participants in accessing healthcare services and managing their membership information. This study aims to explore the experiences and perspectives of outpatient patients regarding the effectiveness of the JKN Mobile online registration system at Baubau City Regional General Hospital. A qualitative phenomenological approach was employed, with informants selected through purposive sampling. Data were collected to capture the meanings of patients’ experiences in using the application. The findings show that most patients are satisfied with the practicality, speed, and flexibility of the online registration system. However, technical problems, particularly unstable internet connectivity, remain a major challenge. Furthermore, the online registration system has contributed to improved service efficiency and patient satisfaction. These findings indicate the importance of continuous evaluation and improvement of the JKN Mobile online registration system to enhance service quality and health information system development at Baubau City Regional General Hospital.

This study aims to analyze the effectiveness of the Village Information System in Delima Village as one of the village government's efforts to improve the quality of public services. The study used qualitative methods with descriptive research and data collection techniques such as observation, interviews, and documentation. The results of the study indicate that the implementation of the Village Information System in Delima Village has not been running effectively. Although this system has been used for administrative activities such as issuing certificates, managing population data, and disseminating village information, its implementation still faces various obstacles. Some of these inhibiting factors include limited human resources who have not fully mastered technology, lack of training for village officials, and unstable internet connections throughout the village. As a result, services through the Village Information System are not optimal and have not yet fully benefited the community. Therefore, it is necessary to increase the capacity of village officials and provide infrastructure support so that the implementation of the Village Information System in Delima Village can run more effectively in the future.

The use of technology-based learning media, such as Smart TVs, has great potential in improving the quality of learning in elementary schools (SD). Smart TVs can support interactive learning, enrich teaching materials, and increase student learning motivation. However, in reality, many elementary schools still face limited supporting facilities so that their use is not optimal. This study analyzes the use of Smart TV in elementary schools with limited infrastructure, teacher readiness, and its impact on the learning process. The analysis method was carried out qualitatively through the study of school conditions, observations, and interviews with teachers. The results of the study show that the limitations of the internet network, the lack of supporting devices, and the lack of teacher training are the main factors that hinder the effectiveness of the use of Smart TVs. The impact of these limitations is the low integration of technology in learning, limited access to digital materials, and the suboptimal role of teachers as facilitators. Therefore, policy support from the government, improving school facilities, and teacher training programs are needed so that the use of Smart TVs can run optimally. The conclusion of the study emphasizes that Smart TV has the potential to become an innovative learning medium in elementary schools if supported by adequate infrastructure facilities and teacher competence in accordance with the demands of the digital era.