Publication Search

This study examined the operational performance of CV Fortis Sportwear Indonesia (FSI) before implementing the Balanced Scorecard approach, identified the factors that hindered each Balanced Scorecard perspective, and analyzed the company's operational performance when measured using this approach.This study employed a descriptive quantitative method, aimed at providing a systematic, factual, and accurate overview of CV FSI's operational performance based on the Balanced Scorecard approach. Data were collected through interviews, questionnaires, observations, and literature review to obtain information related to the four main perspectives of the Balanced Scorecard: financial, customer, internal business processes, and learning and growth.After implementing the Balanced Scorecard, the performance evaluation of CV Fortis Sportswear Indonesia became more comprehensive compared to the previous system, which focused solely on financial aspects. The financial perspective showed improvement, but the customer aspect remained adequate, with declining retention and increasing complaints. Internal business processes still faced inefficiencies and quality issues, despite the introduction of new technology. The learning and growth perspective also improved through training, but employee satisfaction remained moderate. The Balanced Scorecard proved to provide a more comprehensive performance assessment and identified the need for improvements in customer, internal processes, and human resource development.

Anxiety in completing a final thesis is a common issue experienced by final-year students, which can affect academic performance, mental health, and even delay graduation. This condition highlights the importance of effective strategies to manage psychological pressure appropriately. This study aims to explore the application of spiritual coping in helping students reduce anxiety during the thesis writing process. The research employed a qualitative approach with a descriptive design. The participants consisted of three students selected from a total of thirteen who had been identified with severe anxiety. The instruments used were the Taylor Manifest Anxiety Scale as an initial assessment, followed by in-depth interviews and observations to explore their experiences, coping strategies, and psychological dynamics. Data were analyzed thematically by focusing on the personal, social, environmental, and religious domains in the practice of spiritual coping. The findings indicate that spiritual coping assists students in managing emotions, discovering life meaning, and maintaining academic commitment. Religious practices, prayer, spiritual reflection, and social support proved effective in fostering inner peace and alleviating anxiety symptoms. In conclusion, spiritual coping can serve as an effective strategy to support students in facing academic pressures and in enhancing psychological well-being.

This study compares the scalability and maintainability of three prominent programming paradigms-functional programming (FP), object-oriented programming (OOP), and declarative programming (DP)-in the context of distributed data processing systems. The research aims to evaluate how each paradigm performs under increased data volume and its ability to handle complex operations, while also assessing the ease of maintenance through code readability, modularity, and the flexibility of updating and debugging. The study employs a comparative experimental design, implementing identical data processing tasks, such as data aggregation, filtering, and transformation, across each paradigm. Key findings indicate that FP and DP outperform OOP in terms of scalability, with their stateless nature and high-level abstractions enabling efficient parallel processing and task distribution. FP, with its emphasis on immutability and concurrency, and DP, with its focus on describing desired outcomes rather than implementation specifics, both demonstrate superior performance in handling large datasets. However, while OOP excels in modularity and flexibility, its reliance on mutable state and shared resources hampers its scalability in distributed environments. In terms of maintainability, both FP and DP offer clearer, more maintainable code due to their abstraction levels, making them easier to update and extend. OOP, while modular, presents challenges in managing mutable state, complicating maintenance. This paper concludes with practical recommendations for developers on when to use each paradigm based on system requirements and suggests areas for future research, such as hybrid paradigms and long-term maintainability studies in real-world applications.

This study aims to evaluate the relationship between skinfold calliper measurements and handgrip strength with segmental fat and muscle composition among adults in Kota Bambu, providing evidence for simple and applicable community-based screening tools. A cross-sectional design was applied to 135 participants aged 18–96 years. Skinfold thickness was assessed at four anatomical sites (biceps, triceps, suprailiac, scapular), handgrip strength was measured using a digital dynamometer, and segmental body composition was obtained via bioelectrical impedance analysis. Findings demonstrated a moderate positive correlation between handgrip strength and arm skeletal muscle mass (r = 0.371–0.407; p < 0.01), indicating that handgrip performance reflects segmental muscle contractility and functional reserve. Skinfold measurements showed moderate-to-strong positive correlations with both local and central subcutaneous fat distribution (r = 0.562–0.635; p < 0.01), confirming their sensitivity in estimating segmental adipose accumulation. These results highlight that calliper and handgrip strength can serve as practical, low-cost preliminary screening indicators for mapping muscle and fat distribution in urban communities, although they are not substitutes for comprehensive body composition assessment. Further longitudinal studies integrating advanced physiological and functional parameters are recommended to enhance predictive validity and clinical applicability.

This research aims to analyze the adaptive role of a dance teacher in teaching the subject of music art at SMK Asta Mitra Purwodadi, as well as identifying the patterns of collaborative approaches and the implementation of the Deep Learning strategy in the learning process. This phenomenon attracts researchers due to the case of a teacher teaching cross-disciplinary subjects, although still within the domain of the arts. This study employs a qualitative method using observation, semi-structured interviews, and documentation techniques. The main subject of this research is Bu Evi, a dance teacher who also serves as the music art instructor. The research results indicate that the non-specialist teacher (with a dance background) successfully overcomes limitations in teaching music by performing a role transformation into a facilitator focusing on expression, rhythm, and performance. The implementation of Deep Learning is realized effectively through a kinesthetic approach, where abstract music concepts (such as tempo and dynamics) are translated through body movement exploration, which is proven to increase student enthusiasm and understanding. Furthermore, the teacher implements a strategic collaborative pattern with the music extracurricular teacher, where responsibilities are divided between aspects of expression/movement and the deepening of theory/vocal technique, ensuring talented students still receive adequate technical development. Assessment focuses on performative aspects (expression, tempo, teamwork, and self-confidence). This research concludes that the teacher's professionalism and pedagogical creativity are the main keys to bridging competency gaps, while simultaneously ensuring the achievement of the goals of the Merdeka Curriculum in shaping student character and 21st-century skills.

Cryptocurrency has become a rapidly developing digital asset class that attracts widespread investor interest due to its decentralized, anonymous, and highly volatile nature. Such volatility creates uncertainty in market movements, making it important to understand the factors that drive fluctuations in returns. This research aims to examine how fundamental indicators namely price, trading volume, and market capitalization affect return volatility, as well as to determine which cryptocurrency demonstrates the highest market efficiency based on risk assessment. The study uses panel data covering the five largest cryptocurrencies by market capitalization (Bitcoin, Ethereum, Tether, USD Coin, and Binance Coin) over the period 2019–2023. The analytical methods applied include panel data regression to identify the determinants of volatility and Value at Risk (VaR) to measure asset risk and efficiency. The findings show that price and trading volume positively and significantly increase return volatility, whereas market capitalization exerts a negative and significant effect, indicating its stabilizing role. Based on VaR analysis, Binance Coin (BNB) emerges as the asset with the highest market efficiency. The study concludes that fundamental indicators play a crucial role in shaping volatility and that BNB offers relatively better risk performance compared to its peers.

Ear, Nose, and Throat (ENT) health is an essential component of adolescents’ well-being and learning performance; however, health literacy related to ENT care among senior high school students remains limited. This community service activity aimed to improve students’ knowledge and basic ENT skills at SMA Negeri 9 Pekanbaru through skill lab–based learning as a school health promotion strategy. The program was conducted through theoretical education covering basic ENT anatomy and common ENT disorders among adolescents, followed by hands-on training in simple ENT examinations using demonstration and direct practice with learning aids. Evaluation was carried out using pre-test and post-test assessments to measure knowledge improvement, as well as direct observation to assess students’ practical skills. The results demonstrated a clear increase in students’ knowledge after the intervention, along with improved ability to perform basic ENT examinations under instructor guidance. Students also showed better understanding of early signs of ENT disorders and appropriate preventive behaviors. Participation and enthusiasm during the activities were high, and most students reported that the program was beneficial and relevant to their daily experiences. This activity also supported the School Health Unit (UKS) program and strengthened collaboration between the school and the university. In conclusion, skill lab–based basic ENT training is an effective promotive and preventive approach to enhancing ENT health literacy and basic clinical skills among senior high school students.

This study compares the effectiveness of MAUT (Multi-Attribute Utility Theory), SMART (Simple Multi-Attribute Rating Technique), and WASPAS (Weighted Aggregated Sum Product Assessment) methods in a decision support system for determining the best employees at Sisilia Boutique. The quality of human resources is crucial in the retail business, but performance evaluation is often influenced by subjectivity. To address this, a multi-criteria-based decision support system is needed. MAUT translates preferences into a numerical scale, SMART calculates the average value of attributes based on weights, while WASPAS combines weighted summation (WSM) and weighted multiplication (WPM) for more balanced results. Employee performance data from Sisilia Boutique in June 2025, including attendance, store layout, customer service, and discipline, were used as the research object. The comparison results show consistency in the highest (K3) and lowest (K7) ratings across the three methods, with differences in the middle ratings. WASPAS offers a more balanced distribution of final scores, making it a comprehensive alternative for performance evaluation.

This study examines the effectiveness of interactive digital platforms in improving student academic outcomes. The integration of digital platforms in education is becoming increasingly important, but challenges arise regarding educators' adaptation of technology. This study analyzes the effectiveness of platforms such as Kahoot and Padlet through a systematic literature review. The study identifies gaps in previous research that focused more on platform features than on learning outcomes and educator adaptation. Using a systematic literature review of 45 peer-reviewed articles (2019-2024), this study explores the relationship between platform interactivity, educator technology proficiency, and measurable academic improvement. Data analysis uses thematic coding to identify patterns in successful digital learning implementation. The results show that interactive platforms can improve academic performance by 15-25% if educators have adequate technological skills, but success rates decline without proper training. This study proposes a comprehensive framework that integrates platform effectiveness metrics with educator development strategies. Recommendations include structured technology training programs and standardized assessment protocols to measure the effectiveness of digital learning.

This study aims to analyze the impact of business combinations through acquisition on the financial performance of PT Sarana Menara Nusantara Tbk. The research employs a descriptive quantitative approach, focusing on the acquiring firm in the Indonesian telecommunications infrastructure sector. The data used are secondary data obtained from the company’s annual financial statements for the period 2019–2023, sourced from the Indonesia Stock Exchange and the company’s official website. Financial performance is analyzed using Return on Assets (ROA), Return on Equity (ROE), Net Profit Margin (NPM), and Debt to Equity Ratio (DER) by comparing the periods before, during, and after the acquisition conducted in 2021. The results indicate that the acquisition exerted short-term pressure on asset efficiency and profitability, as reflected by the decline in ROA and NPM in the year of acquisition. However, in the post-acquisition period, the company demonstrated an improvement in operational performance, particularly in Net Profit Margin, suggesting that the economic benefits of the business combination gradually materialized. Meanwhile, fluctuations in ROE and DER reflect adjustments in the capital structure following the acquisition. These findings suggest that the success of an acquisition cannot be evaluated solely based on short-term financial performance but requires continuous assessment to capture its medium- and long-term effects. This study provides practical implications for management in formulating post-acquisition integration strategies and contributes empirically to the accounting and finance literature on business combinations in Indonesia.

Magnetic resonance imaging (MRI) provides rich anatomical contrast for brain tumor assessment, yet routine interpretation remains time-intensive and demands high precision. This work develops a pipeline for four-class brain MRI image classification (glioma, meningioma, pituitary tumor, and no tumor) by combining automated brain-region cropping, data augmentation, and transfer learning with EfficientNetB1. Experimental results demonstrate exceptional performance, achieving an overall accuracy of 0.99 (99%) on the test set. Specifically, the model reached an F1-score of 1.00 for the no tumor class, 0.99 for pituitary, and 0.98 for both glioma and meningioma classes. Beyond reporting numerical performance, the study utilizes Grad-CAM heatmaps to verify that predictions rely on clinically plausible regions rather than spurious background cues. These results indicate that an efficiency-oriented backbone, paired with systematic preprocessing, can achieve reliable and interpretable performance for brain tumor classification tasks.

The COVID-19 pandemic significantly affected the financial performance of PT Kereta Api Indonesia (Persero), as reflected in the shift from profit in 2020 to a substantial pre-tax loss in 2021. This change had direct implications for the company’s tax components, particularly current tax and deferred tax, in accordance with PSAK 46 on Income Taxes. This study aims to analyze the changes in current tax and deferred tax between the two reporting periods and to examine the role of deferred tax benefits in reducing the company’s net loss. The research employs a quantitative descriptive approach with a comparative analysis method using secondary data from the company’s interim consolidated financial statements. The findings indicate that in 2021 the company recognized a deferred tax benefit that converted total income tax into a net tax benefit, thereby reducing the company’s net loss by approximately 15.8 percent. These results demonstrate that deferred tax does not merely arise from temporary differences but can function as an instrument of loss mitigation during periods of financial distress. The implications of this study highlight the importance of accurate application of PSAK 46, especially in times of economic downturn, and emphasize the need for realistic assessments of future taxable profits to ensure the reliability of deferred tax asset recognition.

This study analyzes creditworthiness assessment and predicts non-performing loan (NPL) risk using the Naïve Bayes algorithm at BPR Ukabima Lestari, Jambi Branch. A quantitative data mining approach with probabilistic classification is applied. The dataset includes borrower attributes such as age, occupation, income, loan amount, tenor, collateral, and repayment history. Research stages comprise data preprocessing, model development, and performance evaluation using accuracy, precision, recall, and F1-score implemented in RapidMiner. The results indicate that the Naïve Bayes model achieves 99.58% accuracy, demonstrating strong capability to predict potential problem loans accurately and efficiently, supporting data-driven credit decisions and strengthening credit risk management in microbanking institutions.

Jambi Province is one of the largest natural rubber producing regions in Indonesia; however, rubber factories under GAPKINDO Jambi still face productivity issues, particularly the gap between production capacity and actual output, and productivity assessment that is still conducted manually by GAPKINDO Jambi. This study employs Decision Tree, Random Forest, KNN, and SVM algorithms within a structured pipeline involving preprocessing, feature selection, standardization, data balancing using SMOTE, and hyperparameter tuning. The proposed solution applies productivity level classification both individually and through paired combinations (ensemble voting). The results show that the Decision Tree + Random Forest model achieves the best performance with an accuracy of 0.84 and an F1-score of 0.83, confirming the effectiveness of ensemble methods in supporting productivity improvement decisions.

The National Student Arts Festival and Competition (FLS3N) is an event aimed at developing students’ talents and achievements in the arts, including solo vocal competitions. The assessment process in this category involves multiple criteria, which may lead to subjectivity in decision-making. This study aims to design and develop a web-based Decision Support System (DSS) for selecting non-academic students in the FLS3N solo vocal category using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The assessment criteria are based on the 2025 FLS3N Technical Guidelines, consisting of voice quality, vocal technique, expression, and performance. The TOPSIS method is applied to generate alternative rankings based on the highest preference value. The system is developed using a web-based software development approach and tested using participant data from both male and female categories. The results indicate that the system can provide objective and consistent ranking recommendations, thereby assisting schools in selecting the best students to represent them in the FLS3N competition.

This study aims to improve the kinesthetic intelligence and physical fitness of students with hearing impairments through rhythmic gymnastics lessons in Physical Education, Sports, and Health (PJOK) at SLB Muhammadiyah Kelayu, East Lombok Regency. The research employed a collaborative classroom action research (CAR) approach involving both the researcher and the PJOK teacher. The action was conducted in two cycles, each comprising planning, implementation, observation, and reflection stages. The research subjects consisted of eight students with hearing impairments, including four females and four males. Data were collected through documentation, observation, and performance assessments using developed kinesthetic intelligence and physical fitness instruments, and then analyzed descriptively using quantitative methods. The results indicate that after the rhythmic gymnastics intervention, kinesthetic intelligence improved, with 75% of students reaching the expected development level by the end of Cycle II. Physical fitness also showed significant improvement across five main components: endurance increased to 68.7%, muscle strength and endurance to 65.6%, agility to 68.7%, flexibility to 65.6%, and balance to 71.8%. Rhythmic gymnastics proved to be an effective approach to support inclusivity while enhancing the kinesthetic intelligence and physical fitness of students with hearing impairments.

SMP Negeri 5 Merlung is a public junior high school in Merlung Subdistrict that has utilized the DAPODIK system for online data processing management, enabling efficient sending and receiving of information to the government. This research analyzes IT governance on the DAPODIK system using the COBIT 5 framework, specifically the MEA01 domain (Monitor, Evaluate and Assess Performance and Conformance), which focuses on monitoring and evaluating performance and conformance. The research background is based on the need to maximize the utilization of the system at the school level. The main objectives are to determine the current and expected capability levels, as well as to provide improvement recommendations to achieve higher process maturity. The research method applies Assessment Process Activities, covering observation, interviews, identification of findings, gap analysis, and recommendations. The results show that the current capability level is at level 3 (established process), while the expected capability level is directed toward level 4 (predictable process). The implications of these findings provide practical recommendations such as routine monitoring enhancements, staff training, and integration of automation tools to bridge the capability gap, thereby improving the effectiveness of IT governance at SMP Negeri 5 Merlung sustainably.

This study aims to analyze the application of accounting according to PSAK 65 concerning consolidated financial statements to assess the company's financial performance at PT Warung Begok Indonesia. The object of this study is a company in the field of processed livestock manufacturing for the period 2023-2024. The data in this study are primary data sourced from the annual financial reports of the head office and branches. The total sample in this study was 3 company financial reports. Data collection techniques used interviews and documentation. The hypothesis in this study was tested using descriptive analysis techniques. Based on the data analysis carried out in this study, it shows that the financial statements before and after consolidation have an effect on the assessment of the company's financial performance. This study contributes to increasing knowledge and understanding of the head office and branch consolidated reports according to PSAK 65, and can assess the company's financial performance. Although the consolidated report has been carried out, it is hoped that the company will continue to apply controls and policies in its implementation, because this can affect the assessment of the company's financial performance so that it will be useful in decision making.

Manual quality assessment of Platelet Concentrate (TC) is highly subjective and inconsistent, necessitating an objective, automated classification system. This study aims to develop a computationally efficient, low-cost model for TC quality classification using Histogram Features extracted from grayscale images combined with the K-Nearest Neighbor (KNN) algorithm. The methodology employed critical preprocessing steps, including StandardScaler for normalization and SMOTE for balancing the training data, followed by optimization across K=1 to K=30. The optimal model achieved a maximum accuracy of 69.23% at K=6, with an F1-Score of 71.43%, confirming robust performance on the imbalanced testing set. The results validate the effectiveness of the Histogram-KNN approach as a consistent and reliable decision support system for rapid TC quality screening in resource-limited settings.

This study aims to implement and evaluate the effectiveness of a learning module designed for X grade students (Phase E) at SMAN 4 Palangkaraya, focusing on the Christian values of love, justice, and tolerance within the framework of the Merdeka Curriculum. The implementation involved classroom teaching using lectures, group discussions, and quizzes to foster active and meaningful learning experiences. The objectives included ensuring students' understanding of the core values, developing their ability to articulate these values, and achieving a minimum score on quizzes. The methodology included direct teaching, observation of student responses and engagement, and evaluation of learning outcomes through cognitive and affective assessments. Findings revealed that 90% of students actively participated in discussions, and all groups engaged in answering quiz questions. The use of rewards notably enhanced student enthusiasm and participation. Despite the overall success, some students did not achieve the highest performance level. The implications suggest that integrating technology into the learning process and thorough preparation of teaching materials are crucial for enhancing student outcomes. This study contributes to the understanding of how Christian values can be effectively integrated into the curriculum to promote holistic student development, aligning with the Pancasila Student Profile, which emphasizes faith, moral integrity, global diversity, and collaboration.