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The purpose of this study is to analyze the influence of Corporate Social Responsibility (CSR), Financial Distress, and Altman Z-Score on Dividend Decisions in automotive sector companies listed on the Indonesia Stock Exchange (IDX) for the 2020–2025 period. This study is motivated by fluctuations in the Dividend Payout Ratio (DPR) in the automotive sector, which indicates changes in company dividend policy due to economic conditions, financial performance, and non-financial factors that influence management decision-making. The research method used is a quantitative approach with a causal associative research type to examine the relationship between the independent and dependent variables. The study population consists of automotive sector companies listed on the IDX, while the sample was determined using a purposive sampling technique based on certain criteria. Research data were obtained from annual reports and company financial statements for the 2020–2025 period. Data analysis was carried out using the Dividend Payout Ratio (DPR) as a proxy for dividend decisions and statistical testing to determine the effect of CSR, Financial Distress, and Altman Z-Score on company dividend, the data were processed using SPSS.

Abstract. PT XYZ, a wooden furniture manufacturing company, served as the research site for this study which applied the Theory of Constraints (TOC) method to analyze production performance and identify bottlenecks. The company faces capacity imbalances between workstations, resulting in production targets that have not been achieved optimally. Data collection involved direct observation and interviews with related parties in the production area. The analysis was conducted by comparing the required capacity with the available capacity at each production workstation. The findings reveal that solid processing, machining, sanding, assembling, painting, and packing have sufficient available capacities to meet production requirements, thus categorized as non-bottleneck processes. In contrast, the panel processing station is identified as the main bottleneck due to its highest workload among all processes. By implementing the Theory of Constraints, the company can identify major constraints and establish improvement priorities to enhance production flow smoothness. It is expected that improvements in bottleneck processes will increase production efficiency, balance capacity among workstations, and support more optimal achievement of production targets. Keywords: bottleneck; capacity; manufacturing; production performance; theory of constraints   Abstrak. PT XYZ sebuah perusahaan manufaktur furnitur kayu, menjadi lokasi penelitian ini yang menggunakan metode Theory of Constraints (TOC) untuk menganalisis kinerja produksi dan mengidentifikasi bottleneck. Perusahaan menghadapi ketidakseimbangan kapasitas antar stasiun kerja yang menyebabkan target produksi belum terdengar secara optimal. Pengumpulan data meliputi observasi langsung dan wawancara dengan pihak terkait di area produksi. Analisis dilaksanakan dengan membandingkan kapasitas yang dibutuhkan terhadap kapasitas yang tersedia pada setiap stasiun kerja produksi. Hasil penelitian menunjukkan bahwa proses pembahanan solid, machining, sanding, assembling, painting, dan packing memiliki kapasitas yang tersedia yang masih mampu memenuhi kebutuhan produksi, sehingga termasuk kategori non-bottleneck. Sebaliknya, stasiun kerja pembahanan panel diidentifikasi sebagai bottleneck utama karena memiliki tingkat beban kerja tertinggi di antara seluruh proses. Dengan penerapan Theory of Constraints, perusahaan dapat mengidentifikasi kendala utama dan menentukan prioritas perbaikan untuk meningkatkan kelancaran aliran produksi. Diharapkan perbaikan pada proses bottleneck dapat meningkatkan efisiensi produksi, menyeimbangkan kapasitas antar stasiun kerja, serta mendukung pencapaian target output perusahaan secara lebih optimal. Kata kunci: bottleneck; kapasitas; kinerja produksi; manufaktur; theory of constraints

This study aims to analyze the management of young preacher (dai cilik) training in developing students’ preaching skills at SD IT Al-Washliyah Kelambir Lima Medan using a management function approach (*planning, organizing, actuating, and controlling*). This study employed a descriptive qualitative method, with data collected through in-depth interviews, participant observation, and documentation. The research informants consisted of the principal and teachers responsible for the young preacher training program. The collected data were analyzed systematically to describe the implementation of management functions in the young preacher training activities and their contribution to the development of students’ preaching skills. The results showed that planning was carried out through the development of a practice-based preaching curriculum, organizing was implemented through task allocation and regular scheduling, implementation focused on *public speaking* practice, sermon material preparation, and moral development, while evaluation was conducted periodically through student performance assessments. The implementation of this systematic training management contributed to the improvement of students’ preaching skills in cognitive, affective, and psychomotor aspects. These findings indicate that management functions applied in a structured manner play a strategic role in supporting the development of students’ preaching competencies at the elementary school level. Furthermore, continuous training provides opportunities for students to enhance their self-confidence, communication skills, and readiness to effectively deliver Islamic preaching messages

Abstract. This research aims to analyze the effectiveness and reliability of production machines in the process of making public street lighting poles (PJU) at PT. XYZ The main problem faced by the company is high machine downtime so that production targets are not achieved. Therefore, a method is needed that is able to measure machine effectiveness as a whole and identify the main causes of production losses. The method applied includes Overall Equipment Effectiveness (OEE) to measure machine effectiveness based on three components, namely availability, performance and quality. The Total Productive Maintenance (TPM) approach is used to identify factors causing low effectiveness through Six Big Losses analysis. Apart from that, Mean Time To Repair (MTTR) and Mean Time Between Failure (MTBF) are calculated to determine the level of machine reliability. The data used includes machine working hours, downtime, operating time, production quantities, defective products, as well as machine damage and repair data. The analysis results are expected to show the level of machine effectiveness and identify the dominant factors causing downtime. Based on these results, improvement proposals are prepared to reduce downtime, increase machine reliability and improve production productivity Keywords: Overall Equipment Effectiveness (OEE), Total Productive Maintenance (TPM), Six Big Losses, Downtime, Efektivitas   Abstrak. Penelitian ini bertujuan untuk menganalisis efektivitas dan keandalan mesin produksi pada proses pembuatan tiang penerangan jalan umum (PJU) di PT. XYZ Permasalahan utama yang dihadapi perusahaan adalah downtime mesin yang tinggi sehingga target produksi tidak tercapai. Oleh karena itu, diperlukan metode yang mampu mengukur efektivitas mesin secara menyeluruh dan mengidentifikasi penyebab utama kerugian produksi. Metode yang diterapkan meliputi Overall Equipment Effectiveness (OEE) untuk mengukur efektivitas mesin berdasarkan tiga komponen, yaitu availability, performance, dan quality. Pendekatan Total Productive Maintenance (TPM) digunakan untuk mengidentifikasi faktor penyebab rendahnya efektivitas melalui analisis Six Big Losses. Selain itu, dilakukan perhitungan Mean Time To Repair (MTTR) dan Mean Time Between Failure (MTBF) untuk mengetahui tingkat keandalan mesin. Data yang digunakan mencakup jam kerja mesin, downtime, waktu operasi, jumlah produksi, produk cacat, serta data kerusakan dan perbaikan mesin. Hasil analisis diharapkan dapat menunjukkan tingkat efektivitas mesin dan mengidentifikasi faktor dominan penyebab downtime. Berdasarkan hasil tersebut, disusun usulan perbaikan untuk mengurangi downtime, meningkatkan keandalan mesin, dan memperbaiki produktivitas produksi Kata kunci: Overall Equipment Effectiveness (OEE), Total Productive Maintenance (TPM), Six Big Losses, Downtime Mesin, Efektivitas Mesin

Pressure sensitive labels (PSLs) made of polyethylene (PE) white are widely used in the packaging industry due to their flexibility, moisture resistance, and ease of application on various substrates. This study aimed to examine the effect of glossy and matte lamination on the tensile strength and color difference (ΔE) of PE white PSLs. An experimental method was employed, with tensile testing conducted using a universal testing machine (UTM) in accordance with ASTM standards and color measurement performed using a spectrodensitometer based on the CIE Lab system. The samples were divided into three treatment groups, namely no lamination, glossy lamination, and matte lamination, with ink coverage controlled at two design conditions, full ink and minim ink. The results indicated that lamination type significantly affected both the mechanical and visual characteristics of the labels. In the tensile strength test, the highest mean value was obtained by one treatment group, indicating superior resistance to tensile loading. In terms of color stability, higher ΔE values indicated greater color change and lower lightfastness, whereas lower ΔE values reflected better color retention. Overall, the findings show that the combination of lamination type and ink coverage influences the performance of PE white PSLs in both mechanical strength and color stability.

This study aims to evaluate the level of sharia compliance in musyarakah contracts within micro-enterprise financing. Musyarakah is a partnership-based financing contract that emphasizes cooperation, profit-sharing based on an agreed ratio (nisbah), and proportional risk sharing in accordance with each party’s capital contribution. In practice, the implementation of musyarakah contracts in micro-enterprise financing must be assessed against the Fatwa of the National Sharia Council–Indonesian Ulema Council (DSN-MUI), principles of fiqh muamalah, and Islamic banking regulatory frameworks in Indonesia. The findings show that the implementation of musyarakah working capital financing in Islamic banking is generally in the good category. However, two non-compliance issues with sharia principles were identified. First, there is an imbalance in work participation, where the business is fully managed by the customer while the bank only provides supervision and guidance without active involvement, whereas active participation of partners is a fundamental principle of musyarakah. Second, there is an element of riba due to the use of a fixed profit-sharing scheme, even though profits in musyarakah should be uncertain and based on actual business performance. The study implies that Islamic banks need to improve musyarakah implementation to ensure full compliance with DSN-MUI fatwas, particularly in terms of active bank participation and non-fixed profit-sharing arrangements. Properly implemented, musyarakah financing can strengthen micro and small enterprises by promoting justice-based and risk-sharing economic cooperation.

The quality of life and well-being of women in Indonesia can be measured through the Female Life Expectancy indicator. Data on Female Life Expectancy from 2022 to 2024 shows a nationally positive trend; however, a significant disparity persists across provinces, particularly between the Western and Eastern regions of Indonesia. The nation still faces challenges in ensuring an equitable quality of life for women, as evidenced by the national Female Life Expectancy (FLE) in 2024 at 74.21 years, which remains lower than ASEAN counterparts such as Singapore at 83.86 years. Furthermore, regional imbalances are reflected in the performance gap between D.I. Yogyakarta (77.4 years) and West Sulawesi (68.28 years). This study aims to analyze the effects of Women's Income Contribution, Access to Clean Water, the Number of Families Receiving Social Assistance, and Women's Mean Years of Schooling on Female Life Expectancy in Indonesia during the 2022–2024 period. The estimation method applied in this research is the Fixed Effect Model (FEM) via a quantitative panel data regression approach, spanning an observation area of 33 provinces (n=99). Based on the analysis, Female Life Expectancy is proven to be positively and significantly influenced by Women's Mean Years of Schooling and Access to Clean Water. These findings indicate that human resource quality and environmental conditions serve as dominant factors in driving up Female Life Expectancy. Therefore, government policy interventions should ideally focus on expanding educational access for women and ensuring the equitable distribution of clean water infrastructure.

This study investigates the role of Baitul Maal wa Tamwil (BMT) in empowering Micro, Small, and Medium Enterprises (MSMEs) through the integration of Maqashid Sharia principles and financial inclusion strategies. Despite the strategic importance of MSMEs in economic growth and poverty reduction, many face challenges in accessing formal financial services. BMT, with its dual function of social (maal) and commercial (tamwil) activities, offers a unique platform to bridge this gap. Using a qualitative systematic literature review guided by PRISMA, this study analyzes 30 relevant articles to examine BMT operational models, implementation of Maqashid Sharia objectives, financial inclusion practices, and their impact on MSME performance. Findings indicate that BMT effectively supports MSMEs in capital access, income generation, and business resilience, but inconsistencies in balancing social and commercial objectives limit. holistic empowerment. Integrating Maqashid Sharia principles enhances ethical and sustainable outcomes, while financial inclusion expands outreach to underserved entrepreneurs. Optimization strategies, including strengthening institutional capacity, combining financial and non-financial support, and context-specific interventions, are essential for maximizing BMT effectiveness. This study contributes a comprehensive framework linking ethical, financial, and empowerment dimensions, offering practical guidance for policymakers and BMT managers in promoting inclusive and sustainable MSME development.

The development of digital services by BPJS Ketenagakerjaan through the JMO (Jamsostek Mobile) application has triggered a surge in large-scale and unstructured user reviews on the Google Play Store, thereby complicating manual analysis and conventional sentiment analysis in accurately identifying specific issues. This research aims to implement the Aspect-Based Sentiment Analysis (ABSA) method to granularly evaluate JMO application reviews based on specific aspects, while simultaneously addressing class imbalance and computational efficiency issues. The proposed method combines the pretrained IndoBERT model as a contextual feature extractor, the SMOTE technique to balance the training data, and an artificial neural network (Neural Network) as the classification layer without performing full fine-tuning. The dataset used consists of 90,268 unique reviews categorized into five main aspects through keyword matching, namely General Satisfaction/Complaints, Performance & Stability, Service & Support, Feature Quality, and UI/UX, with initial lexicon-based labeling using the InSet Lexicon. The research results indicate that the proposed model successfully achieves highly optimal performance with an accuracy rate of 91.81% and a weighted F1-score of 92%. Furthermore, the implementation of SMOTE proved effective in enhancing model reliability on the minority class (negative sentiment), achieving an F1-score of 89%. The implications of this research contribute an accurate and efficient aspect-based sentiment analysis framework for developers, and serve as a strategic evaluation tool for BPJS Ketenagakerjaan in mapping specific user complaints to accelerate continuous improvements in the performance, stability, and service quality of the JMO application.

Conflict is an inevitable phenomenon in educational environments due to differences in characteristics, interests, perceptions, and goals among school members. If not managed properly, conflict can disrupt the learning process, weaken social relationships, and negatively affect educational quality. This study aims to analyze the role of collaborative conflict management in improving the quality of education in madrasahs and schools. The research employed a qualitative approach using a library research method by reviewing various books, scientific journals, and relevant literature related to conflict management and education. The findings indicate that collaborative conflict management, implemented through effective communication, deliberation, discussion, negotiation, and cooperation, can facilitate constructive and sustainable conflict resolution. Furthermore, the application of collaborative conflict management contributes to strengthening cooperation among school members, creating a harmonious and conducive learning environment, and improving teacher performance as well as student learning outcomes. School principals play a strategic role as mediators and facilitators in guiding conflict resolution processes fairly and participatively. Therefore, collaborative conflict management can serve as an effective strategy for enhancing educational quality and fostering a positive educational climate in madrasahs and schools.

Aerobic capacity, commonly measured by maximal oxygen uptake (VO₂max), is a key indicator of physical fitness and athletic performance, particularly in endurance sports. Recent attention has focused on the role of respiratory muscle function in supporting exercise performance, as respiratory muscle fatigue during high-intensity or prolonged activity may reduce ventilatory efficiency and exercise tolerance. This literature review aims to examine current evidence regarding the effects of Respiratory Muscle Training (RMT), including Inspiratory Muscle Training (IMT), on aerobic capacity in athletes. Relevant studies were identified through electronic databases such as PubMed, Scopus, and Google Scholar using keywords related to respiratory muscle training, VO₂max, and athletes. The reviewed studies generally reported improvements in inspiratory muscle strength, reduced respiratory muscle fatigue, and enhanced ventilatory efficiency following RMT interventions. These physiological adaptations may contribute to better exercise tolerance and overall athletic performance. However, evidence regarding direct improvements in VO₂max remains inconsistent across studies. The findings suggest that RMT can be used as a complementary strategy alongside conventional training programs to support aerobic performance. In addition, improved respiratory muscle function may provide benefits in health promotion and rehabilitation by reducing dyspnea and increasing exercise tolerance. Further well-designed studies are needed to clarify the extent of RMT’s contribution to improving VO₂max in athletic populations.

Aerobic capacity, commonly measured by maximal oxygen uptake (VO₂max), is a key indicator of physical fitness and athletic performance, particularly in endurance sports. Recent attention has focused on the role of respiratory muscle function in supporting exercise performance, as respiratory muscle fatigue during high-intensity or prolonged activity may reduce ventilatory efficiency and exercise tolerance. This literature review aims to examine current evidence regarding the effects of Respiratory Muscle Training (RMT), including Inspiratory Muscle Training (IMT), on aerobic capacity in athletes. Relevant studies were identified through electronic databases such as PubMed, Scopus, and Google Scholar using keywords related to respiratory muscle training, VO₂max, and athletes. The reviewed studies generally reported improvements in inspiratory muscle strength, reduced respiratory muscle fatigue, and enhanced ventilatory efficiency following RMT interventions. These physiological adaptations may contribute to better exercise tolerance and overall athletic performance. However, evidence regarding direct improvements in VO₂max remains inconsistent across studies. The findings suggest that RMT can be used as a complementary strategy alongside conventional training programs to support aerobic performance. In addition, improved respiratory muscle function may provide benefits in health promotion and rehabilitation by reducing dyspnea and increasing exercise tolerance. Further well-designed studies are needed to clarify the extent of RMT’s contribution to improving VO₂max in athletic populations.

This study aims to analyze the effect of homework load and extended study hours on students’ learning stress levels. The background of this research is based on increasing academic demands that may affect students’ psychological conditions. This study employs a qualitative approach with data collected through observation and interviews. The results indicate that excessive homework load and prolonged study duration significantly contribute to higher levels of learning stress. Students tend to experience physical and mental fatigue, decreased motivation, and difficulty managing time between study and rest. In addition, pressure to achieve high academic performance further exacerbates stress levels. Other factors such as lack of environmental support and less varied teaching methods also influence students’ stress. Furthermore, students often report feelings of anxiety and emotional exhaustion when academic tasks accumulate without adequate rest periods. This condition not only affects their psychological well-being but also reduces concentration and learning effectiveness in the classroom. Therefore, balanced learning load management, appropriate task distribution, and more effective and humanistic teaching strategies are needed to reduce learning stress and improve the quality of education. Schools and educators are encouraged to consider students’ cognitive capacity and mental health in designing assignments and study schedules to create a more supportive learning environment.

Agentic artificial intelligence (AI) systems capable of autonomous goal-directed behavior, multi-step planning, tool use, multi-agent coordination, and iterative self-correction represent a transition from passive clinical AI tools toward systems that can participate in complex healthcare workflows. However, empirical evidence remains fragmented across clinical decision support, patient monitoring, and administrative applications, and no systematic synthesis has evaluated which agentic principles have been technically demonstrated and which have accumulated sufficient evidence to support responsible clinical deployment. We conducted a PRISMA-informed systematic review of peer-reviewed empirical studies published between January 2025 and April 2026. Searches across five bibliographic databases and Google Scholar, supplemented by citation tracking, identified 443 unique records for screening, of which 25 met the predefined PICOS and quality appraisal criteria. Evidence was synthesized using an evidence-informed seven-principle framework derived from the integration of agentic AI, clinical AI, and healthcare governance literature. This framework provides a structured lens for examining how agentic principles are evaluated individually and in combination, enabling a deployment-readiness perspective that extends beyond capability-focused assessments alone. The evidence base was concentrated on technical capability principles, whereas human oversight, safety, compliance, and equity-related evaluation received comparatively limited attention. Most studies remained at the laboratory, benchmark, or proof-of-concept stage, and none reported demographic-stratified performance outcomes. Overall, the findings suggest a structural asymmetry in agentic healthcare AI: empirical research is advancing agentic capabilities more rapidly than it is generating evidence for the oversight, safety, equity, and governance mechanisms required for responsible clinical translation.

Document-level sentiment analysis assigns a single polarity label to an entire review, often obscuring opinion diversity within multi-sentence submissions. This limitation is particularly evident in reviews of multi-service platforms, where users frequently express heterogeneous opinions toward different aspects of the platform in the same review. To address this challenge, this study proposes a sentence-level sentiment analysis framework for Indonesian Gojek app reviews collected from the Google Play Store. The proposed framework introduces a two-stage segmentation strategy that combines punctuation-aware rules with conjunction-aware splitting based on coordinating and adversative conjunctions (e.g., tapi [but], padahal [even though]) to identify opinion boundaries and decompose mixed-sentiment reviews into independently classifiable sentence units. A total of 14,730 raw reviews collected between May and July 2025 were subjected to data cleaning and quality filtering, resulting in 7,187 valid reviews that were further segmented into 14,187 sentence-level instances. Each instance was manually annotated by three annotators using a four-class labeling scheme consisting of app-positive, app-negative, app-neutral, and service categories. Sentiment-level inter-annotator agreement, computed on the subset of instances unanimously categorized as app-related by all three annotators (n = 4,384), achieved substantial agreement (Fleiss'  = 0.636). Hyperparameter optimization was conducted using Optuna with the Tree-structured Parzen Estimator (TPE) sampler across four experimental scenarios. The best performance was achieved by IndoBERTweet under Stratified K-Fold evaluation, attaining an accuracy of 0.751 and a macro F1-score of 0.729, outperforming all IndoBERT configurations. The results demonstrate the effectiveness of domain-adaptive pre-training on informal Indonesian text and highlight the value of conjunction-aware segmentation for preserving fine-grained opinion structures in mixed-sentiment reviews. These findings suggest that domain-aligned language representations provide a practical and effective solution for sentence-level sentiment analysis of Indonesian app reviews.

This study examines human resource competence in improving financial management at the Public Service Agency of Gorontalo State University, a public higher education institution that operates under a flexible financial management model while remaining accountable for public funds. The main problem addressed is how financial management personnel translate regulatory knowledge, technical skills, and professional attitudes into efficient, effective, and accountable financial governance. This study aims to analyze the competence of financial management personnel and explain its contribution to strengthening institutional financial management. A qualitative descriptive approach was employed through interviews, observation, and document analysis involving bureau leaders, financial work team officials, treasurers, and financial managers across relevant work units. The findings show that knowledge competence is reflected in personnel understanding of regulations, policies, financial systems, budgeting procedures, reporting requirements, and the linkage between budget and institutional performance. Skills competence is demonstrated through financial administration, transaction recording, document verification, use of financial information systems, reconciliation, reporting, and preparation of accountability documents. Attitudinal competence appears in professionalism, compliance, integrity, prudence, responsibility, and openness to evaluation and audit. Financial management has been directed toward performance-based planning, expenditure control, budget realization monitoring, reporting, supervision, and audit follow-up. However, challenges remain in regulatory adaptation, system integration, data quality, document timeliness, account-code accuracy, inter-unit coordination, and consistency of audit follow-up. The study concludes that strengthening human resource competence is essential for improving financial management that is efficient, effective, accountable, and performance-oriented in public university financial governance.

Discrimination in the workplace is a problem that can hinder the creation of a fair and inclusive work environment. Discrimination can take the form of differential treatment of employees based on gender, race, religion, disability, sexual orientation, or other factors unrelated to individual performance and competence. To address this issue, the law plays a crucial role in providing employee protection to ensure equality and non-discrimination in the workplace. Various legal instruments, both national and international, regulate employee protection from discrimination, including the Employment Law, the Human Rights Law, and conventions issued by the International Labour Organization (ILO). However, the effective implementation of these regulations remains a challenge, particularly in terms of implementation, enforcement, and employee awareness of their rights. This study aims to analyze the role of law in protecting employees from discrimination in the workplace by examining applicable regulations and the challenges in their implementation. The research method used is a normative juridical method, which focuses on the study of relevant laws and legal principles. The analysis is conducted on national legal provisions and international legal instruments as references for protecting workers from discrimination. Furthermore, this study identifies barriers to legal implementation and offers recommendations to improve the effectiveness of legal protection for employees. This analysis is expected to provide insight into the urgency of regulatory reform and strengthening so that the law can play an optimal role in creating a fairer and more discrimination-free work environment.

Python programming has become a fundamental competence in the digital era, yet students often struggle to transform algorithmic logic into functional code. This gap between conceptual understanding and practical implementation skills requires a thorough investigation into learning challenges within the Industrial Informatics Engineering Technology (TRIN) program at Politeknik Manufaktur Bandung. Grounded in Bloom's Revised Taxonomy and Cognitive Load Theory, this descriptive quantitative study utilized a Likert-scale questionnaire and an objective comprehension test administered to 87 third-year students. Data were analyzed using descriptive statistics to map performance across three aspects: conceptual understanding, syntactic comprehension, and implementation ability. Results indicate the conceptual aspect achieved the highest average of 4.15, followed by syntax at 3.56 and implementation at 3.54, with objective test accuracy rates of 76.09%, 65.52%, and 67.36%, respectively. Major obstacles identified include difficulties with looping, debugging, and comparison operators. Therefore, enhanced structured practice and Project-Based Learning approaches are recommended to strengthen students' implementation competencies.

Batik motif classification has attracted growing attention in visual computing due to its role in cultural heritage preservation, textile informatics, museum documentation, and automated cataloging. Although many studies report high classification accuracy, robustness under real-world acquisition conditions remains insufficiently understood. Batik images are frequently affected by illumination variation, blur, folds, watermark overlays, wearable deformation, scale inconsistency, and background clutter, creating challenges that extend beyond conventional image-noise assumptions. Existing studies largely focus on improving classification performance, while the interactions among acquisition variability, feature representation, evaluation practice, and deployment constraints remain fragmented. This systematic literature review addresses this gap by synthesizing batik classification research through a robustness-aware perspective. Using query expansion, backward and forward citation chaining, relevance screening, and thematic coding, 116 candidate records were identified, resulting in 50 highly relevant studies for detailed analysis. The review reveals that robustness is shaped less by denoising alone than by the combined effects of acquisition conditions, representation design, evaluation realism, and deployment context. Handcrafted descriptors remain competitive for small datasets and structured motifs due to their data efficiency and interpretability, whereas deep learning models achieve the highest reported accuracy when supported by sufficient data diversity and realistic augmentation. Hybrid representations emerge as the most consistently balanced approach, combining local texture stability with higher-level abstraction across heterogeneous acquisition settings. The review further identifies recurring robustness failure patterns, including background dependency, illumination instability, motif-scale inconsistency, wearable deformation, and source-shift vulnerability. Based on these findings, a robustness-oriented research agenda is proposed, emphasizing cross-acquisition evaluation, representation-stability analysis, batik-specific robustness benchmarks, acquisition-aware augmentation, and deployable lightweight or hybrid architectures. The study contributes a domain-specific synthesis that reframes batik motif classification from an accuracy-centric task toward a robustness-aware visual recognition problem.

This study examines the role of the creative economy in enhancing sustainable tourism potential in Pampang Cultural Village, Samarinda, Indonesia, and identifies strategic priorities for its development. Pampang Cultural Village is recognized for its rich cultural heritage preserved by the Dayak Kenyah community, which serves as a valuable tourism asset. Despite this potential, the contribution of creative economy activities to tourism development has not been fully optimized. Therefore, a comprehensive analysis is needed to formulate effective development strategies. This research employs a mixed qualitative–quantitative approach using the SWOT-AHP method. SWOT analysis is utilized to identify internal strengths and weaknesses as well as external opportunities and threats affecting creative economy development. Subsequently, the Analytic Hierarchy Process (AHP) is applied to determine the priority level of each strategic factor and alternative strategy. The findings indicate that the village possesses significant creative economy potential in cultural performances, handicrafts, culinary products, traditional fashion, and cultural souvenirs. Cultural authenticity emerges as the primary strength, while limited innovation capacity and digital marketing skills remain the major weaknesses. The results further reveal that the highest-priority strategy is the development of innovative creative tourism products rooted in Dayak Kenyah cultural heritage while preserving cultural authenticity. This strategy should be supported by digital promotion, human resource capacity building, stakeholder collaboration, and improvements in tourism infrastructure to achieve sustainable tourism development.