Machine learning methods enable industry professionals in the metallurgy sector to rapidly, accurately, cost-effectively, and environmentally responsibly design the mechanical properties of low-alloy steel to meet specific application needs. However, the success of these methods highly relies on data quality and a substantial amount of data. In this study, we evaluate the use of synthetic data in predicting the mechanical properties of low-alloy steel using six machine learning algorithms. Synthetic data is generated using the Mostly AI synthetic data platform, which includes chemical composition, temperature, and the mechanical properties of low-alloy steel. Each model is trained with three different training dataset combinations: (1) using synthetic data, (2) using only experimental data, and (3) using a combined dataset that integrates synthetic and experimental data. Each model is evaluated with three evaluation metrics: MAE, RMSE, and R-squared. The research findings demonstrate that employing a combined dataset with the Decision Tree (DT) algorithm yields significantly better performance compared to models using only experimental or synthetic data. DT achieves an MAE of 8.87, RMSE of 20.38, and an R-squared of 0.98 for YS prediction. For TS, DT attains an MAE of 9.06, RMSE of 20.96, and an R-squared of 0.97. These findings suggest that utilizing synthetic data in modeling the prediction of low-alloy steel’s mechanical properties through machine learning methods can substantially enhance model performance.
Penelitian ini mengkaji Kemuhammadiyahan melalui tiga dimensi utama: historis, ideologis, dan kontributif terhadap pembangunan bangsa Indonesia. Menggunakan metode kualitatif berbasis studi kepustakaan (library research) dengan analisis model Miles, Huberman & Saldaña (2014), data bersumber dari dokumen resmi PP Muhammadiyah, jurnal terakreditasi Sinta, dan literatur akademis terbitan 2018–2026. Hasil kajian menunjukkan bahwa: (1) Muhammadiyah lahir pada 18 November 1912 sebagai gerakan reformis-modernis atas respons terhadap kemunduran umat Islam di era kolonial Belanda; (2) ideologi gerakannya berpijak pada tauhid, amar ma'ruf nahi munkar, tajdid, dan konsep Islam Berkemajuan berwawasan wasathiyah yang bersifat adaptif dan kontekstual; serta (3) kontribusinya terhadap bangsa terbukti secara empiris melalui jaringan amal usaha yang mencakup 170+ perguruan tinggi, 6.000+ sekolah, dan 400+ rumah sakit. Penelitian ini menyimpulkan bahwa nilai-nilai kemuhammadiyahan merupakan warisan ideologis yang relevan dan strategis sebagai fondasi gerakan Islam berkemajuan di Indonesia.
This study examines the ratio legis underlying the 30% quota for women’s parliamentary representation and the causal dimensions of this figure not being met. Why was 30% set as the benchmark for female representation in parliament? Has 30% female representation in parliament been achieved in Indonesia's legislative elections? If not, why is this the case? The method Framed within a normative paradigm, the study analyzes primary/secondary/tertiary legal documents through philosophical, conceptual, and legislative approaches, applying a qualitative, explanatory–descriptive analysis. Novelty the present study will examine the ratio legis that underpins the 30% representation figure, and the causal factors that contribute to the failure to meet this figure. The following analysis will employ a radical feminist legal theory. The analysis that follows consolidates the relevant research landscape. The Results A thirty-percent threshold for women’s participation is in place adopted by Indonesia is not a 'magical a priori' figure, but rather a minimum policy threshold that has emerged from mainstream global norms, supported by human rights obligations (CEDAW), and has an epistemological foundation regarding how numbers affect institutional dynamics (anti-tokenism). The causal justification for the failure of the 30% quota is influenced by a number of factors, including patriarchal culture, party pragmatism and legal structures. The Conclusion the 30% ratio is intended as a corrective tool to shift from formal equality to substantive equality by creating a critical mass so that women's voices are not merely tokenistic. The failure of this threshold reveals a pseudo-neutral legal structure quotas in Indonesia bind candidate lists (descriptive representation) in an open list proportional system without locking in seats (substantive representation), allowing structural barriers political costs, patronage networks, and masculine culture to persist.
The emergence of Muhammadiyah represents a pivotal milestone in the history of Islamic reform in Indonesia, closely linked to the pioneering thought of KH Ahmad Dahlan. Nevertheless, previous studies have predominantly focused on Muhammadiyah as an organization or Ahmad Dahlan as its founder, leaving limited attention to the reconstruction of his ideas as the conceptual foundation of the Muhammadiyah reform movement. This study aims to analyze the pioneering thought of KH Ahmad Dahlan in shaping the Muhammadiyah reform movement and to explain how his ideas were institutionalized into a sustainable socio-religious movement. The research employs a qualitative conceptual approach based on an extensive literature review of reputable journal articles, academic books, and relevant documents. Data were analyzed using qualitative content analysis supported by the perspectives of Islamic Modernism, Social Movement Theory, and Institutional Theory. The findings reveal that Ahmad Dahlan's reform paradigm consists of five interconnected dimensions: purification of Islamic creed, revitalization of ijtihad, integration of Islamic and modern education, Al-Ma'un-based social theology, and organizational modernization. These dimensions enabled Muhammadiyah to institutionalize Islamic values through education, healthcare, philanthropy, and community empowerment, ensuring its sustainability as a reform movement. This study contributes to the literature by providing a conceptual reconstruction of the relationship between Islamic reformist thought, institutional development, and the sustainability of Muhammadiyah. The findings also offer practical insights for strengthening moderate Islamic movements and promoting adaptive Islamic education in addressing contemporary social and technological challenges.
Thermodynamics is often regarded as an abstract and challenging subject by many students, largely due to the complexity of its core principles. Concepts such as entropy, enthalpy, and energy transformation are typically introduced through detailed mathematical equations, which are not always accompanied by adequate visual explanations. This lack of visual support can make it difficult for students to fully grasp the underlying phenomena. To address this issue, the present study focuses on the development of a visualization tool that leverages experimental and simulation data to enhance the learning experience in thermodynamics. The tool is built using operational data collected from a mini coal-fired power plant trainer, which serves as a hands-on educational platform for simulating thermodynamic processes. The application is developed in the Python programming language and deployed using the Streamlit web framework. Several features are integrated into the tool, including automated data reporting, correlation analysis visualized through heatmaps, dynamic visualization of energy flow using Sankey diagrams, and the implementation of three machine learning models to predict electrical output. To evaluate the effectiveness of the tool, experts in the field of thermodynamics assessed it using a Likert scale based on four main criteria. The evaluation results indicate strong performance in all categories. The accuracy of information received an average score of 4.0, visual quality was rated at 4.25, alignment with educational objectives scored 3.75, and ease of use was rated highest at 4.5. All scores fall within the “Good” category, with some approaching “Very Good.” These findings suggest that a data-driven visualization tool, when based on realistic and practical datasets, holds significant potential for improving the clarity and interactivity of thermodynamics instruction.
