Malikussaleh University (Indonesian: Universitas Malikussaleh, abbreviated UNIMAL) is an Indonesian public university in North Aceh Regency. Founded in 1969 as a Sharia academy, it branched into multiple subjects, which were integrated into the modern university in 1989. It was nationalized in 2001.With seven faculties, it is one of the four public universities (Perguruan Tinggi Negeri) in Aceh province.
Objectives: The present study investigated the therapeutic effects of a standardized capsule combination consisting of Channa striata, Phyllanthus niruri L., and Curcuma xanthorrhiza extracts (CCE) on biomarkers of kidney function, antioxidant status, and kidney histopathology in a high-fat diet (HFD) and alloxan-induced diabetic/nephrotoxic rat model. Materials and Methods: Male Wistar rats (n = 24) were divided into 4 groups: Control; HFD + alloxan treatment (diabetics/nephrotoxic); diabetics/nephrotoxic + CCE (49.5 mg/kg BW); diabetic/ nephrotoxic+ CCE + pioglitazone treatment group (1.35 mg/kg BW). Serum Cystatin C, superoxide dismutase (SOD) activity, and kidney histopathology were assessed at Day 60. Results: Model induction markedly increased blood glucose, HbA1c, and serum Cystatin C levels and decreased SOD activity (p < 0.001 vs controls). CCE significantly attenuated cystatin C by decreasing Cystatin C by 18.2% (p < 0.001) and restored SOD activity to 94.0% of control (p < 0.001). Histopathology showed marked improvements in glomerular hypertrophy, tubular injury, vascular congestion, and inflammatory infiltration (p < 0.001 vs model). CCE + pioglitazone showed comparable biochemical trends and enhanced histological preservation. Conclusions: CCE combination significantly attenuated diabetic/nephrotoxic-induced kidney injury by improving antioxidant defense and preserving kidney structure. This suggests therapeutic potential for managing metabolic kidney complications.
Nut shell is a natural filler widely used across various industries, including furniture, insulation, lightweight products, construction, packaging, and automotive, due to its superior performance and its contribution to industry sustainability. Natural fillers possess hydrophilic characteristics and exhibit heterogeneous behavior upon interaction with other materials, necessitating chemical, mechanical, ultrasonic, and hydrothermal treatments to enhance their interlocking and compatibility. The primary objective of this investigation is to assess the performance of composites, modification processes, fabrication methods, and the performance of different nut shells, to offer more comprehensive recommendations for industrial applications. The findings of this study unequivocally indicate that the modification, shape, and size of fillers, together with manufacturing factors, significantly influence the characterization, physical, mechanical, thermal, and tribological features, and degradation processes of nut shell-reinforced composites. In addition, this study provides the latest advances in understanding the degradation mechanisms of composites, including thermal, biological, and chemical mechanisms. Moreover, Life Cycle Assessment (LCA) indicates that using nut shells in composites significantly creates eco-friendly materials and innovative industries. Therefore, further studies must focus on improving compatibility with various matrix types and other materials, optimizing production parameters, and exploring the performance of nut shell-reinforced composites.
Cognitive diagnostic assessment (CDA) provides precise insights into students’ cognitive strengths and weaknesses. This systematic literature review analyzed 56 Scopus-indexed articles (2015-2025) using the theory-context-method framework. CDA is predominantly applied in mathematics, science, and language education, with significant contributions from China, USA, and Malaysia. While classical DINA and G-DINA models remain prevalent, recent studies integrate machine learning for Q-matrix validation. Quantitative approaches dominate (76.8%), revealing a gap between technical sophistication and practical implementation. The review emphasizes CDA’s potential for personalized learning and evidence-based policy, recommending future research to adopt longitudinal designs, expand interdisciplinary integration, and bridge diagnostic insights with pedagogical practice.
Digital transformation has become a strategic priority for enhancing the competitiveness and sustainability of Micro, Small, and Medium Enterprises (MSMEs). However, the implementation of digital transformation policies across various regions still shows a partial and uneven level of adoption. Previous research has generally examined structural barriers such as infrastructure limitations, regulations, and institutional capacity or cultural barriers such as low digital literacy, motivation, and resistance to change separately. As a result, the resulting policy recommendations have not been able to explain how these two dimensions interact with one another in policy implementation. This study aims to analyze the interaction of structural and cultural factors in the implementation of digital transformation policies for MSMEs and to develop an Adaptive Policy Model to support the digital transformation of MSMEs in Lhokseumawe City. The study employed a qualitative approach using the case study method, involving 47 purposively selected informants, including MSME operators, local government officials, academics, financial institutions, legislators, community members, consumers, and the media. Data were collected through in-depth interviews, observations, and document analysis, and were subsequently analyzed using NVivo 12. The research findings indicate that the implementation of digital transformation policies is influenced by a mutually reinforcing interaction between structural barriers including policy fragmentation, unequal access to digital infrastructure, weak institutional capacity, and poor interagency coordination and cultural barriers, such as low digital literacy, resistance to change, and weak motivation among MSME actors. These interactions have resulted in a digital adoption process that is partial, uneven, and unsustainable Based on these findings, this study developed an Adaptive Policy Model consisting of three mutually integrated stages policy set-up, policy design, and policy implementation, as well as monitoring and evaluation which emphasizes strengthening institutional coordination, long-term planning, interventions tailored to the capacity of MSMEs, inclusive implementation, and data-driven evaluation as a policy learning mechanism. These findings expand the study of public policy implementation through the development of an adaptive policy model that can serve as a reference for local governments in designing a more effective and sustainable digital transformation for MSMEs.
Fingerprint file integrity verification in driver license systems requires reliable cryptographic hash algorithms. MD5, currently widely deployed, has been deprecated by NIST (2008) due to demonstrated collision vulnerabilities, while SHA-256 offers enhanced security with potentially higher computational overhead. This study comprehensively compares MD5 and SHA-256 performance and security characteristics to provide evidence-based recommendations for biometric data integrity verification. We conducted empirical benchmarking using 1,000 real operational fingerprint files (BMP 8-bit grayscale, 512×512 pixels, 257 KB uniform) from Regional Police Traffic Directorate. Each file underwent 30 repeated trials with warm-up runs. Testing encompassed performance metrics (execution time, CPU usage, memory consumption), security evaluation (avalanche effect on 100 samples, collision detection), and grouping analysis by finger type using ANOVA (α=0.05). SHA-256 exhibited mean execution time of 2.28 ms, 48% slower than MD5's 1.54 ms (p<0.001), with CPU usage of 1.24% versus 0.98%, while memory consumption remained negligible. Avalanche effect approached ideal 50%: MD5 49.98%±4.43%, SHA-256 49.62%±3.21% (superior consistency). Zero collisions detected in 1,000 files. Grouping analysis revealed statistically significant differences between finger types (p<0.05) but with small effect size (η²<0.05) and negligible magnitude (<0.1 ms). For operational systems, SHA-256 is recommended based on acceptable performance overhead (<1 ms per file, 7.4 seconds daily for 10,000 transactions), superior security (no known attacks), regulatory compliance (NIST/ISO), more stable avalanche effect, and future-proofing capability.
