Expert Assessment Research Articles

Complex Pythagorean Normal Interval-Valued Fuzzy Aggregation Operators for Solving Medical Diagnosis Problem

This paper presents a new methodology for solving multiple-attribute decision-making problems (MADMs) using a complex Pythagorean normal interval-valued fuzzy set (CPNIVFS), which is an extended concept of a complex Pythagorean fuzzy set. Four types of different aggregating operations (AOs), including CPNIVF weighted averaging (CPNIVFWA), CPNIVF weighted geometric (CPNIVFWG), generalized CPNIVFWA (CGPNIVFWA), and generalized CPNIVFWG (CGPNIVFWG), are discussed. The scoring function, accuracy function, and operational laws of the CPNIVFS are defined. Algebraic structures, such as associative, distributive, idempotent, bounded, commutativity, and monotonicity properties, are also shown to be satisfied by complex Pythagorean normal interval-valued fuzzy numbers. Furthermore, an algorithm is proposed to solve the MADM problems based on the defined AOs. The proposed approach is then used for a medical diagnosis problem about brain tumors because computer science and machine tool technology are among the most important components of brain tumor research. The five types of brain tumors diagnosed in these patients are gliomas, meningiomas, metastases, embryonal tumors, and ependymomas. Several types of treatments are available, which are often combined as part of an overall treatment plan. Brain tumors can be treated in various ways, including surgery, radiation therapy, chemotherapy, immunotherapy, and clinical trials. Based on the comparisons and options gathered, the most suitable treatment can be chosen. In this regard, it is evident that the value of the integer ⅁\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Game $$\\end{document} plays a significant role in determining the model. The candidate models under consideration can be validated by comparing them with the previously proposed ones. The proposed technique is compared with the existing method to demonstrate its superiority and validity, and the results conclude that the former is more reliable and effective than the latter. Finally, the criteria are evaluated by expert assessments to determine the most appropriate options.

NEUROPERSONALITY APPROACH TO THE ISSUE OF COGNITIVE SECURITY AS A NECESSARY CONDITION FOR WORK-RELATED SOCIALIZATION OF IT-SPECIALISTS

The post-classical paradigm of understanding the system of personality potentials due to virtualization and informatization of most spheres of natural life emphasizes the need to rethink the many positions of determining personal development and resourcefulness of specialists. The conceptual principles of cognitive security research of specialists in the field of IT technologies, whose professional activity is directly related to information culture, information, and cognitive security of others, need to be clarified. Methodology. An empirical study was conducted on two randomized groups of IT specialists. The groups are differentiated according to the criterion of professional experience. Accordingly, two groups were formed: EG1 (n 76) - IT specialists with experience of up to five years and group EG2 (n 83) - IT specialists with experience of more than five years (6-10 years). To generalize the structure of the relationship of categories that reveal the range of factors of cognitive-stylistic determination and neurodynamic conditionality of cognitive security of IT specialists, an expert evaluation was conducted. Research technology involved the assessment of IT experts (22 specialists with 15-22 years of experience) the importance of parameters that identified three main strategies for cognitive security of IT specialists Results. Sixteen neuropersonality types of solving professional problems and ensuring cognitive security of IT specialists differentiated by professional experience were identified. Three strategies of cognitive security of IT specialists: "Life-sustainability-strategicity", "Metacognitive knowledge - control over action" and "Positive refocusing - Metacognitive activity" are specified.

Northeast Atlantic fish stock productivity hindcasts and forecasts from a Bayesian framework reveal pronounced climate‐induced dynamics

AbstractClimate change continues to exert pressure on ocean ecosystems. The fisheries‐related responses, such as altered body growth, recruitment and spatial distribution of the targeted stock(s), have generally been reasonably well investigated. Nevertheless, there are still important knowledge gaps in how biophysical drivers impact stock productivity and thereby sustainable harvest levels. Considering this, we investigated 26 fish stocks in the Northeast Atlantic, a region characterized by accelerated climate change effects and a diverse set of fisheries. A novel, stepwise, Bayesian framework to quantify stock productivity was established to identify shared trends and project future patterns, aiming at determining essential baselines for adaptive fishery management in the face of climate change. Despite variation among large marine ecosystems and stocks, an overall declining trend in productivity over the past four decades was observed, especially in high‐latitude areas. These hindcast results were mainly attributed to higher temperatures posing negative effects on productivity, which was dependent on the stock's thermal preference. Contrastingly, the proxy for food availability – gross secondary production – exhibited less consistent impacts. In the forecast, the applied Shared Socio‐economic Pathways (SSPs) indicated that most stocks are likely to encounter adverse effects, with the worst cases expected to occur under SSP2‐4.5 in the 2050s, and under SSP5‐8.5 in the 2090s. Thus, this study generally not only supports earlier climate vulnerability assessments (‘scorings’) of experts but also provides evidence for revised directional effects under climate change, underlining the complexity of processes affecting stock productivity.

The ‘Implicit Intelligence’ of artificial intelligence. Investigating the potential of large language models in social science research

ABSTRACT Researchers in ‘hard' science disciplines are exploring the transformative potential of Artificial Intelligence (AI) for advancing research in their fields. Their colleagues in ‘soft' science, however, have produced thus far a limited number of articles on this subject. This paper addresses this gap. Our main hypothesis is that existing Artificial Intelligence Large Language Models (LLMs) can closely align with human expert assessments in specialized social science surveys. To test this, we compare data from a multi-country expert survey with those collected from the two powerful LLMs created by OpenAI and Google. The statistical difference between the two sets of data is minimal in most cases, supporting our hypothesis, albeit with certain limitations and within specific parameters. The tested language models demonstrate domain-agnostic algorithmic accuracy, indicating an inherent ability to incorporate human knowledge and independently replicate human judgment across various subfields without specific training. We refer to this property as the ‘implicit intelligence' of Artificial Intelligence, representing a highly promising advancement for social science research.

Pengembangan E-Booklet Berbasis Aplikasi Android Pada Sub Konsep Sistem Peredaran Darah Manusia Kelas XI SMA

Electronic booklets are learning resources that are in accordance with online learning conditions, the 2013 curriculum and IT advances in education. The research model used is 4D namely: 1) Define, 2) Design and 3) Development which then in the Development stage uses the Tessmer Formative Evaluation design namely 1) Expert assessment and 2) individual test 3) small group test. The subjects of the validity test were 2 Biology Education lecturers and 1 Biology teacher at SMA Negeri 4 Banjarmasin. The individual test subjects were 3 class XI MIPA 3 students at SMA Negeri 4 Banjarmasin and the small group test subjects were 4 students in the same class. The results of the study show 1) the validity of the Android application-based E-Booklet based on 5 aspects has a valid category; 2) the practicality of the contents of the Android application-based E-Booklet has attractiveness based on the responses of students in the at least good category, the practicality of the hope that the E-Booklet is easy to use based on the responses of students in the least good category; and 3) the effectiveness of expectations based on critical thinking assessments obtains a very good category in interpretation, analysis, evaluation, explanation, and self-regulation skills, and has a good category in the aspect of inference

Augmenting large language models with chemistry tools

AbstractLarge language models (LLMs) have shown strong performance in tasks across domains but struggle with chemistry-related problems. These models also lack access to external knowledge sources, limiting their usefulness in scientific applications. We introduce ChemCrow, an LLM chemistry agent designed to accomplish tasks across organic synthesis, drug discovery and materials design. By integrating 18 expert-designed tools and using GPT-4 as the LLM, ChemCrow augments the LLM performance in chemistry, and new capabilities emerge. Our agent autonomously planned and executed the syntheses of an insect repellent and three organocatalysts and guided the discovery of a novel chromophore. Our evaluation, including both LLM and expert assessments, demonstrates ChemCrow’s effectiveness in automating a diverse set of chemical tasks. Our work not only aids expert chemists and lowers barriers for non-experts but also fosters scientific advancement by bridging the gap between experimental and computational chemistry.

Logical Platforms for Mobile Application in Decision Support Systems Based on Color Information Processing

Logical Platforms for Mobile Application in Decision Support Systems Based on Color Information Processing

On the intrinsic recycling potential of carbon-based materials and products; an assessment method and outlook

In this paper we investigate the market size of all materials and products presently produced from (organic) carbon and we present a method to estimate the intrinsic recycling potential of these materials/chemicals as a function of their respective applications. The method is based on the expert assessment of a number of variables that are important within the different application categories and markets of the carbon-based materials/chemicals. Applying the method, the paper presents the recycling potential of all carbon-based products. Following, an estimation of the amount of new products that can be produced each year through recycling of discarded products is presented and the amount of carbon that needs to come from other sustainable sources to fulfil our demand for new products is calculated.We distinguish nine different categories of (organic) carbon-based materials/chemicals: plastics, textile fibres, thermoset resins, rubbers, surfactants, solvents, fine chemicals, paper/board and wood products. Within these nine categories the most important materials/chemicals types were taken into account. Fossil-based and bio-based materials/chemicals were assessed separately. For each of the materials/chemicals types, the market size in terms of mass (Mt) was calculated for the main applications in which they are applied. Next, for all materials/chemicals types in these applications, the maximum recycling potential, in case mechanical or physical recycling methods are applied, was assessed, using an expert panel. Also, inevitable leakage of materials/chemicals in the different applications was assessed. Finally, the amount of feedstock coming from recycling streams that may be made available for chemical recycling or carbon capture and utilisation technologies was derived. From this, the magnitude of carbon-based materials/chemicals that need to be replaced each year by other renewable feedstock than recycled content in terms of Mton carbon was calculated.The analysis is relevant in view of implementation of a circular economy and reuse and recycling of materials, to combat depletion of raw materials. Next, it is relevant in view of phasing out fossil-feedstock to combat climate change. Our analysis indicates that the recycling potential of carbon-based materials and products through mechanical or physical methods lies around 50%, even in a system that is fully optimised for recycling. Chemical recycling and carbon capture and utilisation may provide another 25% of the renewable-carbon feedstock needed, but they generally require far more energy and other inputs to produce new materials and chemicals than the mechanical and physical recycling methods. The remaining demand for renewable-carbon feedstock thus needs to come from either biomass or CO2 through carbon capture and utilisation technologies. Based on our findings, we argue that the composition of our present carbon-based products pool needs to be redesigned on a fundamental molecular level, towards material types that contain more oxygen. Carbon-based materials that contain more oxygen generally can be recycled more efficiently, and are also easier to produce from the alternative feedstocks biomass and CO2 through CCU.

Automated pneumothorax segmentation and quantification algorithm based on deep learning

A collapsed lung, also known as a pneumothorax, is a medical condition characterized by the presence of air in the chest cavity between the lung and chest wall. A chest radiograph is commonly used to diagnose pneumothorax; however, manual segmentation of the pneumothorax region can be difficult to achieve due to its complicated appearance and the variable quality of the image. To address this, we introduce a two-phase deep learning framework designed to enhance the accuracy of lung and pneumothorax segmentation from chest radiographs. Initially, a U-Net model with a ResNet34 backbone, trained on the Shenzhen and Montgomery datasets, is utilized to achieve precise lung region segmentation. Subsequently, for pneumothorax segmentation, we propose the PTXSeg-Net—a convolutional neural network model trained on the SIIM-ACR pneumothorax dataset. The PTXSeg-Net is an enhancement of the U-Net architecture, modified to incorporate attention gates and residual blocks to refine learning capabilities, further strengthened by deep supervision, allowing for more nuanced gradient utilization across all network layers. We employ transfer learning by pre-training an autoencoder to extract robust chest X-ray representations. Data refinement techniques are applied to the SIIM-ACR dataset to further improve training outcomes. Our results indicate that PTXSeg-Net outperforms other models in pneumothorax segmentation, achieving the highest Dice score of 0.9124 and Jaccard index of 0.8894 on the refined dataset with autoencoder pre-training. Moreover, leveraging the predicted lung and pneumothorax segmentation masks from the two-phase framework, we propose a quantification algorithm for estimating the pneumothorax size ratio. Its validity has been confirmed through expert assessments by a radiologist and a surgeon on a test set comprising 495 images. The high acceptance rates, averaging 96.97 %, demonstrate substantial agreement between the proposed method and expert clinical assessments. The implications of these results are significant for clinical practice, offering a deep learning technology for more accurate and efficient pneumothorax identification and quantification. This improvement facilitates the timely determination of required management and treatment strategies, potentially leading to enhancements in patient outcomes.

Deep learning-based model for difficult transfemoral access prediction compared with human assessment in stroke thrombectomy

BackgroundIn mechanical thrombectomy (MT), extracranial vascular tortuosity is among the main determinants of procedure duration and success. Currently, no rapid and reliable method exists to identify the anatomical features precluding...

Phylobook: a tool for display, clade annotation and extraction of sequences from molecular phylogenies.

As the volume of sequence data from variable pathogens increases, means of analyzing, annotating and extracting specific taxa for study becomes more difficult. To meet these challenges for datasets with hundreds to thousands of taxa, 'Phylobook' was developed. Starting with a sequence alignment file, Phylobook generates and displays phylogenetic trees adjacent to highlighter plots showing the position of mutations, and allows the user to identify lineages and recombinants, annotate and export selected subsets of sequences for downstream analysis. Accurate lineage assignment, which is difficult to automate, is aided using annotations created by different clustering methods. Phylobook provides web-based display combined with automated clustering and manual editing to allow for expert assessment and correction of lineage assignments and extraction for downstream analysis.

Potential of socio-humanitarian disciplines in training future engineers: students’ opinions analyzed

Introduction. Higher education is a key factor for societal development; new challenges associated with ultra-fast socio-technological transformations create new demands for professionals, especially in engineering. In addition to knowledge of natural and technical sciences, a modern engineer is to possess a wide range of so-called flexible competencies. In this regard, the issue of how these skills can be developed becomes particularly relevant. In particular, experts in higher education development believe that sociohumanitarian disciplines are indispensable for solving this issue. The study aims to assess the potential of socio-humanitarian disciplines in training future engineers and to outline proposals for optimizing their role in education. Research methods. The study had two stages: a comparative analysis of Russian and foreign research and expert assessments regarding challenges to modern engineering education, and an assessment of the influence that specific disciplines of engineering education have on its quality; a survey-research of 548 students of Saint Petersburg Mining University (Russian Federation). Research methods: survey, comparative analysis, pedagogical consultation. Research results. More than 60% of students positively assess the potential of socio-humanitarian disciplines, considering them essential for the development of a wide range of communication and cognitive skills. At the same time, 60% of students noted that the teaching methods used and the content of work programs do not always meet their expectations. Conclusion. The survey results confirm the opinion of experts that modern technical education is to be more practice-oriented and address current problems of modern society in order to be competitive. Based on the results of the study, proposals were formulated for solving the identified problems in engineering education.

Phenomenology of the inclusive potential of the family as a factor in socialization of children with disabilities

Introduction. The lack of tools for studying the potential resources and capabilities of the family, as well as the search for optimal strategies and mechanisms for the real inclusion of people with disabilities in all spheres of public life is on the current national and international agenda. Aspects of rehabilitation potential of the individual and the environment, educational potential, functionality and effectiveness of the family, competence, including inclusive competence, are considered for a comprehensive analysis of inclusive potential of families raising children with disabilities. The emphasis is shifted to understanding the potential of the family as a factor in socialization of children with disabilities. The article aims to systematize and scientifically analyze ideas about the potential opportunities and resources for the socialization of children with disabilities and their families, followed by justification of the criteria base and mechanism for assessing the inclusive potential of families. Materials and methods. Within the framework of interdisciplinary scientific discourse, a model of a criteria base and of mechanism for analyzing and assessing the inclusive potential of a family raising a child with disabilities is proposed. The basis for constructing such model is decomposition of groups of competencies through indicators of parental effectiveness based on formalization. Results and discussion. Based on the analysis of the terminological field related to assessing and developing family potential in matters of development and socialization of a child with disabilities, the author’s positions on ‘inclusive family potential’ are presented. Some socio-psychological phenomena are considered that reflect the capabilities and resources of both the children themselves and their social environment. Particular attention is paid to indicating the functional effectiveness of parents of children with disabilities. Conclusion. The discussed model for assessing the inclusive potential of families raising children with disabilities has a universal design, formed as a result of initial testing and expert assessment. This approach allows for a comparative analysis of individual indicators and assessment of the influence certain factors exert on the effectiveness of accompanying children of different categories of disabilities. Systematically analyzing individual groups of parents’ inclusive competencies allows optimizing their inclusion in comprehensive support of children with disabilities.

МЕТОДЫ ОЦЕНКИ ОЗДОРАВЛИВАЮЩИХ ФАКТОРОВ САНАТОРНО-КУРОРТНОЙ СФЕРЫ

Background. Preventive measures aimed at preserving the health of the country's population should be based on health-resort rehabilitation and treatment using the healing factors of health resorts. In this regard, the study, from the point of view of a systematic approach, considers the data availability assessment of the health-improving factors that affect the activities of the health resort sector in the regions of the country with prioritization of the activities of health resort The purpose of the study is to establish the data availability assessment of health-improving factors that affect the activities of health resort organizations. Material and methods. A retrospective analysis of the sources of official statistical data, the state cadastre systems of natural resources, the results of scientific research in the health resort sector and health resort organizations. The level of data availability assessment of the health-improving factors of health resorts is determined by the method of expert assessment. Results. It is proposed to take into account the system of healing factors affecting the health resort sphere in the following components: natural therapeutic potential (biomedical – meteorological characteristics, severity index, etc.) and natural resource – landscape conditions, mineral waters, therapeutic mud). Medical diagnostic and human resources potential is the medical and diagnostic base of health resorts, staff qualifications. Social and cultural potential is the quality of services provided for health resort treatment and rehabilitation, inextricably linked with social and cultural events, as well as the basis to carry out these events, and qualified staff of health resorts. The interrelation of the components is manifested in both internal and external relations of health resort organizations, awareness and degree of satisfaction with the services of health resort treatment of the population. Conclusion. The methods of assessing the healing factors are grouped, the methodology of an integrated approach – monitoring of health resort organizations and the possibility of establishing permanent contacts between healthcare institutions and health resorts of the country is proposed.

PENGEMBANGAN MEDIA BOOKLET BERBASIS SETS MATERI SUMBER ENERGI UNTUK MENINGKATKAN KEMAMPUAN BERPIKIR KRITIS SISWA SEKOLAH DASAR

Learning media is an object or tool which can be used as an intermediary by teachers and accepted by recipients, namely students, in the teaching and learning process so that learning can run effectively and efficiently so that learning objectives can be achieved according to the desired curriculum. This sets-based booklet media was created as an alternative in learning science subjects. This stage consists of: analyze, design, development, implementation and evaluation. The stages in implementing research and development activities are contained in the ADDIE model. The results of validation of sets-based booklet media were carried out by several experts, such as media experts, material experts and language experts. The media expert's assessment of this learning media is based on two aspects (1) Clarity and (2) Appearance is "Very Valid" based on the table, namely the assessment percentage is 97%. The material expert's assessment of this learning media is based on two aspects (1) Clarity and (2) Appearance is "Very Valid" based on the table, namely the assessment percentage is 90%. The linguist's assessment of this learning media is based on two aspects (1) Clarity and (2) Appearance is "Very Valid" based on the table, namely the assessment percentage is 90%. Based on the results of the n-gain test, the critical thinking abilities of class IV students obtained a total significant value of 0.85. The result obtained high criteria.

PENGEMBANGAN MEDIA BOOKLET PADA MATERI PERUBAHAN CUACA BERBASIS AUGMENTED REALITY MENINGKATKAN KETERAMPILAN BERPIKIR KRITIS SISWA KELAS III SEKOLAH DASAR

Integrated thematic learning is learning that is packaged in themes based on the integrated learning content. The aim of this research is to develop Augmented Reality-based Booklet media in order to further improve critical thinking skills of class III elementary school students. This research applied the research and development (R&D) method with ADDIE model which consists of 5 steps, namely analysis, design, development, implementation and evaluation. The instruments in this research are observation, interviews, tests and questionnaires. The data analysis technique used is quantitative descriptive analysis technique. The research results of this study can be seen from the average results of media experts for Augmented Reality-based Booklet media getting 4.95 which is stated "very feasible", the assessment of material experts getting 4.46 which is stated as "very feasible", and the assessment of language experts getting 4.4 which is stated "very decent". Based on the effectiveness of the media, teachers' responses received an average of 4.8 which was stated "very effective" while the pre-test and post-test results of class 3 students using the N-Gain test received an average of 0.87 in the "high" category. Based on the results of this research, it can be concluded that research and development of augmented reality-based booklet media can improve the critical thinking skills of third grade elementary school students.

STRATEGIC ASPECTS OF HUMAN RESOURCES MANAGEMENT IN THE CONTEXT OF MILITARY OPERATIONS: UKRAINIAN EXPERIENCE

The purpose of the article is to study the strategic aspects of human resource management in the context of military operations and to substantiate the ways to minimise the negative effects of permanent crisis phenomena. Theoretical research has shown that when quarantine is lifted and during martial law, it is not about increasing the company's efficiency, but about how not to lose it. The research forms the theoretical and methodological basis for the practical aspects of HR management under martial law, but further study is needed to adapt the methods of HR management of organisations and enterprises to the conditions of military operations. An important aspect of management is to create conditions for the development of innovation, team spirit and the pursuit of high quality. Encouraging employees to be flexible in the interests of an adaptive organisation and continuously improving the quality of work are key. In addition, it is important to maintain working conditions that guarantee a high level of employee health and safety. By summarising theoretical studies and expert assessments, the article provides general approaches to the development of a human resources management strategy in the context of armed conflict. In the context of a permanent armed conflict localised in certain regions, it is important to have sufficiently qualified and trained personnel capable of effectively performing the tasks assigned. It is substantiated that motivation and recognition are important factors of personnel management in organisations. Ensuring the safety of personnel is the main task in wartime. The importance of effective internal communications in wartime increases significantly. The conditions of armed conflict can change very quickly, making flexibility and adaptability important qualities in human resources management. Organisations need to be prepared for rapid changes in plans and objectives, as well as changes in staffing levels. Effective management and leadership can ensure staff cohesion and motivation and ensure that tasks are completed successfully. Organisations should be prepared for changes in plans and strategies, as well as in the composition of their staff. The use of integrated approaches to strategy development will help organisations to effectively manage their workforce in times of war and ensure the functioning of their organisations.

Toolkit for Integrated Assessment of Socio-Economic Development Scale of Urban Agglomerations

The formation of urban agglomerations in the Russian Federation is currently one of the most significant forms of spatial development both at the national and regional levels. The need to strengthen agglomeration processes is dictated by the provision of polarised socio-economic development of different territories of the country. Urban agglomerations in the Russian Federation receive legal status at the federal and regional levels. Institutional support for agglomerations is the development of an appropriate legal framework and financial mechanisms aimed at the infrastructural development of territories, improving the quality of human capital, scientific and technological development, etc. At the same time, recently the public authorities at the federal and regional levels have started to pay attention not only to large and largest urban agglomerations defined in the Strategy for Spatial Development of the Russian Federation, but also to smaller urban agglomerations. A special intensification of institutionalisation of the status of urban agglomerations is observed in the normative legal acts of many constituent entities of the Russian Federation. However, the methodological aspects of formation and development of urban agglomerations in the regions are not elaborated. The analysis of existing theoretical and methodological approaches to the study of agglomeration processes also revealed the lack of methods for analysing the scale of complex socio-economic processes of urban agglomerations. Therefore, the need to form a methodology for assessing the scale of agglomeration development in the regions of the Russian Federation determined the relevance of the study. The aim of the study is to develop an indicator of the scale of socio-economic processes of Russian urban agglomerations. To achieve this aim, the existing methodologies of urban agglomerations research, presented in the approaches of Russian and foreign scientists, were analysed. The analysis allowed us to systematise the existing methodological approaches into two groups: the features of spatial development of agglomerated systems and the characteristics of their economic condition. The advantages and disadvantages of the existing methodologies are presented, on the basis of which a methodological toolkit for the scale of agglomerated systems is developed. The conclusion is made about the possibility of using the proposed indicator by public administration authorities in the development of normative legal acts of strategic planning in the field of spatial and socio-economic development of regions, in scientific and analytical research in the field of regional economy. The methods of content and comparative analysis, mathematical formalisation, expert assessments, modelling, observation and synthesis were used to solve the research problems.

Development of Collaborative Learning-Based LKPD to Improve Collaboration Skills of Grade IV Elementary School Students

Collaboration skills are the skills of working together effectively. Ideally, students' collaboration skills are that they are able to work together in groups, respect others, and build good relationships with their peers. the results of observations made by researchers at SDN 01 Sukamaju show that the school applies the 2013 curriculum and the teaching materials used. However, in the implementation of learning, teachers do not involve students in learning activities (teacher centered), teachers also have not used a variety of learning resources and are less than optimal in using models in learning. In learning activities, the main sources or teaching materials are textbooks and LKPD. This study aims to analyze the effectiveness and attractiveness of the development of Collaborative Learning-based student worksheets. This research is a 4-D type R & D (Research and Development) development research (define, design, develop, disseminate) in this study researchers limit it to the develop stage, the sample used amounted to 70 students. The results showed a recapitulation of the assessment of material experts, media experts and design experts getting a percentage of 92% with very feasible criteria in the development of Collaborative Learning LKPD. The effectiveness of product development received a positive response with a value of 87.3% and very high criteria. The attractiveness of the developed product shows a value of 90.5% with a very high intervention from the attractiveness of the collaborative learning LKPD implemented by researchers to students

PENGEMBANGAN LEMBAR KERJA SISWA MATERI GARIS SUDUT BERORIENTASI ETNOMATEMATIKA SENI GERAKAN PENCAK SILAT GASMI

This research aims to describe the process and results of developing ethnomathematics-oriented teaching materials that are valid, practical and effective. This research uses the ADDIE development model which consists of 5 stages, namely analysis, design, development, implementation, evaluation. The instruments used include validation sheet, implementation observation sheet, student response questionnaire, and test question sheet. The subjects of this research were 16 class VII students at SMP Kartika IV-6 Ambulu. The quality of teaching materials viewed from the validity aspect is included in the valid category with the assessment average of media experts is 3.77 with valid category. Material expert assessment average is 3.87 with valid category. RPP validation assessment average is 4.08 in the valid category. Validation assessment average of implementation observations is 4.6 with very valid category. Student response questionnaire assessment average is 4,08 with valid category. Assessment average of test questions is 4.54 with a very valid category. The practical aspect of the LKS was obtained from the results of implementation observations with a score of 87.5% and the results of the student response questionnaire with a score of 84.62% with the category very practical. From the aspect of the effectiveness of the LKS, it can be seen from the student test results with a score of 86.67%. In this way, the ethnomathematics-oriented teaching materials developed meet the aspects of validity, practicality and effectiveness.