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Performance-based management (PBM) has emerged as a critical strategic approach for enhancing organizational productivity in contemporary business environments. This systematic review examines the theoretical frameworks, implementation strategies, and empirical evidence regarding PBM systems and their impact on organizational performance from 2020 to 2025. Through analysis of peer-reviewed literature, this article identifies key mechanisms through which performance management systems influence productivity outcomes, explores organizational challenges in implementation, and proposes evidence-based recommendations for practitioners. The findings suggest that effectively designed and implemented PBM systems, when aligned with organisational strategy, employee development, and stakeholder engagement, significantly contribute to improved productivity metrics. However, success depends on comprehensive change management, adequate resource allocation, and continuous system refinement. This review provides both theoretical insights and practical guidance for organizations seeking to optimize their performance management approaches.

This study aims to determine whether there is an influence of practical activities on students' critical thinking skills and scientific attitudes. The study was conducted in June-July 2025, the method used in this study is quantitative quasi-experimental. Sampling was carried out non-randomly using purposive sampling techniques. The sample of this study was 27 second semester students. The average value of critical thinking skills was 82.22 while the average value of the scientific attitude posttest was 67.48. The average value of critical thinking skills and scientific attitudes was obtained from the calculation of prerequisite tests, namely the normality test and the homogeneity test. Furthermore, a t-test was carried out is using the Paired Samples Test. The results of the Paired Samples Test were 0.000 because the p value <0.05, it can be concluded that there is an influence of discovery learning-based practical activities on students' critical thinking skills and scientific attitudes

This study aims to develop an entrepreneurship-based science module to enhance the creative thinking skills of students at SMPN 7 Seluma. The development model employed in this study was the ADDIE model. The research subjects were ninth-grade students of SMPN 7 Seluma, with samples consisting of students from classes IX C, IX D, and IX E. The research instruments included expert validation sheets, questionnaires, and pretest and posttest questions. The validation results from experts indicated that the developed entrepreneurship-based science module was valid. In the first trial phase, the module obtained a score of 95%, categorized as very practical. In the second trial phase, the module achieved a score of 96%, also categorized as very practical. The N-gain value of 0.779 in Trial I indicated a high level of improvement in students’ creative thinking skills, while the N-gain value of 0.797 in Trial II also showed a high level of improvement. Therefore, the developed entrepreneurship-based science module is proven to be valid, practical, and effective in enhancing students’ creative thinking skills and can be easily implemented in science learning

This research seeks to examine the innovative governance of police logistics to enhance the operational service efficiency at the Logistics Bureau of East Java Regional Police. The research context arises from the need to reform police logistics management to meet technological innovations and demands for public accountability. This research utilized a qualitative method featuring a case study approach, incorporating extensive interviews with logistics officers, operational personnel, and third-party providers, along with firsthand observations of digital logistics management systems. The results indicate that the adoption of the Integrated Logistic Management System (ILMS) and barcode tracking has improved transparency, distribution speed, and efficiency in operational budgets. Nonetheless, difficulties persist in human resource capability and interdepartmental collaboration. The dialogue suggests that these advancements correspond with adaptive governance theory, stressing bureaucratic adaptability in response to organizational shifts, and public service motivation, which underscores the importance of motivation and professionalism in enhancing the quality of public services. The research finds that digital innovation and performance-oriented assessment enhance the efficiency of police operational services. It suggests enhancing human resource capabilities, performance assessment systems, and collaboration among units to attain transparent, effective, and sustainable logistics management.

This research seeks to evaluate how asset and logistics management innovation enhances operational efficiency in the Household Division of the East Java Provincial Secretariat. The study focuses on the bureaucratic reform initiative aimed at attaining transparent, accountable, and effective asset management via digital transformation. The emphasis lies on how digital inventory systems, purchasing methods, and asset allocation aid in minimizing budget waste and improving efficiency. This research utilized a qualitative descriptive strategy through a case study technique. Data were gathered via extensive interviews, direct observation, and analysis of internal documents, subsequently undergoing data reduction and triangulation to confirm validity. The results indicate that the adoption of the e-inventory system has enhanced administrative efficiency by as much as 30%, but issues persist with data integration and employee digital skills. Additionally, the lack of a real-time public monitoring system restricts transparency in logistics management. The research advises enhancing employee training, creating cohesive SOPs, and adopting technology-driven assessment systems. These actions are anticipated to promote effective, efficient, and sustainable asset management in the East Java Provincial Secretariat.

This research aims to: (1) differentiated biology learning tools with ethnoscience content, (2) determine the practicality of differentiated biology learning tools with ethnoscience content and (3) determine the effectiveness of differentiated biology learning tools with etnoscience content in improving critical thinking skills and environemantal literacy of phase E student. This study is a development research using the Design and Development Research model, which adopts the ADDIE development model comprising five stages: (1) analysis, (2) design, (3) development, (4) implementation, and (5) evaluation. The research method used is the Quasi-Experimental Design with a Nonequivalent Control Group Design approach. Data analysis includes normality tests, Levene's homogeneity test, and the Normalized Gain Score (N-Gain Score) test. The limited trial involved 30 eleventh-grade students from SMA Negeri 1 Simpangkatis. The field trial involved tenth-grade students from the same school, consisting of 31 students in the experimental class and 30 students in the control class. The data collection instruments consisted of questionnaires to gather responses from experts, teachers, and students regarding the biology learning tools, as well as tests to measure students' critical thinking skills and environmental literacy. Instrument validity was ensured through content validation by subject matter experts and media experts. The practicality of the learning tools was evaluated based on feedback from teachers and students. The results of the study showed that: (1) the developed biology learning tools were rated as highly feasible by experts; (2) the tools were considered highly practical by both teachers and students; and (3) the tools were effective in improving students' critical thinking skills and environmental literacy. This effectiveness was supported by the average gain score analysis in the experimental class, which was 0.71 for critical thinking skills (high category) and 0.57 for environmental literacy (moderate category).

This study examines the phenomenon of creator teachers on TikTok as a form of digital professionalism that represents the integration of ethical values, aesthetics, and educational philosophy. The focus of the research lies in how teachers negotiate moral responsibility and creative expression in the algorithmic culture of social media. The aim of this research is to analyze the philosophical meaning behind teachers' digital representations as well as interpret how moral and aesthetic values are reflected in their pedagogical practices. The method used is digital netnography with four stages: online observation, digital documentation, audience interaction analysis, and researcher reflection. A total of eight teacher accounts were analyzed with a total of 80 videos using a categorization of themes that focused on ethics, aesthetics, and professionalism. The results showed that 62.5% of the content was educational and featured learning innovations, while the other 37.5% contained elements of entertainment and social interaction. High audience interaction shows public appreciation for the creativity and integrity of teachers. Popularity is not solely generated by algorithms, but by the appreciation of moral values and pedagogical beauty in the actions of teachers. Based on the framework of arete and phronesis from Aristotle and the concept of aesthetic experience from Dewey (1934), this study concludes that the digital professionalism of teachers is a form of reflective praxis that combines ethical responsibility and creative expression. This research makes a theoretical contribution by integrating digital netnography and educational philosophy, and shows that teachers in the digital era play the role of moral and creative agents who maintain the dignity of their profession in the algorithmic space.

This study investigates students’ perceptions of Smalltalk2Me, an artificial intelligence (AI)-powered conversational assistant designed to improve speaking skills in classroom learning. The main objective of this research is to explore how students perceive the tool’s effectiveness, usefulness, interactivity, and overall learning experience when using it for speaking practice. The research employed a qualitative descriptive method, with data collected through semi-structured interviews involving students who had used Smalltalk2Me as part of their English-speaking activities. The interview data were analyzed thematically to identify emerging patterns related to engagement, motivation, and skill development. The findings reveal that students view Smalltalk2Me as an effective and accessible tool that enhances speaking fluency and confidence since it allows practice anytime and anywhere. Students also appreciate its realistic conversation simulations and personalized feedback, which help them recognize pronunciation errors, improve vocabulary use, and refine sentence structure. Additionally, the AI assistant creates a supportive and low-anxiety learning environment, making learners more comfortable expressing themselves in English. Overall, the study concludes that Smalltalk2Me serves as a valuable supplementary tool for improving students’ speaking competence and fostering autonomous learning in technology-enhanced language classrooms.

This study aims to analyze the influence of the Problem-Based Learning (PBL) model assisted by e-LKPD on students’ problem-solving abilities and self-confidence in vocational high schools. Specifically, the objectives are: (1) to examine the simultaneous effect of the PBL model assisted by e-LKPD on both variables, (2) to determine its effect on problem-solving ability, and (3) to evaluate its effect on self-confidence. A quantitative approach with a quasi-experimental pretest–posttest control group design was applied. The population consisted of all 10th-grade students at SMK Negeri 1 Tarakan, while the sample was selected using purposive sampling, resulting in class X Marketing 1 (35 students) as the experimental group and class X Culinary 2 (34 students) as the control group. Research instruments included a problem-solving test and a self-confidence questionnaire. Hypothesis testing utilized Hotelling’s T² and independent sample t-tests. The findings showed that 97% of students in the experimental class met the Learning Objectives Mastery (KKTP), compared to only 18% in the control group. Improvement in the experimental group was categorized as high, whereas in the control group it was moderate. Self-confidence also increased significantly in the experimental group, with most students moving from low to high categories. Hotelling’s Trace (Fcount = 77.109, p < 0.001) and t-tests confirmed significant effects on both problem-solving (tcount = 11.657) and self-confidence (tcount = 8.140), proving that the PBL model assisted by e-LKPD effectively enhances students’ abilities and confidence.

Application of Multi-Layer Perceptron neural network to fault classification in high-voltage transmission lines is demonstrated in this paper. Different fault types on protected transmission line should be detected and classified rapidly and correctly. This paper presents the use of Discrete Wavelet Transform energy features combined with zero sequence current magnitude as input features for neural network classifier. The proposed method uses eight extracted features to learn hidden relationship in fault signal patterns. Using proposed approach, fault detection and classification of all 11 fault types could be achieved with high accuracy. Improved performance is experienced once the neural network is trained sufficiently with 1188 fault samples, thus performing correctly when faced with different system conditions. Results of performance studies show that proposed neural network-based classifier achieves 96.18% average accuracy, which demonstrates that it can improve the performance of conventional fault classification algorithms, which in turn can provide more efficient solutions in the management and protection of high voltage electrical systems.

The DC motor serves as the main drive of the vessel and is equipped with a rotary encoder that functions to regulate the movement of the sensor in measuring sediment levels. This rotary encoder is also used to monitor and represent the rotational speed of the DC motor. System testing was carried out by implementing a Fuzzy Logic Controller (FLC) algorithm to control the DC motor speed in moving the vessel, ensuring stable motion. This fuzzy logic–based approach is expected to improve accuracy and efficiency in sediment volume calculations, while also reducing potential errors that commonly occur in manual methods. Simulating motor speed control using the fuzzy logic algorithm in MATLAB, the best test results were achieved over several trials, with a rise time of 376.310 ms and an overshoot of 83.33%. Motor speed measurements using both a tachometer and Arduino produced consistent results, with an average relative error of 0.18%.

Mining activities in Indonesia result in significant environmental degradation, necessitating a robust legal framework for post-mining rehabilitation. However, enforcement is often hindered by normative overlaps between the Mining Law (No. 3/2020) and the Environmental Law (No. 32/2009), alongside a "supervisory vacuum" caused by recent centralization. This research evaluates the government's role in enforcing rehabilitation obligations and proposes a synchronized legal approach. Using a normative juridical method, the study identifies that authority fragmentation leads to a lack of accountability in reclamation fund management. Findings suggest that rehabilitation is frequently treated as a formal administrative procedure rather than a substantive ecological duty. Consequently, this study proposes a "Green Mining Governance" model that integrates environmental standards directly into mining permits (IUP) through a unified, inter-agency supervision system. This proposed framework integrates stringent environmental standards directly into the Mining Business Permit (IUP) and the annual Work Program and Budget (RKAB) through a unified, inter-agency supervision system. Such a reconstruction is essential to ensure that environmental restoration transcends formalistic requirements, evolving into a substantive legal obligation aimed at achieving long-term ecological justice and sustainable resource management.

The paradigm of the Indonesian criminal justice system is currently undergoing a significant shift from a retributive approach toward a restorative one. Criminal offenses resulting from negligence (culpa) present a unique case within this transition, as they lack malicious intent (mens rea in the form of dolus), yet often result in severe harm or loss of life. Despite its potential, the application of restorative justice for culpa offenses remains hindered by fragmented and sectoral regulations among law enforcement agencies, leading to legal uncertainty and inconsistent implementation. This research aims to analyze the urgency of restorative justice in negligence cases and proposes a model for its reconstruction. Using a normative juridical research method with statutory and conceptual approaches, this study examines existing regulations from the National Police, the Attorney General’s Office, and the Supreme Court. The findings indicate that the current framework requires a structural reconstruction through the synchronization of inter-institutional policies and the integration of restorative justice principles into the National Criminal Procedure Code (KUHAP). This reconstruction is essential to ensure a unified standard that balances legal certainty, the rehabilitation of the offender, and the restoration of the victim’s rights in unintentional crimes.

An answer to the worldwide need for solutions to food security, data fusion technology that combines climate data with satellite imagery greatly improves the accuracy of agricultural yield predictions; this study intends to examine the advancements, methods, and key contributions of this area. By sifting through 62 papers pulled from Scopus, this research employs the SLR methodology. Document type, data source, open access, subject area, and year of publication (2020–2024) are some of the categories filtered through by Boolean keywords in the selection process. To assess patterns in publications, the efficacy of machine learning models, and key contributions, bibliometric analysis was performed. An upward tendency in publication has been identified by the analysis, particularly beyond the year 2023. Integrating geographical and temporal data has been a great success with machine learning models like Random Forest, Random Forest, and Gradient Boosting. Data resolution, integration of data from several sources, and a real-time framework are still missing pieces to the puzzle when it comes to generalizing research outcomes. More complex data fusion approaches, multiregional datasets, and advanced machine learning models to back more accurate agricultural predictions are all things that this study notes as needing additional investigation in the future. To further innovate agricultural yield prediction, multidisciplinary collaboration is also crucial.

The digital era is characterized by the widespread use of gadgets in daily life. In this era, gadgets also play a crucial role in building Pancasila character. This study explores the role of gadgets in shaping Pancasila character in students, focusing on both the positive and negative impacts and the opportunities available. Using the Systematic Literature Review (SLR) method, the study draws on secondary data from various national journals. Data collection was conducted through observation and note-taking, with validation using triangulation. The findings reveal that gadgets significantly contribute to shaping intelligent students who embody Pancasila values in the digital era. The study identifies four key roles of gadgets: 1) providing access to information and knowledge, 2) fostering collaboration and communication, 3) supporting the development of digital skills, and 4) promoting the formation of Pancasila character. The study concludes that gadgets are instrumental in enhancing students' learning and character development in the digital age.

Introduction: Experiential marketing has become a growing trend in promotional activities by emphasizing personalization and active customer involvement. Preliminary observations indicate a decline in outpatient visits among patients with general insurance and non-JKN coverage in 2023, which may be influenced by a decrease in their intention to use outpatient services. This condition highlights the need for hospitals to implement experiential marketing strategies to enhance patient interest and experience. Objective: This study aims to empirically examine the influence of patient experience and service perception on the intention to use outpatient services, with Strategic Experiential Modules (SEMs) as an intervening variable. Methods: This quantitative research employs a causal design involving outpatient service users as the population. A non-probability sampling technique was used, yielding 249 respondents. Data were collected using a questionnaire and analyzed using Structural Equation Modeling (SEM) with AMOS software. Results: The findings reveal that patient experience and service perception simultaneously have a significant positive influence on the intention to use outpatient services through SEMs. Service perception directly shows a significant positive effect on both SEMs and intention to use outpatient services, while SEMs also significantly enhance usage intention. Service perception emerges as the dominant variable in increasing SEMs and usage intention, whereas patient experience has the weakest effect. Conclusion: Patient experience and service perception collectively influence the intention to use outpatient services with SEMs as an intervening variable. Strengthening Customer Relationship Management is essential by improving human resources and optimizing service asset.

Digital transformation in the Industry 4.0 era has accelerated changes in consumer behavior and intensified competition in online markets. Under heterogeneous and increasingly saturated conditions, mass-marketing approaches become less effective, making niche market strategies more relevant as a path to differentiation. This article aims to formulate a systematic framework for independently building a niche market in the digital era through a synthesis of academic literature and a practical social-media case. The study uses a conceptual literature review integrating niche marketing theory, niche success characteristics, and social media marketing dynamics. The review indicates that effective niche market development follows sequential stages: (1) identifying specific market needs/problems, (2) designing a relevant product/service solution, (3) sharpening the target into a clearly defined niche, (4) formulating a unique selling point (USP) and value proposition, (5) conducting small-scale validation through a portfolio/MVP, (6) executing social media marketing, (7) maintaining consistent content and digital branding, and (8) performing continuous adaptive evaluation. The @foodish_mks case reinforces that content consistency and social-media utilization act as key mechanisms linking digital marketing intensity to niche success. This article contributes a cross-sector niche-building roadmap aligned with algorithmic, community-based digital platforms, and proposes a testable hypothesis model (H1–H6) for future empirical validation.

This study explores the intellectual and thematic evolution of green sukuk research within Islamic sustainable finance from 2015 to 2025. Using a hybrid methodological design that integrates the PRISMA-guided Systematic Literature Review with Watase Uake network analysis, the study identifies 17 core Scopus-indexed articles that collectively define the field’s conceptual and empirical development. Results reveal a three-phase evolution: (1) a formative stage emphasizing ethical legitimacy and Sharia compliance; (2) a transitional phase integrating pricing efficiency, market risk, and policy frameworks; and (3) a maturity phase characterized by econometric modeling, behavioral-finance integration, and sustainability governance. Thematic clusters extracted from bibliometric mapping include financial performance and market dynamics, institutional legitimacy and policy frameworks, behavioral intention and investor psychology, and technological innovation and ESG disclosure. Despite methodological advancement, the literature remains geographically concentrated in Malaysia and Indonesia and exhibits theoretical fragmentation across behavioral, financial, and institutional models. Findings highlight key research gaps involving contradictory evidence on yield–risk relationships, inconsistent behavioral determinants of investment intention, and insufficient integration of moderating or mediating mechanisms. The study advances theoretical pluralism by connecting the Theory of Planned Behavior (TPB), Institutional and Legitimacy Theory, and Resource-Based View (RBV) into an integrated model explaining how legitimacy, behavior, and strategic capability jointly drive green sukuk adoption. Policy implications emphasize the need for harmonized regulation, behavioral incentives, and digital transparency to strengthen credibility and accelerate sustainable-finance transformation in line with SDGs 7 and 13.

This study examines the strategic role of job satisfaction in shaping organizational commitment in the context of companies by synthesizing empirical evidence published between 2016 and 2025. Although it has been extensively researched, findings related to the consistency and determinants of the relationship between job satisfaction and organizational commitment are still scattered and have not been integrated, thus requiring comprehensive mapping. Therefore, this study aims to identify empirical patterns, conceptual issues, and theoretical foundations that explain how job satisfaction contributes to the formation of organizational commitment. Using the PRISMA based Systematic Literature Review (SLR) method, 35 articles were selected through the stages of identification, screening, quality assessment, and thematic synthesis. The review results show that job satisfaction is consistently a major predictor of organizational commitment in various corporate sectors. These findings are consistent with theories such as Social Exchange Theory, Equity Theory, Herzberg's Two Factor Theory, and Job Demands Resources Model, which explain the cognitive and affective mechanisms of commitment formation. In addition, variables such as work environment, job involvement, work life balance, internal CSR, and HR practices were identified as mediators or moderators that strengthen this relationship. This study concludes that increasing job satisfaction is an important strategy for strengthening commitment, reducing turnover intentions, and improving organizational performance. This review contributes to an integrative understanding of empirical developments and theoretical perspectives, and provides recommendations for future research to expand the data base and consider cross-cultural dynamics in organizations.

The rapid growth of social media as a primary channel for information dissemination has triggered a significant surge in the distribution of hoaxes, potentially damaging social order, instigating mass disinformation, and threatening national security. This research aims to design an intelligent algorithm for hoax detection by integrating a critical thinking approach into Natural Language Processing (NLP)-based text processing. The algorithmic model is built using a combination of linguistic features, argument logic, and cognitive indicators such as the detection of unsubstantiated claims, identification of source bias, and evidence testing. To ensure accountability and transparency of the system, an Explainable AI (XAI) approach is applied so that classification results can be understood by non-technical users. The research results show that integrating critical thinking significantly improves detection accuracy to 93.1%, with an increase in precision and recall for detecting hoaxes based on emotional narratives. Beyond technical aspects, this model aligns with the mandate of Law of the Republic of Indonesia Number 11 of 2008 concerning Information and Electronic Transactions (ITE Law), particularly Article 28 paragraph (1), which prohibits the dissemination of false and misleading news that harms the public. Therefore, this system is not only scientifically relevant but also supports law enforcement and strengthens digital literacy in the post-truth era. These findings are expected to be a strategic contribution to the development of an ethical, critical, and responsible digital ecosystem.