This study aims to describe the types of errors and the factors causing errors made by students in solving System of Linear Equations in Two Variables (SLETV) problems based on Newman’s Error Analysis. This research is a descriptive qualitative study with the subjects being students of class IX-10 at SMP Negeri 1 Percut Sei Tuan in the 2025/2026 academic year. The data were collected through diagnostic tests, questionnaires, and interviews. The data analysis technique was carried out by identifying students' errors based on the five stages of Newman, namely reading errors, comprehension errors, transformation errors, process skill errors, and encoding errors. The results showed that students made errors at all stages of Newman’s procedure, with the dominant errors occurring at the transformation and process skill stages. These errors include students’ inability to understand the meaning of the problems, transform word problems into mathematical models, and carry out calculation procedures accurately. The factors causing students’ errors include low conceptual understanding, lack of procedural skills, lack of accuracy in answering questions, ineffective study habits, and low student attitudes toward mathematics. Based on the findings, it can be concluded that error analysis using Newman’s procedure is able to systematically identify the location of students’ errors in solving SLETV problems. Therefore, it is expected that teachers can use the results of this analysis as a basis for designing more effective learning strategies to minimize students’ errors and improve learning outcomes.
The development of the Islamic insurance industry in Indonesia continues to grow as the public becomes more aware of financial products that adhere to Islamic principles. Among the various business sectors within Islamic general insurance, Islamic motor vehicle insurance offers significant potential. This study aims to determine the contribution of Islamic motor vehicle insurance premiums to the total premiums of the Islamic insurance industry in Indonesia and to understand its role within the overall structure of the industry. This study uses a descriptive quantitative method by analyzing secondary data derived from reports from the Financial Services Authority (OJK) and the Indonesian Islamic Insurance Association (AASI).The research results show that Sharia motor vehicle insurance premiums contribute significantly to the Sharia general insurance category, but their contribution to the total premiums of the Sharia insurance industry remains relatively small compared to Sharia life insurance, which dominates the market. This is because Sharia life insurance products are well-known and widely accepted, while Sharia general insurance still has a limited market share. It is hoped that this research will assist stakeholders and industry regulators in designing Sharia motor vehicle insurance development strategies to increase its contribution to the national Sharia insurance industry.
This study develops an IHSG stock price forecasting model using a hybrid CNN–BiGRU architecture enhanced by an attention mechanism. The key novelty lies in combining CNN-based local pattern extraction with BiGRU-based bidirectional temporal modeling, while attention selectively emphasizes the most informative time steps, improving representation quality for complex and noisy financial series. Historical IHSG data from public sources were preprocessed through feature engineering and normalization, followed by XGBoost-based feature selection to retain the most predictive variables. Model robustness was assessed in two settings: (i) the full dataset and (ii) a “cleaned” dataset excluding the extreme COVID-19 volatility period. The proposed model achieved strong accuracy, with MAE/RMSE of 0.0125/0.02 on the full dataset and 0.0167/0.03 on the cleaned dataset, while Pearson correlation remained close to 1 in both scenarios, indicating high alignment with actual IHSG movements. A 30-day ahead forecast produced a stable and realistic trend. Overall, the CNN–BiGRU with attention provides an effective and robust approach for capturing multi-scale temporal patterns in IHSG forecasting.
The development of Integrated Islamic Primary Schools is in response to the society’s increasing demand for quality graduates. Thus, the emphasis on the effectiveness of learning in Integrated Islamic Primary Schools (IIPS) necessitates institutional innovation and teacher professionalism. This research investigates the professionalism in IIPS and determines the factors that contribute to teachers' professional practices. The study is qualitative with a phenomenological approach. This study employed the “Tarbiyah learning framework” developed by Abdurahman Al-Nahlawi, and the data were collected through in-depth interviews and observations to investigate the dimensions of teacher professionalism, teaching methodologies, and factors affecting teacher professionalism. The findings reveal that there is a mismatch between professional development initiatives and the actual conditions faced by students. Teaching-learning process that is responsive to students needs and characteristics, collaborative learning programs and supervision sctivities are all viable strategies. Teacher professionalism can be identified by demonstrating strong commitment and work discipline. The IIPS also provides structured training programs and collaborative partnerships with the education office to improve relevant teaching competencies and methodologies. Further, the social implications of this research include the availability of high-quality educational options for the community at the primary school level. Furthermore, the varied management system of IIPS serves as a social control to ensure the quality of primary education continues to develop.
The purpose of this study is to determine the influence of digital marketing and product quality, digital marketing and product image on purchasing decisions for Wardah brand cosmetics at the Alisa Simpang Mangga Rantau store. This research aims to determine and analyze the influence of product quality and digital marketing on Wardah brand loyalty. This research uses a quantitative approach with descriptive methods. Quantitative descriptive is a type of research to carry out data analysis by providing a description or explanation of the data that has been collected. The instrument in this research used a questionnaire and for sampling used the Lemeshow theory approach. Data analysis techniques in this research use validity tests, reliability tests, normality tests, heteroscedasticity tests, multicollinearity tests, coefficient of determination tests, hypothesis tests, partial tests, simultaneous tests, and the method used is the multiple linear regression analysis method. The results of this research show that Product Quality has a positive and significant influence on Brand Loyalty and Digital Marketing has a positive and significant influence on Brand Loyalty.
