Accurate and structured performance assessment is an essential requirement for service-oriented organizations such as law firms. This study aims to develop a personnel performance measurement system at MFP Law Firm Jakarta using the Balanced Scorecard (BSC) approach. The BSC method was selected because it enables comprehensive performance evaluation from four perspectives: financial, customer, internal business processes, and learning and growth. The research was conducted by determining relevant performance indicators for each position within the law firm, namely Partner, Senior Lawyer, Junior Lawyer, Legal Staff, and Finance Staff. The assessment weights were set at 35% for the financial perspective, 25% for customer, 25% for internal business processes, and 15% for learning and growth. The results showed that the highest performance score was achieved by Personnel B (90.55), while the lowest was recorded by Pesonnel N (74.05). This system provides an objective overview of personnel performance achievements and can serve as a foundation for improving human resource management strategies within the law firm

Breast cancer remains one of the leading causes of death among women worldwide, primarily due to late detection and diagnosis. Early and accurate prediction is essential to improve survival rates. Machine learning (ML) techniques have proven effective in supporting early diagnosis. This study aims to evaluate and compare the performance of three different approaches: traditional ML, ensemble ML, and deep learning (DL) for early prediction of breast cancer using the Wisconsin Diagnostic Breast Cancer (WDBC) dataset. The methodology includes data collection, preprocessing, and the design of predictive models. Traditional ML algorithms used include Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Naïve Bayes (NB), and Decision Tree (DT). Ensemble ML techniques comprise Random Forest (RF), XGBoost, and AdaBoost, while DL models include Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). The models were evaluated using precision, recall, F1-score, and accuracy. The results indicate that XGBoost achieved the highest accuracy (0.99), with strong recall (0.98) and F1-score (0.986), outperforming all other ensemble and traditional ML methods. CNN achieved 0.99 in all evaluation metrics, slightly outperforming RNN, which attained 0.98 accuracy and 0.985 F1-score. These findings confirm that ensemble ML techniques outperform traditional models, while CNN leads among DL models. Furthermore, the proposed models demonstrated superior prediction performance compared to existing studies, particularly in minimizing false negatives, which is critical for healthcare applications.

Purpose: This research aims to address the methodological challenges posed by imbalanced data in classification tasks, where minority classes are severely underrepresented, often leading to biased model performance. It evaluates the effectiveness of hybrid sampling techniques specifically, the Synthetic Minority Oversampling Technique combined with Neighborhood Cleaning Rule (SMOTE-NCL) and with Edited Nearest Neighbors (SMOTE-ENN) in improving the predictive performance of ensemble classifiers, namely Double Random Forest (DRF) and Extremely Randomized Trees (ET), with a focus on enhancing minority class detection.
Methods: A total of eighteen simulated scenarios were developed by varying class imbalance ratios, sample sizes, and feature correlation levels. In addition, empirical data from the 2023 National Socioeconomic Survey (SUSENAS) in Riau Province were employed. The data were partitioned using stratified random sampling (80% training, 20% testing). Models were trained with and without hybrid sampling and optimized through grid search. Their performance was evaluated over 100 iterations using balanced accuracy, sensitivity, and G-mean. Feature importance was interpreted using Shapley Additive Explanations (SHAP).
Results: DRF combined with SMOTE-NCL consistently outperformed all other models, achieving 87.56% balanced accuracy, 82.17% sensitivity, and 86.75% G-mean in the most extreme simulation scenario. On the empirical dataset, the model achieved 76.37% balanced accuracy and 75.49% G-mean.
Novelty: This study introduces a novel integration of hybrid sampling techniques and ensemble learning within an interpretable machine learning framework, providing a robust solution for poverty classification in imbalanced datasets.

Folklore is an oral cultural heritage that contains moral values and local wisdom that are important to be transmitted to the younger generation. This study aims to identify and describe the moral values in the folklore "Sultan Hadlirin and At-Taqwa Mosque Loram Kulon Kudus" contained in the book Cerita Rakyat Pesisir Timur by Mohammad Kanzunnudin. The method used is descriptive qualitative with data collection techniques in the form of observing and taking notes and data analysis using the Miles and Huberman model (data reduction, data presentation, and drawing conclusions). The results of the study indicate that this story contains a number of main moral values, namely responsibility, religiosity, social concern, and tolerance. This finding confirms that folklore is not only a medium of entertainment and cultural preservation, but also a means of character education that is relevant to answer the moral challenges of today's young generation. Therefore, the integration of folklore in moral education needs to be encouraged in order to strengthen cultural identity and form individuals with noble character.

In Aceh, the provision of guidance is regulated in Articles 5 and 6 of Gubenur Regulation Number 139 of 2016, which states that the main task and function of the Civil Service Police Unit and Wilayatul Hisbah Aceh is the guidance function. Article 1 point 14 of Qanun Number 7 Year 2013 on Jinayat Procedure Law states that the function of Wilayatul Hisbah (WH) is to socialise, supervise, enforce, and foster the implementation of Islamic Sharia. Therefore, there is a problem of interpreting the authority of coaching carried out by Satpol PP and WH of Lhokseumawe City. This study aims to determine the legal basis for the coaching of suspected jarimah violators by Satpol PP and WH of Lhokseumawe City and the legal consequences of coaching suspected jarimah violators without going through the judicial process carried out by Satpol PP and WH of Lhokseumawe City. The research method used is empirical juridical. Data sources are obtained through interviews with respondents and informants. The results of this study indicate that the coaching carried out by Satpol PP and WH of Lhokseumawe city against suspected jarimah violators does not have a clear legal basis. The coaching carried out is only based on a statement signed by the alleged jarimah violator during the investigation and the legal consequences of coaching against jarimah offenders by Satpol PP and WH of Lhoseumawe City without going through the judicial process is carried out without a legal basis which results in serious legal consequences such as the coaching is not legally valid (can be cancelled), violates human rights, and can be sued civilly or criminally prosecuted and reduces public confidence in Sharia law.

This study aims to improve students' learning outcomes in the subject of Civic Education (PKn), particularly on the topic of Human Rights (HAM), which has often posed challenges at the elementary school level due to students’ low comprehension. The Contextual Teaching and Learning (CTL) model was implemented to connect learning materials with students’ real-life experiences. This research employed a Classroom Action Research (CAR) method using the Kemmis and McTaggart model, which includes four stages: planning, action, observation, and reflection, conducted over two cycles. Data were collected through observation, learning outcome tests, and documentation. The data were analyzed using descriptive quantitative analysis to evaluate the improvement in learning outcomes based on the number of students meeting the Minimum Mastery Criteria (KKM). The results showed a significant increase, with 12 out of 17 students (70.59%) achieving the KKM in the first cycle, and 16 students (94.12%) in the second cycle. These findings indicate that the CTL model effectively enhances students’ learning outcomes by helping them relate the concept of human rights to their daily lives. CTL can serve as an innovative alternative teaching strategy for Civic Education at the elementary level. The researcher recommends the continuous application of the CTL model and further development of varied contextual learning materials to achieve more optimal outcomes.

MSMEs are the backbone of the Indonesian economy. To maintain the continuity of their business, MSMEs must have good and correct financial report management. MSME financial reports tend to be simple and ignore financial administration rules. This research aims to create and compile financial reports in accordance with the Financial Accounting Standards for Micro, Small and Medium Entities (SAK EMKM) for the Berkah Laris Frozen Food UMKM in Malang. The method used in this research is a descriptive qualitative method. The data sources used are primary data in the form of interviews and secondary data in the form of documentation. The results of the research are the presentation of an income statement showing operating profit, a change in capital report showing capital at the end of 2024, a financial position report showing the amount of assets owned equal to the total of liabilities and capital, and notes to the financial report which presents a general overview, an overview of important accounting policies, retained earnings and sales revenue for the period 31 December 2024.

This study aims to analyze the strategic role of differentiated learning management in developing teacher competencies. Employing a literature review methodology, this study examines and synthesizes various relevant scholarly sources addressing the concept of differentiated learning management and its connection with enhancing teachers' competencies. The findings reveal that the implementation of differentiated learning management—encompassing planning, organizing, implementing, and evaluating learning focused on meeting diverse student needs (through differentiation of content, process, and product based on readiness, interests, and learning profiles)—significantly challenges and sharpens teachers' pedagogical and professional competencies. This process encourages teachers to be more innovative in instructional design, effective in managing heterogeneous classrooms, and adaptive to curriculum demands. It is concluded that differentiated learning management is a crucial and effective approach for the sustainable improvement of teachers' competencies, thus fostering an inclusive and high-quality learning environment.

Sitiung is a nagari in West Sumatra. It is located in Sitiung District, Dharmasraya Regency, West Sumatra Province. This Nagari has an area of about 32.27 km2 and is about 18 km from Punjung Island, the capital of the regency. It is also the administrative center of Sitiung Sub-district. Mapping was conducted in the area to determine the administrative boundaries between jorong and the topography of the nagari. A map is simply defined as a representation of an area in which symbols indicate information about the area. Due to the fact that maps indirectly serve as a communication tool between the creator and the person reading it, the captions relating to the contents of the map are very important. The more detailed and complete the information contained in the map, the better and higher quality it is. In addition, it is easier for readers and users to use it. Data collection in the field can be done in various ways. Administrative and Topographic maps will be produced from the measurements taken.

The rapid advancement of digital technology has not been followed by equal digital literacy among elementary school students, especially in areas with limited access. This community service activity focused on increasing students' literacy skills through digital literacy understanding at SD Satu Atap Kelurahan Layana Indah, Mantikulore Sub-District. The objective was to enhance students' ability to access, analyze, and utilize digital information responsibly. The strategy used was participatory learning through socialization, workshops, and direct practice involving both students and teachers. This activity was carried out through classroom action and mentoring. The results show that students gained a better understanding of how to use digital platforms for learning purposes, and teachers improved their ability to integrate technology into their teaching. This program successfully increased students’ enthusiasm and skills in digital learning environments.