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This research examines the optimization of the administrative service system at the Regional Personnel Agency of Central Kalimantan Province using a descriptive qualitative approach. The focus of the research includes the implementation of the service system, identification of obstacles, and development of a resolution strategy. The results revealed that the administrative service system has been implemented through six main aspects that are integrated with each other, including guest services, management of incoming letters and dispositions, numbering of outgoing letters, reporting on letter administration, file distribution, and distribution of Decision Letters (SK). The main obstacle identified is the management of non-physical incoming mail that has not been well organized, but has been overcome through a systematic search strategy and intensive internal communication. Efforts to improve service quality are implemented comprehensively through the development of employee competencies, strengthening work integrity, periodic evaluations, and building a culture of excellent service, all of which contribute to improving the effectiveness of the overall administrative service system.

Learning of the Qur'an and Tajweed is an important aspect of education in Islamic boarding schools, because it is the foundation in understanding Islamic teachings as a whole. One of the factors that greatly affects a student is the application of the learning method used by the teacher. With the Active learning method as one of the effective ways to teach the Qur'an and Tajweed in the Putra Islamic Boarding School Dormitory, this study uses a qualitative approach with the research object of 30 students who participated in the learning program for 40 days through data collected through direct observation, in-depth interviews with teachers and students, and analysis of documents related to the teaching and learning process.The results of the study show that the methods applied, such as the use of the Recitation method, and active learning which have succeeded in improving students' understanding of tajweed and reading skills of the Qur'an. This interactive and effective method involving group-based learning has a positive impact, which can be seen from the increase in students' confidence in reading the Qur'an. In addition, the results of the evaluation showed that students felt more comfortable, and interested and motivated to learn when using methods that involved social interaction.Thus, this study recommends the application of more innovative and comprehensive learning methods to increase the effectiveness of learning the Qur'an and Tajweed in Islamic boarding schools. It is hoped that this research can be a reference for pesantren managers in designing better learning programs and empowering students to master the Qur'an properly and correctly.

The results of the research show that 1) Islamic boarding school management planning in improving the competency of students, namely starting from the planning, implementation and management evaluation stages which started from the beginning of the year activities to the end of year activities, namely teacher work meeting activities which included all the elements in MBI Amanatul The ummah of functionary teachers, security guards, sweepers and so on are involved. 2) Implementation of Islamic Boarding Schools in improving the competency of santri, there are daily programs, various extracurricular and organizational activities are handled seriously so that many santri graduates become leaders at universities (such as the President of BEM, head of UKM) and there are reminders of the 7 keys to success that are always upheld. 3) Obstacles and solutions in improving the competency of students, namely the presence of teachers and asatidz, not all of whom live in Islamic boarding schools or in the surrounding area. The solution provided by the institution is the existence of adequate transportation facilities to pick up and pick up teachers and their Asatidz.

This research examines formation management at the Regional Staffing Agency of Central Kalimantan Province using a descriptive qualitative approach. The focus of the research includes the implementation of formation management, identification of the scope of routine activities, and development of optimization strategies. The results revealed that formation management has been implemented through various integrated aspects, including employee needs planning, formation preparation, staffing budget preparation, employee recruitment process, development and training, and performance evaluation. BKD Central Kalimantan Province has shown good performance in carrying out its duties and functions, focusing on developing employee competencies and increasing employee mobility as part of a quality formation strategy.

Palembang Religious Education and Training Center as an education and training institution utilizes information technology, especially wifi internet networks to support various learning and training activities. To support these needs, a quality internet network is needed, so an evaluation and measurement of Quality of Service (QoS) is needed, because QoS is able to measure various important parameters in the network, such as throughput, delay, jitter, and packet loss, all of which play an important role in ensuring the network functions properly.  The standard used is TIPHON. By using the Action Research method, this research will produce real internet quality data in accordance with actual conditions. After testing, the average results on the 4 parameters tested obtained an index value of 3. So that the overall quality of the internet network at the Palembang Religious Education and Training Center has good network quality.

Dengue fever (DHF) is an infectious disease caused by the dengue virus and transmitted through the bite of the Aedes aegypti mosquito. This disease is a major health problem in many tropical countries, including Indonesia. Identification and classification of DHF patients is very important to prevent further spread and to provide appropriate medical treatment. In this study, the classification of DHF disease is carried out using the K-Means algorithm, which is one of the methods in machine learning used to classify data based on similarity of features. This study aims to apply the K-Means algorithm in classifying DHF cases based on data on symptoms that appear in patients, such as high fever, joint pain, skin rashes, and others. The data used includes patient medical records that record various clinical and demographic parameters. The K-Means algorithm is used to group the data into clusters that describe the severity category or potential risk of dengue disease. The results showed that the K-Means algorithm can be used to cluster DHF patients well, with the division of groups that can describe the severity of the disease. Evaluation was conducted using metrics such as silhouette and cluster validity to assess the effectiveness of the algorithm in performing classification. This model is expected to help medical personnel in decision-making, provide early warning, and improve rapid response to dengue cases.

Non-Communicable Diseases (NCDs) pose a growing threat to public health, especially among elderly populations. This community service program was conducted in RT 001 and RT 01A, 20 Ilir 4 Village, Palembang, focusing on early detection and education to prevent NCDs such as hypertension, diabetes, and high cholesterol. The program utilized a participatory action research approach, incorporating health screenings and interactive health education sessions. Activities included blood pressure, glucose, cholesterol measurements, and lifestyle counseling. The results demonstrated a significant increase in awareness and proactive health behaviors among residents. Over 60% of participants with high-risk conditions were referred for further medical evaluation. Regular exercise initiatives and dietary modifications were adopted by the community. The program also established health cadres trained to sustain these efforts post-intervention. This initiative highlights the effectiveness of early detection and education in reducing NCD risks and fostering long-term community health improvements.

This research discusses the impact of the School Literacy Movement (GLS) at MAN 1 Pandeglang to increase students' interest in reading and literacy skills through literacy outreach every Wednesday morning. The method used is descriptive qualitative, with data collection through interviews, observation and documentation. The results show that GLS is implemented in three stages: Habituation, Development, and Learning. Even though there is support from various parties, challenges such as a lack of reading materials and the performance of the school literacy team are obstacles. This research recommends improving facilities and program evaluation to support the success of GLS. With that, the writing of this article will discuss the problem statement: 1) What is the meaning of the School Literacy Movement (GLS) 2) How is the School Literacy Movement (GLS) implemented. 3) What is the impact of the Literacy program on MAN 1 Pandeglang students and students?

Pontianak has a low topographic condition with the state of the  water cathment area that has changed function into a residential area. Pontianak city also has a high rainfall intensity every year. Due to the high intensity of rainfall, some of the rainwater that falls on the earth’s surface is absorebed into the soil which is called infiltration and some flows into surface runoff. To control the surface runoff, a good drainage system must be created. Good drainage channels can help control surface runoff due to high rainfall intensity. In this study, the drainage channel studied was the drainage channel on Purnama 1 street, Parit Tokaya Village, South Pontianak District, Pontianak City, Which currently has a width and height of 7 meters and 1,5 meters. Where from the evaluation of the existing drainage is not optimal optimal in overcoming surface runoff caused by high rainfall in the area. From the results of the calculation analysis the optimal drainage channel in the area has dimensions of 7 meters wide and a depth 1,6714 meters, and a guard height of 0,9141 meters with a surface flow runoff discharge that can be accommodated from the annual daily rainfall data for a 10 years period of 17,5499 .

Computer vision technology has advanced rapidly and made significant contributions across various fields, including object identification in images. This study aims to develop a computer vision-based system to identify fruit types from images. A machine learning model is applied using a dataset of fruit images to train the system for accurate fruit recognition. The primary processes include data acquisition, image preprocessing, feature extraction, model training, and performance evaluation. The results demonstrate a high level of accuracy in identifying specific fruit types, showcasing the potential of this technology in agricultural and commercial applications.

Conflict management is a crucial element in organizational management aimed at effectively improving performance. Poorly managed conflicts can lead to decreased productivity, interpersonal tension, and disruptions in achieving organizational goals. However, when managed with the right strategies, conflicts can act as catalysts for innovation, collaboration, and process improvement. This study uses a literature review method to analyze theories and empirical findings on the urgency of conflict management in organizations. The results show that strategies such as open communication, mediation, and routine evaluation play a significant role in transforming conflicts into opportunities. By implementing effective conflict management, organizations can create a harmonious work environment, enhance collaboration among members, and optimize goal achievement.  

This study aims to identify obstacles and challenges in the application of digital evaluation tools for English learning in grade VI of SD Negeri 2 Siangan. The method used was qualitative descriptive research, with data collection through questionnaires and interviews involving 31 students and grade VI teachers. The results of the study showed that 85% of students felt an increase in learning motivation after using digital evaluation tools, although 40% of students experienced difficulties, especially related to limited internet access. Interviews with teachers revealed that they felt trained enough to utilize this tool effectively. Limited infrastructure and lack of training for teachers were identified as major challenges. Therefore, this study recommends the need to improve technology infrastructure and training programs for teachers to optimize the use of digital evaluation tools in English learning.

This research aims to identify strategies for implementing Pancasila Student Profile activities to support the development of student creativity at SMAN 2 Pandeglang. The method in this research is a qualitative method using a descriptive approach. This data was collected through literature study, which includes searching various written sources such as journals, books and articles as scientific references to build a strong theoretical basis. Apart from that, direct observations were also carried out in the school environment to understand the situation and interactions related to the implementation of the project to strengthen the Pancasila Student Profile (P5). The research results show that effective P5 implementation strategies in encouraging student creativity include three main stages: planning, implementation, and evaluation. The planning stage involves forming a facilitator team, determining themes, and preparing teaching tools. At the implementation stage, activities begin with the introduction of P5 and optimizing the implementation process. Meanwhile, the evaluation stage was carried out to assess the effectiveness of P5 activities involving teachers and students.

Topic modeling is an integral text mining component, employing diverse algorithms to uncover hidden themes within texts. This study examines the comparative performance of prominent topic modeling techniques on news headlines, which is characterized by brevity and specific linguistic style. Given the corpus originates from a non-native English-speaking country, an additional layer of complexity is introduced to the task. Our research explores the feasibility of employing a committee approach for topic modeling, evaluating the efficacy and challenges of various methods in practical settings. We applied three techniques—Latent Dirichlet Allocation (LDA), Non-negative Matrix Factorization (NMF), and BERTopic—to create models with a fixed number of topics (n=40). These models were then tested on approximately 150,000 news headlines. To assess topic coherence, we utilized Word2Vec, human evaluators, and two large language models. Statistical tests confirmed the significance and impact of our findings. BERTopic demonstrated superior coherence compared to NMF, though slightly, but consistently outperformed NMF and LDA according to human and LLM evaluations. The notable disparity in LDA's performance relative to BERTopic and NMF underscores the importance of carefully selecting a topic modeling technique, as the choice can significantly influence the outcome of the analysis.

This community service aims to provide an understanding of financial literacy and training and guidance related to the use of social media to disseminate their products online to students of Muhammadiyah Wanaraja Garut High School. The problem faced by partners in this programme is the lack of understanding of students of Muhammadiyah Wanaraja Garut High School regarding financial literacy. The method of implementing this activity using the Participatory Action Research (PAR) method is carried out starting from the socialisation stage at the beginning of the service activity, in the form of providing information to partners / communities about community service activities to be carried out, the objectives of the activity, the stages of implementing the activity, and the schedule for implementing the activity based on an agreement between the proposing team and partners, the next stage of training and mentoring and evaluation of activities. The results of the activity showed an increase in the literacy knowledge of students of Muhammadiyah Wanaraja Garut High School (SMA) related to financial literacy before and after training.

The reliability of sterilization equipment, such as autoclaves, is essential to ensure patient safety, infection control, and operational continuity in healthcare facilities. Damage or malfunction of autoclaves may disrupt sterilization processes and pose significant risks to medical services. This study aims to develop an expert system for autoclave damage detection using the fuzzy logic method to support faster and more accurate diagnostic decision-making. The proposed system applies fuzzy inference to evaluate the level of damage based on input symptoms provided by users. By handling uncertainty and varying symptom intensities, the fuzzy logic approach enables proportional assessment rather than rigid rule-based classification. The system was designed through knowledge acquisition from technical experts and implemented using fuzzy membership functions and inference rules to determine damage severity levels. Experimental testing was conducted to evaluate system performance and diagnostic accuracy. The results indicate that the expert system successfully generated diagnosis outputs for all tested scenarios, achieving functional diagnostic accuracy within the defined test cases. The system was also able to calculate a quantified damage severity value of 11.6235981% based on the given symptoms, demonstrating its capability to assess damage levels numerically and objectively. Furthermore, the developed system significantly reduces the time required for damage detection compared to manual diagnostic procedures. Automating the evaluation process, it assists electromedical technicians in identifying faults more efficiently and taking preventive or corrective actions promptly. Overall, the implementation of a fuzzy logic-based expert system provides an effective, accurate, and practical solution for improving autoclave maintenance management and supporting healthcare service reliability.

This research discusses the implementation of the duties and functions of the Registrar at the Military Court III - 12 Surabaya in the criminal case administration system. The purpose of this research is to evaluate the suitability of the Registrar's duties with applicable regulations, namely PERMA No. 7 of 2015 and Law no. 31 of 1997 concerning Military Justice. The method used is empirical juridical with a qualitative approach, which includes interviews and document analysis. The research results show that the Registrar has three main tasks: carrying out case administration, assisting judges in trials, and implementing decisions. Even though it complies with regulations, there are challenges in carrying out tasks, such as manual processes, limited register books, and problems with coordination and understanding the law. This research recommends improving administrative facilities and systems, training for human resources, and periodic evaluations to increase the effectiveness of criminal case administration at the III-12 Surabaya Military Court.

Educational management plays a strategic role in determining the success of learning processes in various educational institutions. Evaluation and accountability are two interrelated key elements in shaping an effective, transparent, and sustainable education system. This study aims to develop an adaptive and responsive educational management concept to meet contemporary demands and provide strategic recommendations for educational institutions in improving learning quality. Using a qualitative approach with a descriptive-analytical design, this research finds that the integration of systematic evaluation and strong accountability is a fundamental aspect of educational management. Evaluation provides in-depth data on learning effectiveness, while accountability ensures that every component of the educational system takes responsibility for the outcomes achieved. Together, they significantly contribute to creating an educational management mechanism oriented toward continuous quality improvement. 

This study presents the development and evaluation of an automatic passenger counting system for public buses using the YOLOv8 algorithm based on Convolutional Neural Networks (CNN). Accurate passenger counting plays a crucial role in optimizing public transportation operations, as it enables effective capacity management, reduces operational costs, and improves overall passenger comfort. Conventional manual counting methods are often inefficient, time-consuming, and prone to human error, particularly in high-density urban transportation environments. Therefore, an automated and intelligent solution is required to support real-time monitoring and operational decision-making. The proposed system employs deep learning-based object detection to identify and count passengers from video streams captured by cameras installed inside buses. Two camera positions, namely front and rear views, were evaluated to assess system performance under different visual conditions. The experimental results show that the system achieves high detection accuracy in the front camera view, with a confidence score of 0.82, indicating reliable performance in scenarios with minimal object occlusion. In contrast, the rear camera view demonstrates slightly lower accuracy, with a confidence score of 0.76, mainly due to increased object overlap and variations in lighting conditions. These findings emphasize the importance of appropriate camera placement and environmental consideration in improving detection reliability. In addition, the implementation of the proposed system enables real-time monitoring of passenger flow, which supports dynamic scheduling, demand-based route planning, and efficient fleet management. Accurate passenger data allows transportation operators to optimize service allocation, reduce congestion, and enhance overall service quality. Overall, this study contributes to the development of intelligent transportation systems by demonstrating the practical applicability of deep learning-based passenger counting solutions. The proposed approach offers strong potential for real-world deployment in smart city environments, supporting the creation of more sustainable, efficient, and passenger-oriented public transportation services.

This research analyzes the role of Pancasila in criminal law reform in Indonesia, particularly in relation to corruption and terrorism. Using a normative juridical approach and qualitative analysis of regulations, court decisions, and scientific literature, this research also applies the case study method. Data was collected through official documents and interviews with legal experts and law enforcement. The results revealed a gap between Pancasila values and existing legal practices, with challenges especially in fair law enforcement. The research highlights the need for community participation and strengthening the integrity of public officials for successful reform, as well as the importance of a holistic approach that includes legal education and continuous policy evaluation.