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The development of bioinformatics has led to the availability of large amounts of genetic data through public databases such as NCBI Gene, OMIM, and Ensembl. However, the complexity of data presentation and the dominance of English language hinder students, novice researchers, and the general public in understanding the relationship between genes and disease. This research aims to develop a simple web-based information system to identify disease-causing genes with concise, Indonesian-language, and user-friendly information presentation. The method used is Research and Development (R&D), which includes literature study, needs analysis, system design, implementation, testing, and evaluation. The system was developed using a MySQL relational database with a web interface that displays basic gene information, chromosome location, biological function, and gene-disease relationships, complete with simple visualizations. Black Box testing results indicate that all main functions run according to user requirements. This system is expected to improve bioinformatics literacy and become an effective learning medium.

The gap between vocational students’ competencies and the needs of the digital creative industry requires efforts to enhance students’ technological and creative skills. This community service program aimed to improve the digital competence and creativity of vocational students through Canva-based motion graphics training. The program was conducted at SMK Swasta Nur Azizi Tanjung Morawa using lectures, demonstrations, hands-on practice, and mentoring methods. The results showed that participants were able to understand bassic motion graphics concepts and produce simple animated works using Canva. Evaluation results indicated that more than 80% of participants were able to operate Canva’s basic animation features, and all participants successfully produced at least one motion graphics project, with an average competency improvement of approximately 30% compared to pre-training levels. Overall, the training proved effective in enhancing students’ creative skills, confidence, and readiness to meet the demands of the digital creative industry.

Savings and Loan Cooperatives (KSP) play a vital role in expanding community access to capital, especially within the informal sector. Nevertheless, non-performing loans remain a persistent challenge that can threaten liquidity and long-term institutional sustainability. KSP CU Mera Ndi Ate faces similar issues, which are assumed to stem not only from administrative weaknesses but also from members’ perceptions and behavioral factors. This research aims to examine the potential causes of non-performing loans through text-based sentiment analysis using an unsupervised learning approach. A quantitative method with a data mining framework was applied. Data were gathered through interviews, observations, documentation, and 200 customer opinion texts processed using the Orange Data Mining application. The analytical stages included preprocessing, corpus development, feature extraction, sentiment clustering, and visualization. Because the dataset lacked predefined labels, unsupervised learning was used to identify naturally emerging sentiment patterns. Findings reveal a predominance of critical sentiments related to credit assessment procedures and service quality. The highest sentiment score (75) concerned insufficient creditworthiness evaluation, followed by concerns about service efficiency (66.6667). These insights suggest that improving assessment accuracy and service quality may help reduce non-performing loans.

Stock price prediction remains a complex challenge due to the dynamic and non-linear nature of financial markets, especially for banking stocks like PT Bank Negara Indonesia (Persero) Tbk (BBNI). This study aims to optimize BBNI stock price forecasting by integrating an automated Extract, Transform, Load (ETL) pipeline with the Long Short-Term Memory (LSTM) algorithm within a data engineering framework. Historical data from 2019 to 2025 were processed through a structured ETL sequence—including data cleaning, feature engineering, and MinMaxScaler normalization—to ensure high data quality. The dataset was partitioned into 80% for model training and 20% for testing to ensure rigorous evaluation. The results demonstrate that the systematic ETL approach significantly enhances model stability and predictive accuracy compared to conventional methods. The LSTM model effectively captured long-term temporal dependencies, providing reliable trend forecasts with an impressive test accuracy, achieving a Root Mean Squared Error (RMSE) of 0.0354. This research underscores that integrating robust data engineering practices with deep learning is essential for building resilient financial decision-support systems.

In the rapidly evolving digital economy, the ability to anticipate transaction surges is a strategic asset for marketplace platforms to maintain operational efficiency. This research aims to build an accurate daily transaction volume forecasting system thru the implementation of an Extract, Transform, and Load (ETL) pipeline and Autoregressive Integrated Moving Average (ARIMA) predictive modeling. The dataset used is sourced from dataset_olshop.csv, which includes transaction history for the entire year of 2025. The ETL stage focused on data cleaning and handling missing values, while time series analysis began with the Augmented Dickey-Fuller (ADF) stationarity test, which yielded a significant p-value of 0.000006. The parameter model was optimized using the auto_arima algorithm, which determined the ARIMA(2,0,0) configuration as the best model. The evaluation results of the model show fairly stable performance with a Root Mean Squared Error (RMSE) value of 2.002 and a Mean Absolute Error (MAE) of 1.704 on the test data. Research findings reveal a consistently higher purchasing pattern during the mid-month and end-of-month periods, with an average of 5.52 daily transactions, compared to the beginning of the month, which saw 5.48 transactions. The 30-day forecast results provide valuable insights for online store managers to proactively adjust inventory and logistics workforce allocation strategies. This research concludes that integrating data engineering techniques and statistical analysis can provide predictive solutions for the dynamics of the digital market.

The assessment of students’ academic performance in higher education is generally still dominated by conventional numerical approaches, which are less capable of representing qualitative and subjective variables such as classroom activeness and student participation. These approaches often result in evaluations that are not holistic and do not fully reflect students’ overall academic achievements. Therefore, this study aims to analyze the concept of fuzzy logic as a support tool for assessing students’ academic performance in higher education, with a case study of students at Universitas Asahan. The research method employs a descriptive qualitative and quantitative approach by applying Mamdani fuzzy logic. The input variables consist of exam scores, assignment scores, and classroom activeness, while the system output is the category of academic performance, namely sufficient, good, and very good. The sample data consist of ten active undergraduate students from Universitas Asahan. The data processing stages include fuzzification, the construction of fuzzy rules (rule base), fuzzy inference, and defuzzification using the centroid method. The results indicate that fuzzy logic is able to integrate quantitative and qualitative variables and accommodate uncertainty in academic assessment. The resulting evaluation is more proportional and realistic compared to conventional assessment methods based solely on average scores. Therefore, fuzzy logic can be considered an effective and flexible alternative approach to support student academic performance assessment systems in higher education.

This study is motivated by the increasing need for accurate modeling and classification of one-dimensional signal data in intelligent systems. The rapid development of deep learning has led to the adoption of more adaptive and complex neural network architectures capable of capturing both temporal dependencies and local patterns in sequential data. This research aims to analyze and compare the performance of several deep learning models, namely Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid Convolutional Neural Network–GRU (CNN–GRU) model for signal data classification. The research method employs a quantitative experimental approach involving data preprocessing, windowing, model training, and performance evaluation. Model performance is evaluated using accuracy, precision, recall, and F1-score metrics. The results indicate that the hybrid CNN–GRU model outperforms the other models, particularly in capturing local features and long-term temporal dependencies within signal data. These findings suggest that the integration of convolutional layers and recurrent mechanisms enhances feature representation and learning stability. This study is expected to contribute both theoretically and practically to the development of deep learning models for signal processing and time-series-based intelligent applications.

Arrhythmias are generally classified into two groups: disorders of impulse formation and disorders of impulse conduction. Cardiac arrhythmias can also be categorized into three main types: supraventricular arrhythmias, ventricular arrhythmias, and bradyarrhythmias. One of the most commonly encountered arrhythmias in clinical practice is Atrial fibrillation. This study employed a case study method using a nursing process approach. The subjects consisted of two patients: Mrs. S, a 74-year-old female, and Mr. R, a 44-year-old male. The nursing intervention administered was antiarrhythmic therapy using intravenous digoxin. Evaluation was conducted by monitoring the patients’ heart rate and cardiac rhythm using an electrocardiogram (ECG) monitor. The results of the case studies in both patients showed that digoxin therapy produced a positive therapeutic response, as evidenced by a gradual reduction in heart rate. However, ECG monitoring revealed no significant changes in cardiac rhythm. These findings suggest that digoxin is effective for rate control, although it does not restore sinus rhythm.

This study aims to evaluate the implementation of Sidoarjo Regent Regulation Number 69 of 2017 concerning the Civil Servant Code of Ethics in the Family Planning Sector at the Sidoarjo Regency Women's Empowerment, Child Protection, and Family Planning Office. A qualitative approach with a case study was used to explore the implementation of the policy through interviews, observation, and documentation. The analysis was conducted using William Dunn's six policy evaluation indicators, namely effectiveness, efficiency, adequacy, equity, responsiveness, and accuracy. The results show that the policy has provided clear behavioral guidelines and is applied evenly in the work environment. However, the effectiveness and efficiency of implementation are not optimal due to disciplinary violations, weak supervision, and unstructured communication between superiors. The aspects of adequacy and accuracy are considered relevant to the needs of the organization, but have not been able to fully overcome obstacles such as high workloads and low internalization of ethical values ​​among employees. In general, this policy contributes to shaping the professionalism of civil servants, but still requires strengthening through continuous supervision and more systematic coaching. The originality of the study lies in the use of Dunn's evaluation model in the context of the implementation of the civil servant code of ethics at the regional level, as well as identifying gaps between normative policies and field practices. These findings confirm that the success of a code of ethics depends heavily on organizational communication, work culture, and consistency of oversight.

This study evaluates the implementation of the Job Analysis (Anjab) policy at the Provincial General Elections Commission (KPU) of East Java using William N. Dunn’s policy evaluation model. The purpose of this research is to assess the extent to which the Anjab policy has been effective, efficient, adequate, equitable, responsive, and appropriate in supporting human resource management within the Provincial KPU. This study employs a descriptive qualitative approach, with data collected through interviews with personnel in the Subdivision of Personnel, observations, and document analysis of relevant regulations and internal documents. The evaluation shows that the implementation of Anjab within the KPU has not been optimal, as the Anjab documents have not been updated regularly, the job map remains generic and nationally standardized, there is no dedicated team responsible for Anjab management, and personnel’s understanding of Anjab remains limited. These conditions result in discrepancies between job descriptions and actual tasks performed, disproportionate task distribution, and low utilization of Anjab in human resource structuring. Consequently, the policy has not been fully effective, efficient, responsive, or well-targeted. Key recommendations include establishing an Anjab implementation team, providing technical training, developing an institution-specific job map, and conducting regular document updates

The prevalence of diabetic ulcers in Indonesia reaches 12-15% of all sufferers. This condition has an impact on the patient's psychological condition in the form of anxiety due to wounds that are difficult to heal, changes in body image, and concerns about the possibility of amputation. One of the nonpharmacological interventions that can help overcome anxiety is the slow deep breathing technique. The purpose of writing this scientific paper is to carry out Nursing Care for Mrs. M with Diagnosis of Diabetic Ulcers using the application of slow deep breathing intervention in reducing anxiety at Az-Zahra Hospital. The writing method is a nursing care process that includes the stages of study, nursing diagnosis, planning, implementation, and evaluation. The subject of care was Mrs. M, a patient with diabetic ulcers in the inpatient room of Az-Zahra Hospital. Data collection was carried out through interviews, observations, documentation studies, and physical examinations, and using a medical-surgical nursing care assessment format. The ethical principles applied use the principles of Nursing Ethics. The results of nursing care showed that after three days of slow deep breathing intervention, patients reported feeling calmer, sleeping better, and anxiety levels decreased from moderate to mild based on observation results and anxiety scales used. This suggests that slow deep breathing interventions are effective in helping to reduce anxiety in patients with diabetic ulcers. It is hoped that patients and families can continue these breathing exercises independently as part of stress management efforts and quality of life improvement.  

Breast cancer represents a significant public health challenge in Indonesia, accounting for the highest incidence with 68,858 new cases annually (16.6%). This study aimed to evaluate the therapeutic potential of bioactive compounds derived from Zingiber officinale (ginger) as anticancer agents, specifically against estrogen receptor-positive (ER+) breast cancer through the inhibition of estrogen receptor alpha (ERα). Utilizing molecular docking simulations, six active ginger compounds were assessed against the 3ERT receptor. Dihydrocurcumin and tetrahydrocurcumin were identified as the most promising candidates, exhibiting superior binding affinities of -8.091 kcal/mol and -7.565 kcal/mol, respectively, indicative of stable ligand-receptor interactions. A complementary in silico pharmacokinetic evaluation using pkCSM for zingerone, dihydrocurcumin, and tetrahydrocurcumin revealed favorable ADMET profiles, characterized by good intestinal absorption, adequate tissue distribution, low toxicity, and non-mutagenicity. Collectively, these findings underscore the significant potential of these ginger-derived compounds as promising lead candidates for the development of natural product-based breast cancer therapies

The implementation of the Health Workload Analysis (ABK Kes) method reveals both strengths and weaknesses, particularly regarding the suboptimal execution of core tasks such as filing and distributing medical records. This study aims to compare the workload of health human resources (SDMK) between primary and advanced healthcare facilities—specifically Banyudono 1 Public Health Center and Indriati Boyolali Hospital—both of which have implemented hybrid medical record systems. Using primary data collected through interviews and observations and analyzed via the ABK Kes method, the results indicate a need for 10 additional staff members in the Casemix Unit at Indriati Boyolali Hospital and 2 additional medical record practitioners at Banyudono 1 Public Health Center. The Available Working Time (WKT) at the Public Health Center was set at 75,000 based on the Minister of PAN-RB Regulation No. 1 of 2020, whereas the Hospital used real-time calculations. While the Public Health Center aligns its policies with Ministry of Health Regulation No. 19 of 2020, the Hospital adjusts its staffing needs based on the ABK Kes results. Given that this method focuses primarily on quantity, future research and development (R&D) should integrate Lean Thinking for process analysis, ABK Kes for capacity, Queueing Theory for dynamic analysis, and NASA-TLX for psychological evaluation to provide a more holistic assessment of staffing needs.

This community service program aims to enhance the capacity of UMKM Mentari Padangsari in developing visual content to strengthen branding and competitiveness. It is hoped that this training activity will have an impact on the development of MSMEs in Padangsari sub-district.The main problems faced by partners include limited skills in creating product photos, graphic designs, promotional videos, and managing social media consistently. The program was implemented through training, mentoring, and evaluation stages involving 14 UMKM actors in Padangsari Village, Semarang City. Training materials focused on product photography using smartphones, simple graphic design, short promotional videos, visual storytelling, and the use of digital platforms such as social media and Google Business are  considered very necessary in this era of rapid technological development. The results show increased knowledge and skills among UMKM actors in producing more attractive visual content, improving brand identity, and enhancing engagement on social media. This program contributes to strengthening UMKM competitiveness and supports sustainable digital-based marketing practices.

The development of information and communication technology requires students to have digital literacy and communication skills as essential competencies for the 21st century. However, limited infrastructure and low technological literacy remain obstacles in a number of schools, including Moria High School in Sorong City. This activity aims to improve computer network technology literacy and students' speaking skills through a hands-on, practice-based training approach. The method used is qualitative with stages of observation, socialization, training, and evaluation. Computer network training includes an introduction to basic networking concepts, cabling practices, and network simulations using Cisco Packet Tracer. While speaking skills training is conducted through role-play techniques, repetition, and direct feedback. The results of the activity showed an increase in students' understanding of computer network technology, technical practical skills, and increased confidence and clarity in speaking. Evaluations showed that most participants were able to apply the material presented conceptually and practically. Thus, this activity has proven effective in improving students' computer network technology literacy and speaking skills as preparation for facing 21st-century learning and the world of work in the digital era.

Flood disasters that struck Cikahuripan Village significantly affected the physical, psychological, and learning motivation conditions of elementary school students, particularly at SD N 1 Cikahuripan. In the post-disaster period, students experienced a decline in learning motivation caused by psychological trauma, loss of a sense of security, and limited learning facilities. This Community Service Program (Pengabdian kepada Masyarakat/PkM) aimed to restore students’ psychological conditions while strengthening their learning motivation through an integrated psychosocial and pedagogical approach. The implementation methods included an initial assessment of students’ conditions, trauma healing activities based on play therapy, and the application of Fun Learning methods combined with the “Tree of Dreams” activity to rebuild students’ intrinsic motivation. The program was conducted from 15 to 22 November 2025 and involved 31 elementary school students as well as teachers as sustainability partners. The evaluation results showed significant positive changes, indicated by increased cheerfulness, active participation, confidence in social interaction, and improved learning focus among students. In addition, teachers’ capacity to implement trauma-sensitive teaching practices also improved. This program demonstrates that post-disaster learning motivation recovery requires a holistic approach integrating psychological and academic recovery, and it has the potential to serve as a replicable model for educational interventions in disaster-prone areas.

Cardiovascular diseases are the leading cause of death worldwide, accounting for 17.9 million deaths annually. Stroke and heart attacks often go undetected due to their silent nature. This community service activity aimed to increase community knowledge about stroke and heart attacks and conduct early detection through health screening. The activity was conducted in Lalimbue Village, Kapoiala District, Konawe Regency on May 11 and 18, 2025. Methods included healthy exercise, educational talk show, first aid workshop, and health screening (blood pressure, blood glucose, cholesterol). Knowledge evaluation used pre-test and post-test with 10 questions. Results showed 56 participants on implementation day and 17 on follow-up. Pre-test showed 23% had good knowledge, 34% moderate, and 43% poor. Post-test showed 87% good knowledge and 13% moderate. Health screening found 10.7% with hypertension and 10.7% with diabetes mellitus on implementation day. Follow-up found 47.1% with hypertension and 23.5% with diabetes mellitus. This study concluded that health education is effective in increasing community knowledge about stroke and heart attack prevention, and health screening is important for early detection of cardiovascular and metabolic diseases.

This study aims to analyze the collective kiai leadership policies in enhancing the quality of madrasah education at Bahrul Ulum Islamic Boarding School, Tambakberas, Jombang. Using a qualitative research method with a phenomenological approach, the study collects data through in-depth interviews, structured observation, and documentation. The data analysis process involves three stages: data condensation, data display, and conclusion drawing. The study reveals that the formulation of collective leadership policies is based on the need to achieve religious goals, legal foundations, and community needs. These policies are oriented toward problem-solving and continuity, formulated through deliberation and consensus involving all kiai leaders of both formal and non-formal educational institutions within the pesantren. The implementation of these policies emphasizes scholarly sanad and intellectual tradition across all educational institutions. Key aspects include educational administration, human resource development, strengthening formal education based on national accreditation standards, providing entrepreneurship education, and participating in faith-based as well as science and technology competitions at national and international levels. The evaluation of these policies is carried out collectively by all caretakers and leaders in alignment with established policies to ensure quality improvement across the pesantren’s formal and non-formal educational institutions.

The study titled “Designing a Web-Based E-Module for Empowering Tenth-Grade Students’ Writing Skills in Descriptive Text” aims to develop a digital learning medium to improve students’ descriptive writing abilities. The research applies a Design and Development (D&D) approach using the ADDIE model, consisting of analysis, design, development, implementation, and evaluation, supported by a descriptive quantitative method. The study addresses limitations of traditional, teacher-centered instruction that relies heavily on printed materials by integrating technology into the learning process. The research begins with an analysis of existing teaching practices and learning resources for descriptive text writing. Based on this analysis, a web-based e-module is designed to provide a more interactive and engaging learning experience. The module includes structured materials such as definitions, purposes, text structures, language features, examples, and practice exercises. The e-module is then implemented in a tenth-grade classroom setting, followed by an evaluation of its effectiveness using quantitative data. The results indicate that the web-based e-module effectively improves students’ descriptive writing skills. Interactive features, including multimedia content, self-paced activities, and immediate feedback, enhance students’ motivation and active participation. Teachers and students report positive perceptions regarding the practicality, accessibility, and usefulness of the e-module. Pre-test and post-test results also show a clear improvement in students’ writing performance. Overall, the study concludes that web-based e-modules are a promising instructional medium for enhancing writing skills and supporting student-centered, technology-integrated English language learning.

The objective of this study is to formulate new propositions on school management based on the findings obtained from the two schools under investigation, namely: (1) school planning in improving teacher performance at State Islamic Senior High School 1 Trenggalek and State Senior High School 1 Trenggalek; (2) the implementation of school management in improving teacher performance at State Islamic Senior High School 1 Trenggalek and State Senior High School 1 Trenggalek; and (3) school supervision in improving teacher performance at State Islamic Senior High School 1 Trenggalek and State Senior High School 1 Trenggalek. This research employed a case study approach with a qualitative research design. The researcher’s presence in the schools served as the primary instrument, supported by non-human instruments as complementary tools. Data sources consisted of primary data in the form of words and actions observed from principals, vice principals, teachers, and administrative staff, as well as secondary data in the form of school documents. Data collection techniques included in-depth interviews, participant observation, and documentation. Data analysis was conducted using the Miles, Huberman, and Saldaña model, which comprises data condensation, data display, and conclusion drawing. The data analysis techniques applied were (1) single-case analysis conducted separately in each school and (2) cross-case analysis conducted by comparing and synthesizing data across cases. The research findings indicate that: (1) school planning to improve teacher performance carried out by principals included (a) adherence to the school’s vision, mission, and objectives; (b) consideration of the results of the School Self-Evaluation (EDS) through SWOT analysis to enhance teacher performance; and (c) the formulation of school activity plans collaboratively with the school committee; (2) the implementation of school management to improve teacher performance by principals involved (a) mobilizing and motivating all members of the school community and utilizing all available school resources; (b) controlling and supervising the implementation of school activities; (c) securing support for school activities from parents/guardians, the school committee, and the community; (d) fulfilling teachers’ needs; (e) proportional distribution of tasks and clear job descriptions aligned with teachers’ competencies; (f) enhancement of teacher competencies; and (g) fostering a culture of mutual cooperation, care, and respect among school members to improve teacher performance.