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The development of modern biotechnology has brought fundamental changes to the life sciences through the application of molecular biology, genetic engineering, and bioinformatics techniques. This article aims to examine the transformation of life sciences through modern biotechnology approaches and its impact on health, agriculture, the environment, and industry. The method used is a descriptive-analytical literature review based on international journal sources and relevant scientific publications. The results of the study indicate that technologies such as CRISPR-Cas9 enable precise gene editing for genetic disease therapy, while the mRNA vaccine platforms developed by Pfizer and Moderna demonstrate the acceleration of biomedical innovation in response to the global pandemic. In the agricultural sector, genetic engineering increases crop productivity and resilience, while in the environmental sector, biotechnology supports environmentally friendly bioremediation processes. However, ethical and regulatory challenges remain important concerns in its implementation. In conclusion, modern biotechnology plays a key role as a catalyst for sustainable, innovation-driven transformation in the life sciences.

The discharge of surfactant-laden wastewater from the rapidly expanding laundry industry poses significant environmental risks, especially in densely populated urban areas. While constructed wetlands (CWs) and Eco-Enzyme technology have shown promise for surfactant remediation, their standalone application requires long hydraulic retention times (HRTs), limiting practical implementation. This study evaluated the efficacy of a novel integrated system combining a subsurface constructed wetland (SSFCW) with fruit peel-derived Eco-Enzyme to treat synthetic laundry wastewater. Over a 6-day treatment period, the combined system achieved a remarkable surfactant removal efficiency of 99.63%, reducing the concentration from 225 mg/L to 0.835 mg/L—well below the regulatory threshold of 3 mg/L. The synergistic degradation mechanism involves enzymatic hydrolysis via Eco-Enzyme lipase and protease activity, complemented by microbial mineralization in the wetland rhizosphere. This system maintains optimal environmental conditions, with a stable pH of 6.85-7.32 and a temperature of 30.9-35.2°C, supporting robust biological activity. These findings demonstrate that the integrated Eco-Enzyme/SSFCW system overcomes the limitations of conventional HRT approaches, offering a highly efficient, sustainable, and practical decentralized wastewater treatment solution for the laundry industry.  

The increasing demand for paper has led to a shortage of wood-based raw materials, thus requiring environmentally friendly alternatives. This study aims to analyze the physical, mechanical, and morphological characteristics of paper made from cassava peels (Manihot esculenta Crantz) and oil palm fruit fibers (Elaeis guineensis Jacq.) as eco-friendly paper raw materials. The research method involved pulp preparation through delignification using 3.5% HNO₃ and 3% NaOH, bleaching with 10% H₂O₂, paper sheet formation with varying compositions (A = 70:30, B = 50:50, C = 30:70, D = 10:90), followed by grammage testing and tensile strain testing. The results showed that the grammage values ranged between 96.3–99.7 g/m², while tensile strain ranged between 2.6–4.4%. The study concluded that the best composition was found in sample C (30% cassava peel : 70% palm fiber) with a grammage of 98.5 g/m² and tensile strain of 3.2%. The implication of this study is that cassava peel and palm fiber waste have the potential to serve as alternative paper raw materials that meet the quality standards of A-grade printing paper (SNI 7274:2008), while also supporting the reduction of dependence on wood.

This study discusses the implementation of the Self-Directed Learning Programme by integrating Learning Outcomes (CP), Learning Objectives (TP), and Learning Objective Processes (ATP) to enhance teaching quality and teacher professionalism. Using a library research method, this study analyses relevant scientific literature to understand the relationship between the integration of the three components of the education programme and classroom teaching practices. The research findings indicate that teachers still encounter challenges in understanding and integrating CP, TP, and ATP, particularly in planning, implementing teaching strategies, and conducting authentic assessments. However, when this integration is well executed, the teaching process becomes more purposeful, flexible and responsive to students' needs. Furthermore, integrating CP–TP–ATP has been shown to strengthen teachers' professionalism by enhancing their understanding of the curriculum, their ability to design learning activities, and their capacity to conduct competency-based assessment. This study confirms that the successful implementation of the Free Education Programme depends heavily on teachers' ability to understand the curriculum's structure and to integrate these three components consistently. Therefore, training, supporting, and developing teachers' competencies is an important requirement for the effective and sustainable implementation of the Liberal Education Programme.

Chili pepper (Capsicum frutescent L.) is known as one of the high sources of vitamin C, which acts as an important natural antioxidant for human health because the body is unable to produce its own. This study aims to analyse vitamin C levels in chili pepper using the iodometric titration method quantitatively by taking a 5 gram sample of chili pepper and titrating it using 0,1 N iodine solution. The analysis results showed that the vitamin C content obtained was 0,0704% or equivalent to 70,4 mg/100g. This value is higher than some research results. This value is higher than some previous research results on fruits and chillies from other regions. This finding shows that chilli pepper has great potential as a source of vitamin C in supporting the fulfilment of people’s daily nutrition. In addition, the iodometric titration method is proven to be effective and efficient to be used in the analysis of vitamin C in foodstuffs. Therefore, chili pepper consumption can be a simple strategy in improving nutritional and preventing disease related to vitamin C deficiency.

This research extends the previous work of Tsaqila, Winiarti, and Widaningrum (2024), who applied the Complex Proportional Assessment (COPRAS) method within a decision support system for supermarket branch location selection. Unlike the prior study, which focused on Ponorogo through a web-based framework, this study expands the implementation of COPRAS to the Medan Area, Medan Kota, Medan Polonia, dan Medan Maimun districts, adapting it to local urban, social, and economic characteristics. The main objective is to identify the most strategic site for a new supermarket by analyzing multiple criteria, including land cost, population density, accessibility, safety, cleanliness, and disaster risk. Data were collected from both field surveys and official government publications. The findings reveal that the COPRAS method provides reliable and objective assessments among the evaluated alternatives, with Medan Area emerging as the most suitable location for supermarket development. Overall, this study broadens the practical scope of the COPRAS method in a different regional context and reinforces its reliability and adaptability as a multi-criteria decision-making tool in the modern retail industry.

PT. Tirta Fresindo Jaya, specifically its Pasuruan plant as the producer of Pucuk Harum Tea beverage, requires a large supply of steam to support various production processes. This steam is used in the process of heating tea leaves, heating water through a heat exchanger, and heating chemicals and water in the cleaning in place (CIP) process. Steam pressure of 5 bar that is flowed to the process equipment will undergo condensation to produce condensate. To separate steam and condensate, steam traps are used, consisting of several types, namely mechanical, thermostatic, and thermodynamic. However, in operational practice, steam trap malfunctions often occur, either in the form of steam leaks that are wasted with condensate or failure to drain condensate from the system. This condition causes a decrease in the efficiency of the steam piping system and increases the workload of the boiler. As a result, fuel consumption and boiler feed water requirements become greater than ideal conditions. Therefore, this study aims to analyze the energy and operational losses caused by steam trap malfunctions, as well as evaluate their impact on boiler system performance and steam utilization efficiency at PT. Tirta Fresindo Jaya Pasuruan plant.      

This quasi-experimental study examines the effectiveness of Artificial Intelligence (AI)-assisted learning in enhancing critical thinking skills among undergraduate history students. The study involved 60 students divided into experimental and control groups. The experimental group received AI-supported instruction integrating adaptive learning modules, scaffolded source-analysis prompts, and guided argumentative discussions facilitated by conversational AI tools, while the control group followed conventional lecture-based instruction. Data were collected using a validated critical thinking test, classroom observation protocols, and semi-structured interviews. Quantitative data were analyzed using paired and independent sample t-tests, while qualitative data were examined through Miles and Huberman’s interactive analysis model. Results indicate statistically significant improvements in critical thinking scores in the experimental group compared to the control group. Thematic findings reveal enhanced sourcing, contextualization, corroboration, and evidence-based argumentation skills. However, minor risks of over-reliance on AI highlight the need for instructional scaffolding and ethical guidance. The findings suggest that AI can function as a cognitive scaffold that strengthens historical thinking and metacognitive awareness when implemented within a structured pedagogical framework.

Vocational education in Vocational High Schools (SMK) requires innovative, interactive, and industry-relevant learning media to support students’ independent and competency-based learning. However, learning activities in the subject Communication in the Workplace for Grade XI MPLB at SMKN 62 Jakarta are still dominated by lecture-based methods with limited instructional media, resulting in low levels of student independence and understanding. This study aimed to develop and examine the feasibility, practicality, and effectiveness of an interactive e-book based on Canva for Oral Communication materials in Indonesian Language. The study employed a Research and Development (R&D) method using the ADDIE development model, consisting of analysis, design, development, implementation, and evaluation stages. The research subjects included 36 students in the needs analysis stage, 5 students in the small-scale trial, and 31 students in the large-scale trial. Data were collected through observation, questionnaires, learning outcome tests, and documentation, and analyzed using descriptive qualitative and quantitative techniques. The validation results indicated that the Canva-based interactive e-book was categorized as very feasible, with validation percentages of 100% from the material expert, 88.24% from the media expert, and 95% from the language expert. The small-scale trial showed a practicality percentage of 82.2%, while the large-scale trial reached 88.39%, both classified as very practical. In addition, the pre-test and post-test results in the large-scale trial demonstrated an increase in students’ average scores and a higher number of students achieving the Minimum Mastery Criteria (KKM). Therefore, the Canva-based interactive e-book is feasible, practical, and effective as a learning medium to enhance students’ understanding, motivation, and independent learning in Oral Communication for vocational high school students.

This study examines the implementation of the Minister of Marine Affairs and Fisheries Regulation Number 7 of 2024 concerning the Management of Lobster, Crab, and Blue Swimming Crab in East Kalimantan. As a strategic policy, the regulation aims to ensure sustainable fisheries management through provisions on minimum catch sizes, restocking mechanisms, traceability systems, and law enforcement against illegal fishing and trade. Using an empirical juridical approach, this research collected primary data through questionnaires distributed to fisheries officers, coastal communities, fishers, and aquaculture business actors in East Kalimantan. The results show that the implementation of Regulation No. 7/2024 is generally categorized as moderately effective, with an average Likert score indicating limited but positive compliance. Respondents acknowledged the importance of sustainability principles embedded in the regulation; however, significant challenges persist, including insufficient formal socialization, weak field monitoring, lack of supporting facilities, and inconsistent coordination among implementing agencies (BARANTIN, PSDKP, and local fisheries officers). Qualitative responses highlight that many stakeholders still lack understanding of technical provisions such as minimum size requirements and restocking obligations. The study concludes that while the regulatory framework is normatively comprehensive and aligned with sustainable fisheries principles, its practical effectiveness remains constrained by institutional and socio-cultural factors. Strengthening community engagement, increasing inter-agency coordination, and enhancing enforcement capacity are crucial to optimizing the policy’s impact on the sustainable management of lobster, crab, and blue swimming crab resources in East Kalimantan.

This study is titled Analysis of the Incumbent's Defeat in the 2024 Regional Head Election in East Flores Regency (A Study of Antonius Hubertus Gege Hadjon's Defeat in East Adonara District), with the aim of analyzing the factors that led to the defeat of incumbent Antonius Hubertus Gege Hadjon in the 2024 Pilkada. This study uses Pierre Bourdieu’s political modality theory, including political, social, economic, and cultural capital. A qualitative approach with a descriptive method is employed, and data is collected through interviews with subjects consisting of the incumbent candidate, a religious leader, a youth leader, a community leader, two party representatives, and the success team. The study focuses on the support base in East Adonara District. The results of the study indicate that the incumbent's defeat was caused by the weakening of political capital, especially due to the vacancy in the regent’s position for two and a half years, which strengthened the opponent's position. This caused stagnation in public services and a decrease in the intensity of local government communication. In addition to these structural factors, weak internal party consolidation and public sentiment about uneven development also contributed to the defeat, indicating the incumbent's failure to manage his political capital amidst the dynamics of governance.

This study aims to analyze the perceptions of students from various majors regarding the urgency of legal protection for the Napoleon wrasse (Cheilinus undulatus), a rare and endangered marine species that plays a crucial role in maintaining the balance of coral reef ecosystems. This fish faces serious pressure due to overexploitation and illegal trade, thus requiring special attention from a legal and conservation perspective. This study used a qualitative descriptive approach with purposive sampling technique, involving students from marine, fisheries, environmental, and legal departments. Primary data were collected through a questionnaire designed to elicit respondents' insights, level of understanding, and recommendations regarding the protection of this species. The data obtained were then analyzed using thematic analysis to identify patterns of perception and key ideas. The results showed that the majority of students considered legal protection for the Napoleon wrasse to be very urgent. They advocated for strengthening regulations, stricter law enforcement, increased surveillance in water areas, education for coastal communities, development of conservation and cultivation programs, and strengthening international cooperation. The implications of this study emphasize the importance of a comprehensive and collaborative protection strategy to support the sustainability of marine resources.

The rapid development of digital technology has significantly transformed financial transactions in Indonesia, particularly through the growing use of e-wallets as practical and efficient payment tools. In a country with a Muslim-majority population, ensuring that e-wallet services comply with Islamic principles—free from riba, gharar, and maysir—is essential. This study aims to analyze Indonesia’s legal politics in regulating the use of e-wallets within the Islamic financial system and to assess their alignment with sharia principles. This research employs a normative juridical method with a qualitative descriptive approach by examining laws, regulations, and fatwas related to sharia-based fintech. The findings indicate that the Indonesian regulatory framework—through the OJK, Bank Indonesia, and DSN-MUI—has attempted to harmonize policies to support sharia-compliant digital financial services. However, several challenges remain, including limited e-wallet platforms with sharia certification, low digital sharia literacy among users, and the absence of detailed technical regulations specific to sharia e-wallet operations. This study recommends strengthening regulatory guidelines, increasing public literacy, and enhancing collaboration between regulators and the fintech industry to promote the development of sharia-compliant e-wallets that are secure, innovative, and aligned with Islamic financial principles.

The integration of Information and Communication Technology (ICT) and tools like Canva has revolutionized English Language Teaching (ELT) in Indonesia, shifting from traditional methods to interactive, student-centered approaches. This study aims to explore the benefits and challenges of incorporating these technologies into ELT practices. Employing a qualitative literature review methodology, the research analyzed over 20 empirical studies from 2020 to 2023 on Canva and ICT in Indonesian ELT, supplemented by global Computer-Assisted Language Learning (CALL) frameworks. Key findings reveal that ICT and Canva enhance student motivation, creativity, and communicative skills through multimodal and constructivist learning, while fostering authentic language exposure and collaboration. However, challenges include inadequate infrastructure, limited teacher training, digital inequities between urban and rural areas, ethical issues such as copyright infringement, and increased teacher workload. The implications underscore the need for systematic professional development, institutional support, curriculum alignment, and policies promoting equitable access to ensure transformative and sustainable technology integration in Indonesian ELT.  

This study examines students’ perceptions of the use of online platforms for English listening practice. The research employs a mixed-methods approach involving 150 undergraduate students through questionnaires and semi-structured interviews. The findings indicate that the majority of students hold positive attitudes toward the use of online platforms, primarily due to time flexibility, diverse content, and the ability to learn independently. Nevertheless, several challenges were identified, including internet connectivity issues that disrupt the learning experience, a lack of personalized feedback, and difficulties in maintaining learning motivation. Features such as adjustable playback speed, the availability of transcripts, and interactive exercises received high levels of satisfaction. Overall, the study concludes that although online platforms have great potential to enhance English listening skills, their effectiveness largely depends on proper implementation, adequate technical infrastructure, and active support from educators. Therefore, this study recommends improvements in technical aspects and the development of more effective learning methods to achieve more optimal outcomes.

The UNAMA Library employs information systems to enhance its academic services. Nevertheless, its administrative framework continues to encounter obstacles, such as inadequate service system support for users, constrained resources allocated for the management and upkeep of the system, an absence of standardized protocols for addressing technical challenges, and insufficient assessment system efficacy. If these issues remain unaddressed, the operational effectiveness of the library information system will be compromised, thereby thwarting the objective of delivering dependable information services. This investigation seeks to illuminate the maturity level of information system governance as delineated by COBIT 2019 within the Decision Support Systems (DSS) domain, specifically focusing on the DSS01 (Manage Operations) and DSS02 (Manage Service Requests and Incidents) processes. The findings suggest that the degree of information system governance capability the UNAMA Library is situated at the Established Process level (level 3), signifying that the process has undergone implementation; however, it has yet to be comprehensively documented and consistently evaluated. Moreover, a disparity persists between the existing state and the anticipated capability level of the organization, particularly concerning IT operations management, the standardization incident handling, and the documentation of operational procedures. An elucidation of the expected level is articulated, especially in terms of operational standards, incident documentation, and IT infrastructure oversight. Recommendations encompass the formulation of standard operating procedures (SOPs), the enhancement of documentation practices, and periodic assessments grounded in COBIT 2019. These findings are anticipated to assist libraries in augmenting the efficacy of information systems governance and the quality of IT services.

Background: The increasing complexity of industrial production systems requires machine condition monitoring solutions that are capable of operating in real time with high accuracy and responsiveness to support predictive maintenance strategies. Conventional cloud based monitoring systems often experience limitations such as high latency and dependence on stable network connectivity, which can delay decision making processes in critical industrial operations. Objective: This study aims to design and evaluate an Industrial Internet of Things (IIoT) architecture based on edge computing to improve the efficiency of industrial sensor data processing and accelerate anomaly detection in industrial machines. Method: The research adopts an experimental approach by designing a system architecture consisting of a sensor layer, edge computing layer, and cloud layer. Industrial sensors, including vibration, temperature, and current sensors, continuously collect machine operational data, which are then processed locally at the edge node using a machine learning based anomaly detection algorithm. System testing is conducted in a simulated manufacturing environment to evaluate performance based on latency, reliability, and detection accuracy. Results: The results indicate that edge based data processing significantly reduces latency compared with cloud-based processing and enables faster responses to machine condition changes. Additionally, the implemented anomaly detection algorithm achieves high accuracy in identifying abnormal sensor data patterns.

Background: The development of industrial technology in the Industry 4.0 era has encouraged the implementation of intelligent monitoring systems to improve machine reliability and operational efficiency. However, machine fault diagnosis systems based on artificial intelligence often face limitations in terms of interpretability because the models used are complex and difficult to explain. Objective: This study aims to develop a deep learning-based industrial machine fault diagnosis system integrated with an Explainable Artificial Intelligence (XAI) approach to improve diagnostic accuracy while providing interpretable insights for users. Method: The research method involves collecting data from industrial machine sensors consisting of vibration signals, temperature measurements, and acoustic signals, followed by data preprocessing and feature extraction processes. The processed data are then used to train a deep learning-based diagnostic model, after which explainability methods such as SHAP or LIME are applied to analyze the contribution of each feature to the model’s prediction results. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics. Results: The results indicate that the proposed deep learning model achieves better performance compared to conventional machine learning methods such as Support Vector Machine and Random Forest. Furthermore, the explainability analysis reveals that vibration amplitude, increases in machine component temperature, and anomalies in acoustic signals are the main factors influencing machine fault detection. Therefore, the proposed system not only improves the accuracy of machine fault diagnosis but also provides transparency in the decision-making process, thereby supporting the implementation of predictive maintenance in smart manufacturing environments.

The integration of Artificial Intelligence (AI) into educational settings, particularly in formative assessments, offers significant benefits in terms of personalized learning, real time feedback, and increased efficiency. However, the successful implementation of AI driven formative assessments depends not only on technological capabilities but also on socio cultural and organizational factors that shape its adoption. This study explores the socio technical factors influencing the use of AI in formative assessments, emphasizing the importance of considering cultural diversity, institutional culture, and educators' beliefs. AI technologies, while powerful in automating grading and providing personalized assessments, often face limitations in addressing complex student responses that require human judgment. Furthermore, cultural factors, such as students' prior exposure to technology and different cultural attitudes towards AI, play a critical role in the acceptance and effectiveness of these tools. Organizational factors, including leadership support, digital literacy, and the readiness of institutions to adopt AI, are also key determinants in the successful implementation of AI systems in education. Teachers’ beliefs about assessment influence their acceptance and use of AI tools, highlighting the need for professional development and training to ensure that AI enhances pedagogical goals rather than replacing human expertise. The study concludes that the alignment of technology, culture, and assessment beliefs is essential for the effective use of AI driven formative assessments in educational settings. Recommendations for educational institutions include adopting a socio technical approach to AI integration, with a focus on providing resources, training, and fostering a culture of innovation. Future research directions should focus on expanding studies to diverse educational contexts, conducting longitudinal research on AI’s impact on learning outcomes, and exploring additional socio technical frameworks to guide AI adoption in education.

This study investigates the long-term impact of adaptive digital learning ecosystems on students' self-regulated learning (SRL) behaviors and academic persistence. Adaptive learning systems personalize the learning experience by adjusting content and feedback to meet individual students' needs, preferences, and performance. These systems enhance engagement, motivation, and learning outcomes through real-time adjustments and continuous feedback. The research aims to explore how adaptive learning systems influence SRL and academic persistence in university courses over time. Using a longitudinal quantitative design, the study tracks SRL behaviors and academic persistence at multiple points during the semester. Results show significant improvements in SRL behaviors such as goal setting, planning, self-monitoring, and reflection among students engaged with adaptive learning environments. These students exhibited greater autonomy, improved metacognitive awareness, and higher motivation. Additionally, students in adaptive systems demonstrated greater academic persistence, as indicated by more time spent on tasks, higher assignment completion rates, and sustained engagement. The findings suggest that adaptive learning platforms promote SRL and academic persistence by offering personalized, responsive learning experiences. Unlike static, non-adaptive environments, adaptive systems provide dynamic support, enhancing students' ability to regulate their learning and remain engaged despite challenges. The study concludes that adaptive learning systems are vital for long-term academic success, though further research is needed to assess the sustainability of these effects in various educational settings and among diverse student populations.