bluuebunny/crossref_metadata_2025 huggingface dataset:
Mapping OMOP-CDM to RDF: Bringing Real-World-Data to the Semantic Web Realm
Authors: Chytas Achilleas , Bassileiades Nick , Natsiavas Pantelis
Published: August 2024

Real-world data (RWD) (i.e., data from Electronic Healthcare Records – EHRs, ePrescription systems, patient registries, etc.) gain increasing attention as they could support observational studies on a large scale. OHDSI is one of the most prominent initiatives regarding the harmonization of RWD and the development of relevant tools via the use of a common data model, OMOP-CDM. OMOP-CDM is a crucial step towards syntactic and semantic data interoperability. Still, OMOP-CDM is based on a typical relational database format, and thus, the vision of a fully connected semantically enriched model is not fully realized. This work presents an open-source effort to map the OMOP-CDM model and the data it hosts, to an ontological model using RDF to support the FAIRness of RWD and their interlinking with Linked Open Data (LOD) towards the vision of the Semantic Web.
Data and Process Harmonisation of Multi-National, Multi-Site Research Data
Authors: Turner Jonathan , Impey Sinéad , Gibbons Frances , Bolger Anthony , Stephens Gaye , Hederman Lucy , Hamed Ramisa , O’Meara Ciara , de la Varga Ferran , Kommala John , Nicholson Matthew , Farrell Daniel , Galvin Miriam , Heverin Mark , Mac Domhnaill Éanna , McFarlane Robert , Meldrum Dara , Murray Deirdre , Hardiman Orla
Published: August 2024

To achieve a single fully harmonised research data set suitable for analysis from data collected at multiple sites requires not only semantic integration of collection concepts and convergence onto single collection units, but harmonisation of data collection processes. We describe our experience of identifying harmonisation challenges in the Precision ALS project, with particular focus on process alignment challenges in a multi-site multi-national research data collection project.
Enhancing Healthcare Informatics: Integrating Category Theory Reasoning into OMOP-CDM Ontology Model
Authors: Albarran Rodrigo , Lamy Jean-Baptiste
Published: August 2024

The task of managing diverse electronic health records requires the consolidation of data from different sources to facilitate clinical research and decision-making support, with the emergence of the Observational Medical Outcomes Partnership - Common Data Model (OMOP-CDM) as a standard relational database schema for structuring health records from different sources. Working with ontologies is strongly associated with reasoners. Implementing them over expansive and intricate Ontologies can pose computational challenges, potentially resulting in slow performance. In this paper, we propose the implementation of a new reasoner based on categorical logic over a translation of OMOP-CDM into an ontology model. This enables enhancements to the efficiency and scalability of implementing such models.
Synthetic Data Generation in Hematology – Paving the Way for OMOP and FHIR Integration
Authors: Hahn Waldemar , Ahmadi Najia , Hoffmann Katja , Eckardt Jan-Niklas , Sedlmayr Martin , Wolfien Markus
Published: August 2024

This study advances the utility of synthetic study data in hematology, particularly for Acute Myeloid Leukemia (AML), by facilitating its integration into healthcare systems and research platforms through standardization into the Observational Medical Outcomes Partnership (OMOP) and Fast Healthcare Interoperability Resources (FHIR) formats. In our previous work, we addressed the need for high-quality patient data and used CTAB-GAN+ and Normalizing Flow (NFlow) to synthesize data from 1606 patients across four multicenter AML clinical trials. We published the generated synthetic cohorts, that accurately replicate the distributions of key demographic, laboratory, molecular, and cytogenetic variables, alongside patient outcomes, demonstrating high fidelity and usability. The conversion to the OMOP format opens avenues for comparative observational multi-center research by enabling seamless combination with related OMOP datasets, thereby broadening the scope of AML research. Similarly, standardization into FHIR facilitates further developments of applications, e.g. via the SMART-on-FHIR platform, offering realistic test data. This effort aims to foster a more collaborative research environment and facilitate the development of innovative tools and applications in AML care and research.
Modelling Events in Biomedical Decision Support Systems Using Ontologies
Authors: Miletic Marko , Sariyar Murat
Published: August 2024

Biomedical decision support systems play a crucial role in modern healthcare by assisting clinicians in making informed decisions. Events, such as physiological changes or drug reactions, are integral components of these systems, influencing patient outcomes and treatment strategies. However, effectively modeling events within these systems presents significant challenges due to the complexity and dynamic nature of medical data. Especially the differentiation between events and processes as well as the nature of events is often unclear. This paper explores approaches to modeling events in biomedical decision support systems, considering factors such as ontology-based representation. By addressing these challenges, we strive to provide the means for enhancing the functionality and interpretability of biomedical decision support systems concerning events.
Technological Literacy as a Framework for Health Professions Education in the Digital Era
Authors: Shachak Aviv , Monkman Helen , Lesselroth Blake , Lee Wei Wei , Alkureishi Maria (Lolita) Alcocer
Published: August 2024

With increasing use of information and communications technologies (ICTs) in health, and rapid technological changes, there is a pressing need to prepare current and future health professionals to use ICTs as an integral part of their practice. We propose the Technological Literacy Framework, which includes 3 interlinked elements—knowledge, capabilities, and critical thinking and decision making—as an overarching structure for organizing and designing competencies, learning objectives, and educational interventions for health professions education in the digital era. We provide examples of EHR and telehealth educational interventions and how they map to the framework.
Towards Efficient Resource Utilization Forecasting in Acute Heat Events Using OMOP
Authors: Thiel Jakob , Nesterow Igor , Sedlmayr Martin , Weidner Jens , Henke Elisa
Published: August 2024

Predicting resource utilization can help to optimize the distribution of limited resources in the healthcare system. This requires different climatic and medical data from different sources, which can lead to problems with interoperability. In the paper we describe which data is needed for the prediction and how the data can be made interoperable using OMOP CDM.
Advancing Healthcare Sustainability: Embracing MACH Architecture for Health IT System Transformation
Authors: Haddad Tia , Kumarapeli Pushpa , de Lusignan Simon , Barman Sarah , Khaddaj Souheil
Published: August 2024

The emergence of new collaborative systems, coupled with uncontrolled data accumulation in traditional systems, poses sustainability challenges. This poster advocates the adoption of the MACH architecture as a potential framework to enhance sustainability and credibility within healthcare systems by offering robust system designs and management controls.
How to Accurately Detect Renal Replacement Therapy Weaning in Intensive Care: Data Quality and Standardization Considerations for the OMOP Common Data Model
Authors: Popoff Benjamin , Delange Boris , Kallout Julien , Cuggia Marc , Clavier Thomas , Bouzille Guillaume
Published: August 2024

This study assesses the effectiveness of the Observational Medical Outcomes Partnership common data model (OMOP CDM) in standardising Continuous Renal Replacement Therapy (CRRT) data from intensive care units (ICU) of two French university hospitals. Our objective was to extract and standardise data from various sources, enabling the development of predictive models for CRRT weaning that are agnostic to the data’s origin. Data for 1,696 ICU stays from the two data sources were extracted, transformed, and loaded into the OMOP format after semantic alignment of 46 CRRT standard concepts. Although the OMOP CDM demonstrated potential in harmonising CRRT data, we encountered challenges related to data variability and the lack of standard concepts. Despite these challenges, our study supports the promise of the OMOP CDM for ICU data standardization, suggesting that further refinement and adaptation could significantly improve clinical decision making and patient outcomes in critical care settings.
Fill in the Blank, MIMIC the Procedure: Tracking Patient Record for Medical Data Reconstruction
Authors: Lee Sujung , Seo Daechul , Ko Taehoon
Published: August 2024

This study addresses the missing data problem in the large-scale medical dataset MIMIC-IV, especially in situations where intubation-extubation events are paired. We employed a strategy involving patient scenario works that checked the temporal order and logical links of intubation/extubation data, and seven reconstruction rules for handling missing values. Through this, we reduced the overall loss rate from 36.89% (3321 records) to 13.37% (1204 records) and achieved a 37.26% data increase (+2117 records) compared to before reconstruction(6582).
Finding Groups in the Portuguese Population Through Lifestyle: A Cross-Sectional Study
Authors: Teixeira Andreia , Páscoa Rosália , Martins Carlos , Rodrigues Pedro Pereira
Published: August 2024

Lifestyle interventions are recognized as essential in the prevention and treatment of noncommunicable diseases, the main causes of multimorbidity. A population-based cross-sectional study was carried out in mainland Portugal. 891 Portuguese patients aged ≥20 years, representative of the population, were personally interviewed. For lifestyle, diet and alcohol consumption, physical activity and sedentarism, use of tobacco and illicit drugs, sleeping habits, screen activities and stress, were studied. The bio-sociodemographic data reported were age, sex, marital status, highest level of education, body mass index and health problems in the last 12 months. This study aimed to apply principal components analysis and clustering to identify distinct groups within the population based on lifestyle. It was possible to identify 3 groups: cardiometabolic, healthy and anxious-depressive. It seems very likely that smoking cessation and other behavioral changes only occur after negative health conditions occur.
Integrating Automation, Interactive Visualization, and Unsupervised Learning for Enhanced Diabetes Management
Authors: Baviera-Martineza Carlos , Martinez-Millana Antonio , Lopez-Casanova Francisco de Borja
Published: August 2024

Effective management of diabetes necessitates efficient data handling, insightful analytics, and personalized interventions. In this study, we present a comprehensive system that automates the extraction, transformation, and loading of continuous glucose monitoring data. Data is integrated into an interactive dashboard with dual access levels: one for healthcare management professionals and another for patients for clinical management. The dashboard provides real-time updates and customizable visualization options, empowering users with actionable insights into their glucose levels. Furthermore, a clustering model to categorize patients into distinct groups based on their glucose profiles was developed. Through this model, three clusters representing different patterns of glucose control are identified. Healthcare professionals can utilize these insights to tailor treatment strategies, allocate resources effectively, and identify high-risk patients.
STOP-HCV-HCC Program: Privacy-Preserving Innovation for Remote Data Access Analytics at Federally Qualified Health Centers in South Texas
Authors: Craven Catherine K. , Bobadilla Raudel , Yao Edward , Castillo Caleb , Cerroblanco Julio , Flores Bertha E. , Jain Mamta , Radunsky Alex , Plesak Mikulas , Gentry Craig , Das Riddhiman , Gharibi Gharib
Published: August 2024

STOP-HCV-HCC program to screen and treat hepatitis C, vaccinate for hepatitis B, and prevent hepatocellular carcinoma is implementing a cloud-based privacy-preserving platform to overcome electronic health record barriers to reporting, without data transfer, at four federally qualified health centers in South Texas, USA.
Toward a Patient-Centered Care Supporting System: Integration of Multidisciplinary Health Records in Breast Cancer Care
Authors: Sugiyama Atsuko , Utsunomiya Kazuki , Okumiya Hayato , Fujimoto Katsuhiko , Shimomura Yuka , Sanuki Masaru , Kume Keitaro , Yano Takahiro , Kagawa Rina , Bando Hiroko
Published: August 2024

An important paradigm shift within healthcare is the shift toward patient-centered care (PCC). Multidisciplinary team meetings (MDTM) are considered essential for PCC, despite being considered time-consuming and expensive. Patient-centered information (PCI) is known to improve the quality of care. This study investigated where and how the PCI of multidisciplinary professionals’ health records exists, and to explore the possibility of a sustainable PCC-supporting healthcare system. We performed an exploratory pilot study of the patient records of three patients with breast cancer. We observed that PCI was documented throughout the care pathway in the cases examined. However, we also found that these data were fragmented and scattered across various medical records, and they were also from different point of views and patient care perspectives. PCI was founded to be less accessible than traditional medical records and was even hard to find using a manual search. We therefore propose that preparing PCI for MDTM may be one of the obvious burdens for healthcare professionals (HPs). We do however believe that integrating PCI from multiple professionals’ records likely plays an important function in a shift towards PCC and serves to improve not only the quality of care but also the HPs’ experiences without additional burden and could contribute to a more sustainable health care system.
An Online Visual Elicitation Tool to Facilitate Conversations About Supportive Care in the Context of Cognitive Impairment
Authors: Turner Anne M. , Child Claire E. , Miller Lyndsey M. , Chen Annie T.
Published: August 2024

Older adults with dementia are often left out of decision-making about their care. We developed and evaluated the use of an online visualization tool to foster discussions about future care preferences. The study provides valuable insights on methods for facilitating conversations about complex topics in the context of cognitive decline.
Applying Machine Learning for Prescriptive Support: A Use Case with Unfractionated Heparin in Intensive Care Units
Authors: Delange Boris , Bouzille Guillaume , Gouin Isabelle , Launey Yoann , Mansour Alexandre , Cuggia Marc , Maamar Adel
Published: August 2024

Continuous unfractionated heparin is widely used in intensive care, yet its complex pharmacokinetic properties complicate the determination of appropriate doses. To address this challenge, we developed machine learning models to predict over- and under-dosing, based on anti-Xa results, using a monocentric retrospective dataset. The random forest model achieved a mean AUROC of 0.80 [0.77-0.83], while the XGB model reached a mean AUROC of 0.80 [0.76-0.83]. Feature importance was employed to enhance the interpretability of the model, a critical factor for clinician acceptance. After prospective validation, machine learning models such as those developed in this study could be implemented within a computerized physician order entry (CPOE) as a clinical decision support system (CDSS).
A Modular Service for Causal Inference in the Context of the Gaia-X Ecosystem
Authors: Vierkant Florian , Filter Björn , Özçep Özgür Lütfü
Published: August 2024

Causal inference seeks to learn the effect of interventions on outcomes. Its potential in the health domain has been dramatically increasing recently, due to advancements in machine learning, as well as in the growing amount of medical data collected. Gaia-X provides a framework to implement Health Data Spaces at scale, in a compliant, secure, and trustable manner. In this paper, we provide a modular online service for causal inference using observational data, building on the Gaia-X framework. While two versions of the IDA algorithm for causal inference are already provided, the service allows users to further contribute algorithms in various programming languages (not only for causal inference), as well as their data, and efficiently execute these on a central server. Additionally, the platform facilitates the exchange of algorithms and data among participants. Users of the platform can enter into agreements with other users over the use of algorithms and data. Calculations can be carried out directly on the platform without the need to locally store foreign data.
Enhancing Clinical Practice: Creating Dynamic Medical Content in Electronic Medical Records
Authors: Yasini Mobin , Rausch Dennis , Kozinova Irina , Hochheim Ingrid , Marin Lise , McClelland Tracy , Gout Laurent , Kumar Gaurav , Dahlweid Michael
Published: August 2024

The integration of Electronic Medical Records (EMRs) revolutionized healthcare but often retained limitations from paper-based structures. This study proposes a framework for developing dynamic medical content specifically adapted to the clinical context including medical specialty and diseases. Tailoring content to this dynamic context offers several benefits, including improved access to relevant information, streamlined workflows, and potentially better patient outcomes. We applied our framework to develop neurosurgical content, focusing on brain tumors. The method involves defining the medical specialty, outlining user journeys, and iteratively developing artifacts like assessment forms, dashboards, and order sets. Standardized terminologies ensure consistency and interoperability. Our results demonstrate a successful development of content meeting user needs and clinical relevance. While initial implementation focused on neurosurgery, exploring scalability and AI integration offers promising avenues for further advancement. Future studies could quantitatively evaluate the impact of this method on user satisfaction and patient outcomes.
Comparison of Imputation Methods for Categorical Real-World Prostate Cancer Data with Natural Order
Authors: Schmitt Susanne , Rothlauf Franz
Published: August 2024

Missing values (NA) often occur in cancer research, which may be due to reasons such as data protection, data loss, or missing follow-up data. Such incomplete patient information can have an impact on prediction models and other data analyses. Imputation methods are a tool for dealing with NA. Cancer data is often presented in an ordered categorical form, such as tumour grading and staging, which requires special methods. This work compares mode imputation, k nearest neighbour (knn) imputation, and, in the context of Multiple Imputation by Chained Equations (MICE), logistic regression model with proportional odds (mice_polr) and random forest (mice_rf) on a real-world prostate cancer dataset provided by the Cancer Registry of Rhineland-Palatinate in Germany. Our dataset contains relevant information for the risk classification of patients and the time between date of diagnosis and date of death. For the imputation comparison, we use Rubin’s (1974) Missing Completely At Random (MCAR) mechanism to remove 10%, 20%, 30%, and 50% observations. The results are evaluated and ranked based on the accuracy per patient. Mice_rf performs significantly best for each percentage of NA, followed by knn, and mice_polr performs significantly worst. Furthermore, our findings indicate that the accuracy of imputation methods increases with a lower number of categories, a relatively even proportion of patients in the categories, or a majority of patients in a particular category.
Remote Monitoring, AI, Machine Learning and Mobile Ultrasound Integration upon 5G Internet in the Prehospital Care to Support the Golden Hour Principle and Optimize Outcomes in Severe Trauma and Emergency Surgery
Authors: Mammas Constantinos S. , Mamma Adamantia S.
Published: August 2024

Aim: Feasibility and reliability evaluation of 5G internet networks (5G IN) upon Artificial Intelligence (AI)/Machine Learning (ML), of telemonitoring and mobile ultrasound (m u/s) in an ambulance car (AC)- integrated in the pre-hospital setting (PS)- to support the Golden Hour Principle (GHP) and optimize outcomes in severe trauma (TRS). Material and Methods: (PS) organization and care upon (5G IN) high bandwidths (10 GB/s) mobile tele-communication (mTC) experimentation by using the experimental Cobot PROMETHEUS III, pn:100016 by simulation upon six severe trauma clinical cases by ten (N1=10) experts: Four professional rescuers (n1=4), three trauma surgeons (n2=3), a radiologist (n3=1) and two information technology specialists (n4=2) to evaluate feasibility, reliability and clinical usability for instant risk, prognosis and triage computation, decision support and treatment planning by (AI)/(ML) computations in (PS) of (TRS) as well as by performing (PS) (m u/s). Results: A. Trauma severity scales instant computations by the Cobot PROMETHEUS III, pn 100016) ) based on AI and ML complex algorithms and Cloud Computing, telemonitoring and r showed very high feasibility and reliability upon (5GIN) under specific, technological, training and ergonomic prerequisites B. Measured be-directional (m u/s) images data sharing between (AC) and (ED/TC) showed very high feasibility and reliability upon (5G IN) under specific, technological and ergonomic conditions in (TRS). Conclusion: Integration of (PS) tele-monitoring with (AI)/(ML) and (PS) (m u/s) upon (5GIN) via the Cobot PROMETHEUS III, (pn 100016) in severe (TRS/ES), seems feasible and under specific prerequisites reliable to support the (GHP) and optimize outcomes in adult and pediatric (TRS/ES).
Surveillance of Disease Outbreaks Using Unsupervised Uni-Multivariate Anomaly Detection of Time-Series Symptoms
Authors: Hashemi Atiye Sadat , Ghazani Mirfarid Musavian , Ohlsson Mattias , Björk Jonas , Dietler Dominik
Published: August 2024

Effectively identifying deviations in real-world medical time-series data is a critical endeavor, essential for early surveillance of disease outbreaks. This paper demonstrates the integration of time-series anomaly detection techniques to develop surveillance systems for disease outbreaks. Utilizing data from Sweden’s telephone counseling service (1177), we first illustrate the trends in physical and mental symptoms recorded as contact reasons, offering valuable insights for outbreak detection. Subsequently, an advanced anomaly detection technique is applied incrementally to these time-series symptoms as univariate and multivariate approaches to assess the effectiveness of a machine learning-based method on early detection of the COVID-19 outbreak.
Harnessing the Core Propagation Phenomenon Ontology to Develop a Knowledge Graph for Tracking Health-Related Phenomena
Authors: Medeiros Gabriel H.A. , Soualmia Lina F. , Zanni-Merk Cecilia
Published: August 2024

Biomedical data analysis and visualization often demand data experts for each unique health event. There is a clear lack of automatic tools for semantic visualization of the spread of health risks through biomedical data. Illnesses such as coronavirus disease (COVID-19) and Monkeypox spread rampantly around the world before governments could make decisions based on the analysis of such data. We propose the design of a knowledge graph (KG) for spatio-temporal tracking of public health event propagation. To achieve this, we propose the specialization of the Core Propagation Phenomenon Ontology (PropaPhen) into a health-related propagation phenomenon domain ontology. Data from the UMLS and OpenStreetMaps are suggested for instantiating the proposed knowledge graph. Finally, the results of a use case on COVID-19 data from the World Health Organization are analyzed to evaluate the possibilities of our approach.
Visualizing Mental Health Insights: A Pipeline from Social Media to Chernoff Faces
Authors: Nagi Fatima , Alzubaidi Mahmood , Shah Uzair , Shah Hurmat , Alabdulla Majid , Househ Mowafa , Agus Marco
Published: August 2024

This study proposes an approach for analyzing mental health through publicly available social media data, employing Large Language Models (LLMs) and visualization techniques to transform textual data into Chernoff Faces. The analysis began with a dataset comprising 15,744 posts sourced from major social media platforms, which was refined down to 2,621 posts through meticulous data cleaning, feature extraction, and visualization processes. Our methodology includes stages of Data Preparation, Feature Extraction, Chernoff Face Visualization, and Clinical Validation. Dimensionality reduction techniques such as PCA, t-SNE, and UMAP were employed to transform complex mental health data into comprehensible visual representations. Validation involved a survey among 60 volunteer psychiatrists, underscoring the visualizations’ potential for enhancing clinical assessments. This work sets the stage for future evaluations, specifically focusing on a combined features method to further refine the visual representation of mental health conditions and to augment the diagnostic tools available to mental health professionals.
Performance of a NLP Tool for Text Classification from Orthopaedic Operative Reports, Using Data from the Large Network of Clinical Data Warehouses of the West of France: The HACRO-HUGORTHO Project
Authors: Ansoborlo Marie , Cardoso Jeremy , Herbert Julien , Salpetrier Christine , Bouzille Guillaume , Cuggia Marc , Rosset Philippe , Le Nail Louis-Romée , Grammatico-Guillon Leslie
Published: August 2024

Electronic health data concerning implantable medical devices (IMD) opens opportunities for dynamic real-world monitoring to assess associated risks related to implanted materials. Due to population ageing and expanding demands, total hip, knee, and shoulder arthroplasties are increasing. Automating the collection and analysis of orthopedic device features could benefit physicians and public health policies enabling early issue detection, IMD monitoring and patient safety assessment. A machine learning tool using natural language processing (NLP) was developed for the automated extraction of operation information from medical reports in orthopedics. A corpus of 959 orthopaedic operative reports from 5 centres was manually annotated using the Prodigy software® with a strong inter-annotator agreement of 0.80. Data to extract concerned key clinical and procedure information (n= 9) selected by a multidisciplinary group based on the French health authority checklist. Performances parameters of the NLP model estimated an overall strong precision and recall of respectively 97.0 and 96.0 with a F1-score 96.3. Systematic monitoring of orthopedic devices could be ensured by an automated tool, leveraging clinical data warehouses. Traceability of medical devices with implantation modalities will allow detection of implant factors leading to complications. The evidence from real-world data could provide concrete and dynamic insights to surgeons and infectious disease specialists concerning implant follow-up, guiding therapeutic decision-making, and informing public health policymakers. The tool will be applied on clinical data warehouses to automate information extraction and presentation, providing feedback on mandatory information completion and contents of operative reports to support improvements, and thereafter implant research projects.
Rice Washing Water as an Alternative to Liquid Organic Fertiliser (LOF) in Margamulya Village, Semangga District, Merauke Regency
Authors: Widyantari Ineke Nursih , Wiranto Retnowati , Loppies Stanly Hence Dolfi , Maulany Gerzon Jokomen
Published: August 2024

Semangga District is one of the rice-producing areas in Merauke Regency. One of the villages in Semangga District is Margamulya Village, which has 981 ha of agricultural land, 3,750 tonnes of rice production, and 5.4 tonnes/ha of rice productivity, a population of 2950 people, and 945 households. The population of Margamulya Village is occupied by farmers, with a total of 1069 people. This large population will produce large amounts of household waste as well, and if the waste is not processed, there will be a lot of garbage disposed of, which can damage the environment. Household waste will be more helpful if further processing is carried out, such as liquid organic fertilizer (LOF), which has many benefits for farmers. The main objectives of this community service are 1) to Help provide alternative organic fertilizer for farmers and 2) to help farmers get additional income. The method used in this service is to provide socialization and technical guidance on making liquid organic fertilizer (LOF) from household waste and packaging and marketing LOF. The technical guidance activities went well, and all village-level officials supported the service activities. With this activity, rice-washing water that was previously discarded becomes more practical and can be utilized as an alternative to increasing income in the family.
The Use of Organic Fertilizer Enriched with Bacteria to Improve the Fertility of the Soil
Authors: Marlina Neni , Rosmiah Rosmiah , Khotimah Khusnul , Helmizuryani Helmizuryani , Palmasari Berliana , Amir Nurbaiti , Rompas Joni Phillep , Meidelima Dewi
Published: August 2024

Majority of farmers in Ketapang 1.  Rantau Panjang District  are accustomed to using inorganic chemical fertilizers and a few use organic fertilizers. Excessive use of chemical fertilizers will have a negative effect on soil fertility, physically, chemically and biologically. Infertile soil can cause the soil to become hard and cause plant roots to develop less well and disrupt nutrient absorption, so that the production of all plants will decrease, therefore to increase soil fertility you can use organic fertilizer enriched with Azospirillum bacteria (N-fixing bacteria from air) and phosphate and potassium solubilizing bacteria. This organic fertilizer enriched with bacteria more quickly contributes the NPK nutrients needed by plants. This activity was carried out in Ketapang 1 village, Rantau Panjang District, Ogan Komering Ilir Regency, in the form of counseling and demonstration of the application of organic fertilizer enriched with bacteria. Knowledge about organic fertilizer enriched with bacteria is very beneficial to society to reduce the use of chemical fertilizers, to make the soil more loose and fertile and crop production can increase.
Community Empowerment through the Application of Tut Wuri Handayani to Organizational Leaders in Indonesia and Malaysia
Authors: Kurniawan Ignasius Soni , Wahidah Umi , Nisa Ana Fitrotun , Purnamarini Tri Ratna
Published: August 2024

These activities aims to provide an explanation of the application of Tut Wuri Handayani to SME leaders in Yogyakarta consisting of SMEs Pottery & Ceramic Crafts "Dwiyanto Ceramic, UMKM Azka Furniture Bantul, Rama Putra Motor Bantul, and Community Learning Center (CLC) in Malaysia. Community development activity method uses direct and remote observation by utilizing the zoom application with interview techniques. The concept used is the concept of Tut Wuri Handayani to help problems in the field and solutions for leaders in achieving organizational goals. The solution used, holding webinars and training workshops offline and online. The observation results can implement the leadership attitude of Tut Wuri Handayani in the Pottery & Ceramic Craft SME "Dwiyanto Ceramic, UMKM Azka Furniture Bantul, Rama Putra Motor Bantul, and Community Learning Center (CLC).
Analysis of Factors Affecting the Production of Rice Farming in Lampuara Village, South Ponrang District, Luwu Regency
Authors: Indarsari Misra , Syafruddin Syafruddin , Suprayitno Adi Rianto
Published: August 2024

This research analyzes the factors that influence rice production in Lampuara Village, South Ponrang District, Luwu Regency, South Sulawesi Province, Indonesia. The factors studied include farmer characteristics, agricultural management and agricultural expansion. This research aims to evaluate the directness and influence of these factors indirectly affecting the production of rice farming. The research method uses descriptive analysis techniques using the SPSS application and inferential analysis using a variant-based Structural Equation Model (SEM) or VB-SEM. The research results show that having farmer characteristics, such as land area, business experience and level of education, has a significant direct impact on production. paddy. Even though agricultural business management has a relatively small impact, it is still important for agricultural efficiency and sustainability. Agricultural extension also plays an important role in increasing production, which involves several factors such as frequency of extension, appropriateness of materials, media and methods contributing to supporting increased rice production. This research highlights the complexity of the relationship between farmer characteristics, agricultural management and agricultural extension in the local agricultural context. The practical implications of this research include the importance of considering farmer education, optimizing agricultural holding management and improving the quality of expansion to achieve increased agricultural rice production. Regular monitoring and evaluation is also needed, identifying changes in these factors and adapting strategies according to the conditions and needs of farming communities. This research provides valuable insights for agricultural extension workers, farmers and stakeholders in local agricultural development to achieve better agricultural results and farmer welfare.
Sensory Properties of Yellow Pumpkin Dodol with the Addition of Soy Protein Isolate
Authors: Murtado Asep Dodo , Yani Ade Vera , Idealistuti Idealistuti , Prayoga Putri Regina
Published: August 2024

One of the traditional foods that is popular among several Indonesian communities is dodol. Processed food is made from a mixture of white glutinous rice flour, sugar, and coconut milk, which is boiled until it becomes thick and non-sticky with a dense and chewy texture.The aim of this research was to determine the best yellow pumpkin dodol based on sensory properties with the addition of soy protein isolate.The method used was a Randomized Block Design (RAK) method arranged in a non-factorial manner with five treatments, namely T0 (pumpkin dodol without the addition of soy protein isolate), T1 (addition of 2% soy protein isolate), T2 (addition of 4% soy protein isolate), T3 (addition of 6% soy protein isolate), and T4 (addition of 8% soy protein isolate). The research results showed that the addition of soy protein isolate had a significant effect on color,taste, and texturebut had no significant effect on aroma. The most preferred treatment was T0 (pumpkin dodol without the addition of soy protein isolate) with an average characteristic value of color (3.60) and aroma (3.48), the most preferred treatment was T1 (yellow pumpkin dodol with the addition of 2% soy protein isolate)with an average value of taste characteristics (4.16); and the most preferred treatment was T4 (pumpkin dodol with the addition of 8% soy protein isolate) with an average value of texture characteristics (4.24
Application of Biophosphate fertilizer on Peanut (Arachis hypogeae L) in Lowland
Authors: Rosmiah Rosmiah , Marlina Neni , Palmasari Berliana , Aryani Ida , Abd. Nasser Gamal
Published: August 2024

The lowland has the potential to be utilized for agriculture, such as planting peanuts, even though the soil fertility level is not very supportive The use of bio-phosphate fertilizers containing phosphate-solubilizing bacteria can be utilized to help improve the soil and contribute to nutrient elements The advantages of bio-phosphate fertilizers include protecting roots from Fusarium infect, optimizing inorganic fertilizers, and increasing peanut production This research was conducted in Pulau Semambu Village, Inderalaya Utara, Ogan Ilir Palembang from October 2023 to January 2024. The experimental layout used a non-factorial randomized block design with 6 treatments repeated 4 times The treatment factors included biofosfat fertilizer (B), namely B1 = 25 kg/ha, B2 = 50 kg/ha, B3 = 75 kg/ha, B4 = 100 kg/ha, B5 = 125 kg/ha, B6 = 150 kg/ha (B)
Pelatihan Public Speaking Bagi Mahasiswa Perguruan Tinggi Advent Surya Nusantara, Pematang Siantar
Authors: Nilamsari Natalina , Sitorus Kristina Berliana
Published: August 2024

Public speaking is a soft skill of communication science, which provides a primary guidance to be skilled speaking in front of audiences. For students of major in accounting at Perguruan Tinggi Advent Surya Nusantara (PTASN) in Pematang Siantar North Sumatera, this training provides benefits for self-development as well as preparation to impenetrate the realm of workplce or  profession. This was the reason for carrying out this community service activity, attended by 45 students. Activities in the form of training held on the PTASN campus for one day. During the training, participants were given material on public speaking and practice and were evaluated by the facilitator. Implementation of the program starts from the early observation, orientation, provision of learning material, practice and evaluation. The results of the training were considered good based on the participants' enthusiasm and their confidence’s when practice of public speaking .
Membangun Community relationss Dalam Perayaan Idul Qurban
Authors: Islami Dian Ismi , Ningsih Cakra , Sukarni Nurul Fadzar
Published: August 2024

The celebration of Eid al-Adha is a unifying celebration among human beings, the meat of qurban animals is not only intended for muslim or the poor, anyone can get the meat of qurban animals. The eid al-Adha moment can also be used as an opportunity to build relationships with the community. The purpose of this activity is a form of community service carried out by the academic community of Prof. Moestopo (Religious) in accordance with the third higher education tridarma, namely community service, fostering good realtion with the community, namely the qurban animal farming community and the beneficiary community of qurban animal as a form of responsibility in transferring and informing knowledge to the public. The implementation method starts with recruiting shohibul qurban, then collaborating with the qurban animal providers and qurban slaughterers, followed by wrapping the qurban meat and distributing it to the public. The results of the implementation of this activity can synergize well with community parties, and can educate the public about the procedures fo slaughtering qurban animal that are good and in accordance with Islamic law.
Pembimbing Keterampilan Dalam Meningkatkan Motivasi Belajar Tuna Daksa
Authors: Aisah Wulandari Siti , Yuwarti Harti , Arifin Kusnul
Published: August 2024

Penyandang disabilitas akan dihadapkan kepada persoalan bagaimana menyesuaikan diri pembimbing keterampilan Sentra Terpadu Inten Soeweno Bogor dengan upaya membangun motivasi belajar keterampilan yaitu dengan cara mendorong, memotivasi, dan membangkitkan kesadaran akan potensi yang dimiliki serta berupaya untuk mengembangkannya dengan dilandasi proses kemandirian. Tujuan penelitian ini untuk memberikan pembimbing keterampilan dalam pelatihan untuk  meningkatkan motivasi belajar tuna daksa dan Implementasi pelatihan pada tuna serta Peran pembimbing keterampilan di Sentra Terpadu Inten Soewono (STIS). Kegiatan ini dilakukan dengan tiga pembimbing keterampilan dan dua Tuna daksa. Hasil kegiatan menunjukan adanya peningkatan motivasi pembimbing keterampilan peserta tuna daksa ini yaitu dengan pendekatan khusus yang menumbuhkan chemistry, pembimbing juga harus menjadi keluarga, sahabat peserta tuna daksa. Mendorong peserta tuna daksa dalam pelatihan keterampilan sebagai komunikator yaitu menasihati secara halus dan sabar untuk dapat terus berlatih dengan peserta tuna daksa ini dengan menjaga psikis emotional pesertanya, serta perlu adanya figure orang tua dan figure orang sukses yang memiliki keahlian dan ketrampilan dalam menjalankan fungsional dengan berwirausaha.
Strategi Akusara Production Dalam Membangkitkan Dunia Event Virtual di Masa Pandemic
Authors: Hanafiah Wildan Anugrah , Krismasakti Bramayanti , Prihatiningsih Nunuk , Srisadono Wahyu , Adhypoetra R. Rama
Published: August 2024

Strategi Akusara Production dalam membangkitkan dunia Event Virtual di Masa Pandemic dengan cara memberikan kesadaran, pengetahuan dan kepercayaan kepada masyarakat dengan memanfaatkan media sosial Google. Pesan yang disampaikan di media sosial mengenai besarnya manfaat yang diperoleh klien dengan melakukan virtual event. Akusara Production juga menyampaikan pesan bahwa penyelenggaraan event virtual menghembat biaya lebih besar dibandingkan dengan event yang diselenggarakan secara langsung. Kualitas event virtual tidak kalah bagusnya dengan event secara langsung karena ditangani tenaga profesional dan sarana-sarana yang mendukung yang dimiliki perusahaan. Kendala yang dihadapi Akusara Production dalam membangkitkan dunia Event Virtual di Masa Pandemic adalah masalah kesadaran dan pemahaman masyarakat. Untuk permasalahan ini Akusara Production secara terus menerus dan konsisten memberikan informasi kepada masyarakat melalui media sosial Google. Digunakan media sosial ini karena media sosial memiliki jangkauan yang luas dan menjadi media komunikasi efektif untuk promosi virtual event. Antusias masyarakat untuk menyelenggarakan event virtual di masa pandemic oleh Akurasi Production memperoleh respon yang positif dari masyarakat. Adanya keinginan mayarakat ini dikarenakan pesan komunikasi yang disampaikan di sosial media sesuai dengan kebutuhan masyarakat yaitu sebagai perusahaan yang telah banyak pengalaman dan perusahaan yang profesional.
STRATEGI KOMUNIKASI PROGRAM ANTI STUNTING ANGGOTA DPR DI DAERAH PEMILIHAN (Studi Kasus Anggota Komisi IX DPR RI Darul Siska Daerah Pemilihan Sumatera Barat I)
Authors: Qadir Subki Abdul , Hadiati Hadiati , Intani Retno
Published: August 2024

Stunting merupakan salah satu masalah kesehatan yang serius di banyak negara, termasuk Indonesia. Angka prevalensi stunting yang tinggi dapat berdampak negatif pada perkembangan fisik dan kognitif anak-anak, serta produktivitas dan kualitas sumber daya manusia di masa depan. Sebagai perwakilan rakyat, anggota Dewan Perwakilan Rakyat Republik Indonesia (DPR RI) memiliki peran penting dalam mengatasi masalah stunting di daerah pemilihan. Tujuan dari kampanye stunting adalah untuk meningkatkan kesadaran dan pemahaman masyarakat terkait stunting. Strategi komunikasi anti stunting untuk anggota DPR di daerah pemilihan adalah langkah kunci dalam upaya mengedukasi dan menggerakkan tindakan untuk mengurangi angka prevalensi stunting. Strategi ini harus memperhatikan konteks budaya, sosial, dan ekonomi setiap daerah pemilihan. Konsep strategi komunikasi Harold Lasswell mengemukakan lima pertanyaan kunci dalam analisis komunikasi: "Who (Siapa)?", "Says What (Mengatakan Apa)?", "In Which Channel (Melalui Saluran Apa)?", "To Whom (Kepada Siapa)?", dan "With What Effect (Dengan Efek Apa). Hasil penelitian ini menunjukkan bahwa anggota Komisi IX DPR RI menggunakan berbagai strategi komunikasi dalam sosialisasi program anti stunting dengan menggunakan media massa, media sosial, pertemuan langsung dengan masyarakat dan kolaborasi dengan kelompok kepentingan terkait untuk menyampaikan pesan tentang pentingnya program anti stunting.
Examining the Detrimental Impact of “Kiss Up, Kick Down” Office Culture in Vietnam: A Qualitative Exploration using Grounded Theory
Authors: Pham Thuy Trut , Thao Le Thanh , Tran Thuy Thi
Published: August 2024

This study aimed to explore the “Kiss up, kick down” culture in Vietnamese educational institutions and understand its implications on teachers at different stages of their career: novice, mid-career, and near-end. Using a qualitative approach, 15 participants were interviewed. The thematic analysis of interview data resulted in the identification of fifteen themes. They highlighted a pervasive culture driven by power dynamics and hierarchy, impacting interpersonal relationships, job satisfaction, professional growth, and mental well-being. Additionally, the culture was found to align with societal norms and was seen as a reflection of the collective culture and historical influences in Vietnam. The study underscores the need for systemic change and offers insights that could inform policy and practice aimed at creating healthier and more inclusive academic environments.
Development of Comic-Based Integrated Science Teaching Materials for Fifth Grade Elementary School Students
Authors: Haris Muhammad , Akmaluddin  , Putra Mulia
Published: August 2024

Incorporating engaging and effective teaching materials is essential for enhancing student learning in science education. This research aims to develop comic-based integrated science teaching materials tailored for fifth-grade students, employing the ADDIE (Analysis, Design, Development, Implementation, Evaluation) method. The research and development process follows these five stages to ensure comprehensive material creation and evaluation. The results indicate high validation scores: 96% for material, 98% for language, and 96% for media, categorizing the comics as highly suitable for educational use. Student and teacher responses further affirm this suitability, with 90% and 94% approval rates, respectively. Evaluation of student test results shows an average score of 90.36, with 90% of students meeting the criteria for excellence. This study concludes that comic-based teaching materials significantly enhance student engagement and understanding of science, contributing valuable insights into educational resource development.
Developing Digital Comics Based on Local Wisdom for Fantasy Story Texts to Enhance Student Learning Outcomes
Authors: Mariani Rika , Novita Rita , Sari Siti Mayang
Published: August 2024

This research discusses the implementation materials Of comic-based teaching. This research aims to develop teaching materials for fantasy story texts based on local wisdom in the form of digital comics to improve the learning outcomes of fifth grade elementary school students. This research is research and development (R&D). In this research and development, researchers used the ADDIE method, Analysis, Design, Development, Implementation and Evaluation. The results of the development research show that the digital comic teaching materials based on local wisdom for grade V elementary school students produced are said to be very feasible. This is proven by the media expert validation results showing a very good category (96%) from the average validator. The material expert validation results show a very good category (96%) from the average validator. Linguist validation results show a very good category (98%) from the average validator. The results of the student response product trials showed the very good category (87.5%) and the results of the teacher response product trials showed the very good category (94%). In the evaluation of the test results, students obtained an average result of 89.71 with a percentage score of 90% with very good criteria with details of 28 students completing. This comic is a good idea for language learning based on students' interests and talents to improve their learning. The research results are proof that digital comic teaching materials based on local wisdom are very feasible and can be used as learning materials that can improve student learning outcomes.