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This study aims to explain the effectiveness of assessment in the learning process, focusing on improving student outcomes at SDN Larangan Tokol 1 Pamekasan. This research applies a qualitative methodology categorized as a descriptive study. Data collection was carried out through observation, interview sessions, and document analysis involving teachers and students at SDN Larangan Tokol 1 Pamekasan The findings of the study indicate that the implementation of learning process evaluation is conducted systematically and continuously through question and answer activities, daily assignments, group discussions, learning practice, daily tests, as well as the assessment of students’ attitudes and skills. Teachers use various strategies to improve the effectiveness of learning evaluation, such as the use of varied teaching methods, providing motivation, habituation of discipline, utilization of learning media, and the implementation of remedial and enrichment programs.Supporting factors for the effectiveness of learning evaluation include the support of the principal, teacher competence, parental support, and the availability of learning facilities. Meanwhile, the obstacles include differences in students’ learning abilities, lack of motivation among some students, and limited availability of certain learning media.The assessment of the learning process contributes effectively to improving students’ academic achievement, shaping discipline and responsibility character, as well as increasing students’ participation and collaboration in the ongoing learning process. Therefore, learning assessment plays a crucial role in creating an effective learning process and improving student achievement at SDN Larangan Tokol 1 Pamekasan.

This systematic literature study conducts a comparative analysis of Reliability-Centered Maintenance (RCM) and Total Productive Maintenance (TPM) in manufacturing, and proposes an integrated hybrid model. The research concludes that RCM and TPM are fundamentally distinct methodologies: RCM excels in risk-based, analytical management of complex, high-criticality assets, while TPM is superior for achieving broad-based productivity gains and cultural empowerment through total employee involvement. The effectiveness of each approach is contingent upon factors such as asset characteristics, organizational culture, data availability, and level of automation. To leverage their complementary strengths, the study proposes the Synergistic RCM-TPM Hybrid Model (SRTHM). This framework advocates for a sequential implementation where TPM establishes the foundational operational stability, discipline, and data culture, upon which selective RCM analysis is applied to critical assets for precision risk management. The model incorporates explicit feedback mechanisms to create a continuous organizational learning cycle. The study provides a contingency framework for methodology selection and a practical roadmap for integration, offering theoretical and practical guidance for building more resilient and context-appropriate maintenance systems in modern manufacturing.

In the era of globalization and rapid technological advancement, Indonesia’s indigenous culture faces various challenges that may gradually erode traditional values within society, particularly among the younger generation. Local cultural diversity represents a vital national asset that must be preserved and sustained through strategic efforts, one of which is education. Social studies education plays an important role in instilling students’ knowledge, understanding, and appreciation of local cultural diversity as an essential component of national identity. This article aims to examine the contribution of social studies education to the development of students’ character through respect for cultural diversity in their surrounding environment, the cultivation of tolerance, and the enhancement of cultural awareness. The study adopts a qualitative descriptive approach using a literature review methodology by analyzing relevant academic sources, including books, journal articles, and previous research findings. The results reveal that integrating local culture and indigenous knowledge into social studies learning can strengthen students’ social awareness, deepen their understanding of cultural values, and foster responsible, empathetic, and tolerant character traits. Moreover, the effectiveness of local culture–based social studies education is strongly influenced by the role of teachers as facilitators, motivators, and role models who provide contextual, relevant, and meaningful learning experiences for students.  

The analysis of locutionary speech acts is a pragmatic study that can reveal the role of digital communication in the learning process, particularly in educational videos such as the Positive Psychology Class on the YouTube channel Garvin Goei. Within this video, there are various forms of utterances, such as declarative, interrogative, and imperative, which serve to convey information clearly and build understanding among viewers. The accurate formulation of locutionary utterances will also influence the effectiveness of online learning, necessitating an in-depth analysis to assess their quality. The objective of this research is to identify the forms and functions of locutionary speech acts present in the video, which can subsequently be used as a reference in designing educational content. Good quality locutionary speech acts will impact learners' comprehension and interaction abilities in a distance learning context. The methodology employed is a descriptive qualitative approach, beginning with data collection through observation and note-taking techniques on the Garvin Goei YouTube video. The observation technique involves reading and observing the entire video content, while the note-taking technique includes recording locutionary utterances and re-verifying the obtained findings. After conducting the analysis, 606 data points of locutionary speech acts were obtained, with a dominance of declarative sentences (213), interrogative (145), and imperative (88), indicating variations in sentence structure and the use of conjunctions. The quality of these utterances is evaluated based on clarity of meaning, pragmatic function, and level of complexity. The results of this research are expected to serve as a reference for teaching materials and provide deeper insights into the influence of locutionary speech acts on the quality of digital educational communication.

 Autonomous robot navigation in dynamic and unstructured environments remains a critical challenge due to unpredictable obstacles, sensor uncertainty, and limited adaptability of traditional planning algorithms. Although conventional navigation methods such as graph-based, potential field–based, and sampling-based approaches have been widely adopted, their performance under real-time dynamic conditions is still constrained. This study aims to design and implement a comprehensive experimental framework to evaluate the effectiveness and limitations of conventional navigation algorithms for autonomous mobile robots operating in dynamic unstructured environments. The research adopts an experimental and comparative methodology by implementing A*, Dijkstra, Artificial Potential Field (APF), and Rapidly-Exploring Random Tree (RRT) algorithms in simulated static and dynamic scenarios. Performance is assessed using quantitative metrics including path length, computation time, success rate, collision rate, and path smoothness. The experimental results demonstrate that graph-based algorithms achieve high success rates and optimal path efficiency in static environments but exhibit limited adaptability to dynamic changes. APF offers fast computation but suffers from high collision rates due to local minima, while RRT shows better adaptability in dynamic environments at the cost of longer and less smooth paths. These findings confirm that conventional navigation methods are insufficient for robust autonomous navigation in highly dynamic and unstructured environments. The study highlights the necessity of adaptive and learning-based navigation frameworks, such as deep reinforcement learning, to enhance real-time decision-making, robustness, and autonomy in future robotic systems.

Abstract: Character education has become a critical challenge in secondary education, particularly in learning contexts that emphasize cognitive achievement over affective and behavioral development. Although Project-Based Learning (PjBL) is widely recognized for its potential to foster collaboration and responsibility, character outcomes are often treated implicitly and rarely evaluated systematically. This study aims to develop and evaluate a character-oriented Project-Based Learning framework using a Design-Based Research (DBR) methodology in Islamic secondary education. The research was conducted through iterative design cycles involving problem analysis, instructional design, implementation, evaluation, and refinement. Explicit character indicators were embedded into each phase of the PjBL process and assessed using quantitative and qualitative instruments. Statistical analysis of pretest and posttest data revealed significant improvements in students’ character-related outcomes following the implementation of the proposed framework. Qualitative findings further indicated enhanced student engagement, collaboration, and social responsibility during project activities. The results demonstrate that integrating explicit character indicators into PjBL through a DBR approach enhances the effectiveness of character education beyond conventional instructional practices. This study contributes to the literature by providing a structured and empirically validated framework that bridges Project-Based Learning, Design-Based Research, and character education. The proposed framework offers practical implications for educators seeking to integrate affective learning objectives into active learning environments.