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The issue of uninhabitable houses still requires an accurate identification mechanism because the manual data collection process has the potential to be time-consuming, costly, and subject to subjectivity in determining aid priorities. This study aims to develop a classification model to identify habitable and uninhabitable houses based on family socioeconomic data using the Random Forest algorithm. The research method includes data preprocessing, data division using stratified split in three scenarios, baseline model development, and optimization through hyperparameter tuning using GridSearchCV with 3-fold cross-validation and balanced class_weight parameters. The data used includes variables such as education type, employment status, occupation type, number of family members, and family insurance type. The test results show that the 70:30 data division scenario after tuning provides the best performance with a recall value of 0.5797 for uninhabitable houses and an F1-score of 0.4746. Feature importance analysis shows that education type and employment status are the most influential variables in the classification. The results of this study show that the model built is capable of increasing sensitivity in detecting uninhabitable houses to support more objective field survey prioritization.

Attention mechanisms have been widely incorporated into recurrent neural network architectures for financial time series forecasting, with most prior work reporting improvements in price-level error metrics. This study revisits that claim through a controlled empirical comparison of four deep learning architectures on nearly two decades of Telkom Indonesia (TLKM) closing price data from the Indonesia Stock Exchange (IDX). The models evaluated are a three-layer Gated Recurrent Unit (GRU) baseline, a comparable Long Short-Term Memory (LSTM) network, a Bahdanau end-attention GRU (Attn-GRU-V2), and a multi-head self-attention GRU hybrid (Attn-GRU-V3). Each architecture is trained over 30 independent runs with distinct random seeds, and performance is reported as 95% confidence intervals derived from the t-distribution. Statistical comparisons employ the Wilcoxon signed-rank test, a nonparametric paired test appropriate given the confirmed non-normality of residuals. The main finding is a consistent trade-off: the plain GRU achieves the lowest RMSE (94.02 ± 1.22 IDR) across all 30 runs, while Attn-GRU-V2 achieves the highest directional accuracy (45.91 ± 0.09%), surpassing GRU in every independent run. Bahdanau attention weights are nearly uniform across the 30-day lookback window (coefficient of variation: 3.21%), indicating that the mechanism cannot identify selectively informative timesteps in this univariate price series. This finding is consistent with the weak-form Efficient Market Hypothesis for the Indonesian market. An ablation study reveals that a 20-day lookback window maximizes directional accuracy (47.72 ± 0.21%) for the Attn-GRU-V2 model. These results suggest that Bahdanau end-attention consistently and significantly improves directional accuracy relative to a plain GRU baseline, providing an architecturally attributable advantage for direction-based applications, even when absolute price-level error is not reduced. The directional accuracy values remaining below 50% across all models are consistent with a weak-form efficiency characterization of the Indonesian market.

The synchronization of physical and juridical land data is a fundamental prerequisite for ensuring legal certainty in every land rights transfer process. Discrepancies between physical field conditions and juridical documents frequently trigger land disputes that impede the performance of Notary/PPAT offices. This community service article reports on a Field Practice (PPL) activity conducted at the Office of Notary/PPAT in Jember Regency during January–February 2026. The primary objective was to provide technical assistance in accelerating physical-juridical data synchronization to guarantee the validity of issued deeds. The method employed was participatory observation, in which students were directly engaged in the partner's workflow. Assistance activities covered document inspection, file digitization, coordination with BPN and tax authorities, and factual field verification. Results indicate that PPL student assistance measurably accelerated the office's administrative workflow, enhanced data validation accuracy, and confirmed conformity between the physical condition of rice-field land and the certificate documents.

This study aims to analyze the influence of internal company factors, including company size, networking capital, operating efficiency, liquidity, and leverage, on financial performance, proxied by Return on Assets. The research population includes 40 food & beverage subsector companies listed on the Indonesia Stock Exchange during the 2019–2024 period. Using purposive sampling, 17 sample companies were selected, yielding a total of 102 data observations. This study adopts a quantitative approach, using secondary data obtained from the company's annual financial statements. Data analysis was performed using multiple linear regression to identify partial and simultaneous influences between variables. Empirical findings show that not all internal factors exert a uniform influence on financial performance, as some variables have been shown to have a significant influence, while others do not show a statistically significant relationship. These results have important implications for managers and investors in formulating internal management strategies to drive sustainable profitability

Good governance has become a crucial framework for improving public sector effectiveness, accountability, and responsiveness to citizens’ needs. In Indonesia, decentralization policies since 1999 have devolved significant authority and resources to local governments, creating both opportunities and challenges in implementing good governance principles. This study examines administrative reform efforts in Indonesian local governments, focusing on progress, challenges, and key success factors. Using a multiple case study design, the research analyzed reform initiatives in six district/city governments with diverse contexts. Data were collected through document analysis, semi-structured interviews with government officials, civil society representatives, and citizens, as well as direct observation of administrative processes conducted between March and November 2024. The study assessed six core principles of good governance: participation, transparency, accountability, effectiveness and efficiency, equity and inclusiveness, and rule of law. The findings reveal variations in implementation across regions, with high-performing governments demonstrating strong leadership commitment, systematic planning, active citizen engagement, and effective monitoring mechanisms. However, challenges persist, including limited capacity, bureaucratic resistance, weak accountability enforcement, and low public participation. Key success factors include visionary leadership, capacity development, strategic partnerships, and institutional strengthening. Policy recommendations emphasize enhancing local capacity, accountability systems, citizen participation, and performance evaluation. Good governance has become a crucial framework for improving public sector effectiveness, accountability, and responsiveness to citizens’ needs. In Indonesia, decentralization policies since 1999 have devolved significant authority and resources to local governments, creating both opportunities and challenges in implementing good governance principles. This study examines administrative reform efforts in Indonesian local governments, focusing on progress, challenges, and key success factors. Using a multiple case study design, the research analyzed reform initiatives in six district/city governments with diverse contexts. Data were collected through document analysis, semi-structured interviews with government officials, civil society representatives, and citizens, as well as direct observation of administrative processes conducted between March and November 2024. The study assessed six core principles of good governance: participation, transparency, accountability, effectiveness and efficiency, equity and inclusiveness, and rule of law. The findings reveal variations in implementation across regions, with high-performing governments demonstrating strong leadership commitment, systematic planning, active citizen engagement, and effective monitoring mechanisms. However, challenges persist, including limited capacity, bureaucratic resistance, weak accountability enforcement, and low public participation. Key success factors include visionary leadership, capacity development, strategic partnerships, and institutional strengthening. Policy recommendations emphasize enhancing local capacity, accountability systems, citizen participation, and performance evaluation.

Leadership constitutes a critical determinant of organizational efficiency, yet the relationship between leadership styles and administrative effectiveness remains incompletely understood, particularly across different institutional contexts. This comparative study examines how transformational, transactional, and laissez-faire leadership styles influence administrative efficiency in public and private sector institutions in Indonesia. Using a mixed-methods approach, quantitative data were collected from 428 employees across 28 public institutions and 24 private organizations through validated survey instruments; qualitative data were gathered through 36 semi-structured interviews with organizational leaders and managers. Results reveal significant positive relationships between transformational leadership and administrative efficiency in both sectors (β = 0.54, p < 0.001 for public; β = 0.48, p < 0.001 for private), with transactional leadership showing moderate positive effects (β = 0.32 public; β = 0.38 private) and laissez-faire leadership demonstrating negative relationships (β = −0.28 public; β = −0.24 private). Leadership styles collectively explain 52% of efficiency variance. Mediation analysis reveals that organizational culture (28%), employee engagement (35%), and trust in leadership (22%) partially mediate transformational leadership's effects, together accounting for 62% of total indirect effects. Sector differences emerged qualitatively: transformational leadership leverages public service motivation in public institutions, while transactional leadership's performance accountability resonates more strongly in private organizations. The study contributes theoretical understanding of leadership effectiveness across institutional contexts and provides practical guidance for developing contextually appropriate leadership development programs.

The increasing sophistication of malware has rendered traditional signature-based detection methods insufficient, necessitating behavior-driven and adaptive analytical frameworks. This study presents a sequential deep learning framework that models system-level API call sequences as structured linguistic representations for behavioral malware detection. Unlike conventional comparative studies, this work systematically evaluates recurrent and attention-based architectures under controlled experimental conditions, with a particular focus on generalization performance and overfitting mitigation. Two neural architectures, a Long Short-Term Memory (LSTM) network and a Transformer-based attention model, are trained on publicly available API call sequence data for binary classification of malicious and benign executables. Beyond standard accuracy metrics, the study further examines model stability, convergence behavior, and the impact of long-range dependency modeling on detection robustness. Experimental results demonstrate that the Transformer architecture achieves superior performance, attaining 95.54% classification accuracy and consistent improvements in precision, recall, and F1-score, indicating a stronger ability to capture complex behavioral dependencies. These findings highlight the effectiveness of attention mechanisms in behavioral malware modeling and provide empirical evidence that NLP-inspired architectures offer a robust and scalable approach for real-world cybersecurity applications.

This community service activity aims to analyze the effectiveness of Time and Motion Study in the production process at PT. Adis Dimension Footwear and provide recommendations for improving work methods. This study employed a qualitative descriptive approach using observation, interviews, and documentation. The results show that implementing Time and Motion Study can enhance work time efficiency, optimize operator movements, and increase productivity by up to 15%. Reducing unnecessary movements, optimizing workflow, and training operators significantly improve production performance. The success of this method depends heavily on socialization, training, and management support. These findings confirm that Time and Motion Study serves not only as a tool for measuring time and movements but also as a strategic instrument for improving efficiency, reducing waste, and increasing overall productivity.

Community service at Toko Entus Collection aimed to improve operational efficiency and sales through the implementation of a digital system. Students actively participated in managing social media, online promotions, and digital stock monitoring. Observations showed that digital media can disseminate product information widely, enhance consumer interaction, and support sales growth. Challenges included limited digital knowledge of the store manager, limited time for promotions, and inconsistent consumer responses. Direct guidance, socialization of digital media use, and adjustment of promotional strategies helped overcome these challenges. Students’ hands-on experience allowed the application of digital marketing theory to real business situations, while store managers benefited from improved operational performance. Therefore, this community service provides dual benefits: practical learning for students and increased competitiveness for SMEs.

This study aims to analyze the role of the Protocol Division in supporting the activities and performance of regional leaders, particularly from the functional and interpersonal aspects in local government administration. The study employs a qualitative approach using Qualitative Secondary Analysis (QSA) through a review of literature, policy documents, and relevant previous research on protocol functions within government organizations. The analysis is grounded in organizational role theory and managerial role concepts. The results indicate that the Protocol Division plays a strategic role in supporting the effectiveness of regional leaders’ duties through two main dimensions. First, the functional role, which includes managing the regional leader’s activity agenda, organizing protocol-related events, arranging official ceremonies, and coordinating with regional apparatus and relevant institutions to ensure smooth implementation of government activities. Second, the interpersonal role, which encompasses acting as a communication liaison between the regional leader and various stakeholders, facilitating inter-agency working relationships, and supporting the representative function of the regional leader in official and community social events. The findings suggest that the successful execution of regional leaders’ activities is influenced not only by the leaders’ own leadership capacity but also by the effectiveness of organizational support from units that assist leadership, such as the Protocol Division. This role contributes to enhancing coordination effectiveness, ensuring smooth implementation of government activities, and strengthening the image and authority of regional leaders in performing their leadership functions. Therefore, strengthening institutional capacity, improving human resource competencies, and utilizing information technology in managing leadership activities are crucial factors in optimizing the role of the Protocol Division in local governance.

Abstraks Tujuan penelitian ini adalah untuk mengidentifikasi faktor-faktor yang mempengaruhi kinerja kerja di Puskesmas Lasem, khususnya dengan melihat iklim kerja, disiplin kerja, dan motivasi karyawan. Output karyawan merupakan variabel dependen dalam analisis ini, dengan ketiga faktor tersebut sebagai variabel independen. Penelitian ini terutama didasarkan pada tanggapan kuesioner, dan menggunakan data primer. Informasi pribadi subjek penelitian menjadi dasar penelitian ini. Sampel yang digunakan berjumlah 85 orang. Proses pengambilan sampel menggunakan sampel jenuh. Penelitian ini menggunakan analisis regresi linier berganda sebagai pendekatan analisis datanya. Hasil penelitian memperlihatkan adanya hubungan positif dan signifikan secara statistik antara variabel lingkungan kerja dan kinerja karyawan, serta hubungan positif dan tidak signifikan secara statistik antara variabel disiplin kerja dan kinerja karyawan.   Abstact The purpose of this research is to identify the factors that affect job performance at the Lasem District Health Center, specifically looking at the workplace climate, work discipline, and employee motivation. Employee output is the dependent variable in this analysis, with the aforementioned three factors serving as independent ones. Primarily based on responses to a questionnaire, this study draws on primary data. Research subjects' personal information is what the research relies on. Using a sample size of 85 people. The sampling process makes use of saturated samples. The research used multiple linear regression analysis as its data analysis approach. The study found that there is a positive and statistically significant relationship between the work environment variable and employee performance, as well as a positive and statistically insignificant relationship between the work discipline variable and employee performance.

Ship berthing and departure planning is one of the crucial aspects in supporting the operational effectiveness of shipping companies. This study aims to analyze the important role of planners in ship berthing and departure activities in supporting marketing activities at PT. Nusantara Pasifik Sentosa Belawan. The method used in this research is a descriptive qualitative approach through observation and documentation study. The findings indicate that well-planned and coordinated ship berthing and departure activities provide a significant contribution to customer satisfaction, delivery punctuality, and the company’s image in the eyes of business partners. Effective planning also helps the company maintain service reliability and improve operational efficiency in port activities. However, several obstacles were identified, including lack of coordination between departments, limited information flow, and schedule disruptions caused by external factors such as weather conditions and port congestion. These challenges can affect the smoothness of operational activities and indirectly influence the company’s marketing performance. Therefore, strategies are required to improve human resource competencies, enhance digital communication systems, and strengthen cross-sector collaboration. With a well-structured planning system, PT.Nusantara Pasifik Sentosa is expected to improve its service quality and increase its competitiveness in the national shipping industry.

This article analyzes the role of Work-Life Balance, Motivation, and Work Environment on Employee Performance in the manufacturing industry. Work-Life Balance (WLB) can be measured on time management, mental health, job satisfaction, and overall performance. Work Motivation is seen from intrinsic and extrinsic factors, while the Work Environment is seen from a conducive, safe, and comfortable atmosphere. This study uses a quantitative approach using SmartPLS. This method was chosen because of its effectiveness in testing complex causal models with many variables and its flexibility assuming data distribution. Primary data was collected from 98 employees via Google from Likert scale, using the seneus technique. Analysis includes evaluating measurement models for validity and reliability and testing hypotheses. The SEM-PLS analysis confirms that Work-Life Balance, Motivation, and Work Environment all have a positive and significant impact on employee performance. WLB showed the most dominant influence among the three factors. This research is an important factor that significantly affects employee performance. Maintaining and improving these factors, especially WLB, is essential for fostering employee motivation, a sense of security, and maximizing work output, thereby contributing to the overall success of the organization.

Ankle sprain is one of the most common musculoskeletal injuries in sports activities and often results in pain, limited range of motion, muscle weakness, and decreased functional ability. Appropriate physiotherapy management is essential to accelerate recovery and restore ankle function. This study aims to analyze the effectiveness of combining electrotherapy modalities and exercise therapy in the rehabilitation of bilateral grade II ankle sprain caused by sports injury. The research used a case study approach with physiotherapy interventions conducted through several treatment sessions. The interventions consisted of electrotherapy modalities combined with therapeutic exercises designed to reduce pain, improve joint mobility, and increase muscle strength and functional stability of the ankle. Clinical evaluation was carried out through observation of pain levels, range of motion, and functional ability during the therapy period. The findings indicated a gradual improvement in the patient’s condition, including decreased pain, increased ankle range of motion, improved muscle strength, and better functional performance during daily activities. These results suggest that the integration of electrotherapy and exercise therapy can provide a comprehensive rehabilitation approach for ankle sprain injuries. The combined intervention not only supports pain reduction but also enhances joint stability and functional recovery, enabling patients to return safely to their physical activities and reducing the risk of recurrent injury.

Bullying in schools continues to be a serious concern that adversely impacts students’ psychological well-being, social relationships, and academic performance. Factors such as low empathy, inadequate social skills, and limited environmental control contribute significantly to this behavior. This study seeks to examine the implementation of group guidance as an approach to reducing bullying among students. A qualitative descriptive method was utilized, involving participants consisting of students identified as bullying perpetrators, school counselors, and victims. Data collection techniques included interviews, observations, and documentation, which were analyzed through processes of data reduction, data presentation, and conclusion drawing. The results reveal that group guidance leads to positive behavioral changes in students, such as enhanced empathy, greater self-awareness, and improved communication and social interaction abilities. Furthermore, a reduction in both verbal and social bullying behaviors was observed. The group dynamics established during the sessions enabled students to better understand the consequences of their actions and gain insights from the experiences of others. These findings imply that group guidance can serve as an effective and sustainable strategy for preventing and managing bullying in school settings.

Online gambling is a form of addictive behavior that often begins with simple experimentation. Early wins tend to encourage individuals to continue gambling with increasingly larger stakes, driven by the belief that higher bets will lead to greater profits. Along with the rapid advancement of digital technology, online gambling has become more accessible to various groups, including university students, through convenient and flexible online platforms. Although it is often perceived as a form of entertainment, online gambling has significant negative impacts. This study aims to analyze the effects of online gambling on students’ mental health. The research uses a qualitative approach, with data collected through observations and interviews involving respondents who engage in online gambling activities. The findings reveal that online gambling has detrimental effects on students’ psychological well-being, including increased levels of stress, anxiety, depression, and sleep disturbances. Furthermore, it contributes to decreased concentration, reduced learning motivation, and declining academic performance. Therefore, stronger preventive measures and educational efforts are necessary to minimize the negative impacts of online gambling among university students.

The issue of illegal parking in the Pasar Jambi area remains unresolved despite various enforcement efforts carried out by the Jambi City Transportation Agency. Non-compliant parking practices, such as the presence of unauthorized parking attendants, the imposition of fees beyond official rates, and the lack of use of official attributes, indicate a discrepancy between established standards and actual field conditions. This study aims to analyze the effectiveness of the Transportation Agency’s supervision in controlling illegal parking in the Pasar Jambi area by applying George R. Terry’s supervision theory indicators. The research employs a qualitative method with a case study approach, using data collection techniques including observation, interviews, and documentation. The findings reveal that supervision has been implemented through stages of setting standards, measuring performance, comparing implementation with standards, and taking corrective actions. However, the effectiveness of supervision is still not optimal. This is reflected in the persistent gap between standards and practices in the field, the limited number of supervisory personnel, and corrective actions that have not been consistently effective in creating a deterrent effect. Although enforcement has been carried out progressively through warnings, guidance, and direct actions, violations continue to occur repeatedly. The implications of this study highlight the need to strengthen consistency in supervision, enforce stricter sanctions, and enhance resource capacity so that supervision is not merely administrative but can create sustainable parking order.

This community service program aims to enhance teachers’ competence in developing Higher Order Thinking Skills (HOTS)-based assessment items to support improved performance in the Computer-Based National Assessment (ANBK) at SMP Negeri Kletek. The main problem faced by the partner school is the limited understanding of teachers in designing assessment instruments that measure higher-order thinking skills, as well as insufficient ability to develop literacy- and numeracy-oriented questions aligned with ANBK characteristics. This condition has resulted in suboptimal learning evaluation quality and limited student readiness for national assessment. The program employed a Participatory Action Research (PAR) approach, emphasizing the active involvement of participants throughout all stages. The implementation included the planning stage through needs assessment and problem identification, the action stage through training and mentoring in HOTS-based item development, the observation stage through evaluation of participants’ work, and the reflection stage to identify achievements and challenges. Data were collected using pre-test and post-test, observation, and reflective discussions. The results indicate an improvement in teachers’ understanding and skills in developing HOTS-based items, as reflected in higher post-test scores. Teachers were able to design competency-based blueprints, contextual stimuli, and analytical, evaluative, and creative questions. This program effectively strengthens teachers’ professional competence and school readiness for ANBK.

This study aims to design and develop a functionally efficient and operationally effective Internet of Things (IoT)-based air quality monitoring system for radiology departments. The system utilises a DHT22 sensor integrated with an ESP32 microcontroller to monitor the temperature and humidity of diagnostic rooms in real time, and to display the data via the UdaraKu mobile application. The research method employed a quantitative experimental approach focused on measuring system performance, specifically the accuracy of the temperature and humidity sensors. The research model used was the Research and Development (R&D) method, aimed at transforming conventional air quality monitoring in radiology into a real-time digital system based on IoT. The research results indicate that the IoT-based monitoring system is capable of maintaining room temperature and humidity stability within the ideal range, namely 22–24°C and 50–60% RH, in accordance with international standards. This improvement in environmental stability has a direct impact on reducing noise in digital radiography images, as evidenced by an increase in the Signal-to-Noise Ratio (SNR). Instrument validation demonstrated a high level of reliability with a Cronbach’s Alpha value of 0.848, reinforcing the reliability of the data and the system. Overall, the IoT-based air quality monitoring system has proven effective in controlling noise in digital radiography images, improving the quality of diagnostic services, and supporting patient safety principles and operational efficiency within radiology departments.

Information technology advancements have sparked a digital revolution in village government operations, especially in tracking and assessing village officials' performance. Performance evaluation is still done by hand in many village government organizations, which frequently causes reporting delays, ineffective data processing, and a lack of transparency in the evaluation process. In order to facilitate a more efficient and organized monitoring and performance evaluation process, an information system therefore required. In order to support the management village apparatus data, performance assessment procedures, and integrated reporting, this study intends design and develop a web-based monitoring system for assessing the performance village officials. To represent the system processes in an organized way, the system design is modeled using the Unified Modeling Language (UML), which includes use case diagrams, activity diagrams, and sequence diagrams. To make sure that every system function performs in accordance with user requirements, system testing is carried out using the Black Box Testing method. The findings demonstrate the system's ability handle village apparatus data, carry out automated performance evaluation procedures, compute final scores using assessment indicators, and produce precise performance reports. It is anticipated that the system's implementation will enhance the village officials' performance monitoring procedure's efficacy, efficiency, transparency, and structure.