Data Sorting Research Articles

Measuring data access and re-use in the European Legal Framework for Data, from the General Data Protection Regulation (GDPR) law to the Proposed Data Act: the case of vehicle data.

This article delves into the difficulties and opportunities associated with the acquisition, sharing, and re-purposing of vehicle data, particularly information derived from black boxes used by insurance companies and event data recorders installed by manufacturers. While this data is usually utilized by insurers and car makers, it may benefit consumers, rival firms, and public institutions profiting from access to data for objectives such as data portability between insurance companies, traffic and transportation management, and the development of intelligent mobility solutions. Among other regulations, the authors examine the proposed Data Act as the European chosen champion to address the legal and technical hurdles surrounding the reuse of privately held corporate data, including privacy and intellectual property, competition, and data interoperability issues. The text also offers an overview of the sorts of data obtained through vehicle recording systems and their potential benefits for various stakeholders. This paper presents a methodology for comparing and evaluating, in an ordinal fashion, the degree of access conferred by various regulations and put it to practical use to assess how much data is currently left out from access by the existing legislation, how much of such data is covered by the Data Act, and ultimately, how much still remains inaccessible for reuse.

The Adoption of Information System Technology in Piloting the Current State of Health Institution in Tier Three Nations

This article is a pragmatic approach on the evaluation and implementation of the health information system as directed in assisting medical institutions to store patients’ health record in an electronic based method. In order to manage lots of information, the health information system comes in handy to sort data, processes and people. The system which consists of a set of interrelated components gathers, stores, and disseminates health or organizational related information of individuals working in the same health sector. All around the world the applications of digital health technology have become vital tools of modern information technology which has aided in the smooth and efficient delivery of quality healthcare. Studies have shown that the success of the electronic health information system implementation in developing countries is still low, and various reasons have however been identified as the cause of this poor outcome. This article is a pragmatic approach on the evaluation of information system technology adoption in the Nigerian health sector. The work focuses on factors that will determine the successful implementation of the health information system in health institutions in Nigeria, and how these factors can be enhanced using the Information System Quality Dimensions (Service Quality, System Quality, and Information Quality) as findings from this study show that attention should be on updating and upgrading the Information System quality dimensions (service Quality, Information Quality, and System Quality) since it reveals that there is a high dependence on these dimensions to bridge the research gap; as results show that there is an overall correlation between the analyzed variables.

Design of a Novel Convolutional Deep Network Model for Car Accident Prediction

Real-time collision risk estimation is thought to be essential to a sophisticated traffic management system. To swiftly determine accident probability is the goal of real-time crash risk prediction. However, due to the complex traffic situation on urban arterials, urban arterials were rarely included in previous studies, which mostly focused on highways. This paper suggests using Convolutional Deep Network model (CDNM) to forecast the probability of vascular accidents in real time. This model has the benefit of being able to use both LSTM and CNN. CNN retrieves the time-invariant characteristics, while LSTM captures the data's long-term dependability. To estimate the likelihood of an accident, many sorts of data are used, including weather, traffic, and signal timing data. There are also many other data preparation methods employed. The problem of data imbalance is also addressed by normalization which oversamples the crash cases. Using a variety of measures, the CDNM is enhanced on the training data and assessed on the test data. Five more benchmark models are constructed for model comparison. K-NN, ISVM, ANN, CNN, CNN-EVT and GAN are some of the models in this group. Experimental findings show that the proposed CDNM beats the competition in terms of sensitivity, specificity, accuracy, AUC and G-mean value. The findings of this paper demonstrate that CDNM can real-time prediction of crash risk at arterials.

Indiana University study highlights billions in annual losses from untreated MI in the state

Untreated mental illness in the Hoosier state comes at a cost of more than $4 billion a year, according to a new Indiana University study, the Daily Journal reported Nov. 1. The research published by the IU Richard M. Fairbanks School of Public Health found that one in five Indiana residents with mental illness do not receive the treatment they need. Hoosiers who do not receive such treatment are also more likely to experience other chronic health conditions, such as diabetes and cardiovascular disease, researchers said. The economic burden of untreated mental illness in Indiana is estimated to be $4.2 billion annually, including $3.3 billion in indirect costs — like unemployment and caregiving — $708.5 million in direct health care costs, and $185.4 million in non‐health care costs. The largest cost attributable to untreated mental illness was premature mortality, at over $1.4 billion. Productivity losses were estimated to cost $885 million each year. “The findings were published Oct. 13 in the Journal of the American Medical Association. Researchers worked with the Indiana Behavioral Health Commission to perform their analysis. Through the researchers' work, they developed a framework that allows Indiana to prioritize key areas in mental health services and treatment. The framework also provides Indiana with a baseline for tracking progress toward improvement efforts. The research was used in support of Senate Enrolled Act 1, which passed during the 2023 legislative session. The sweeping legislation will create a new mental health care system in Indiana, fortifying the relatively new 988 crisis response center and hotline with funding for mental health emergencies. The IU study population consisted of more than 6.1 million individuals of whom an estimated 429,000 had untreated mental illness in 2019, according to the research paper. “One of the most significant impacts of this research is that other states can use this framework to understand the financial burden in their state,” said Justin Blackburn, Ph.D., associate professor at the Fairbanks School. “There is a scarcity of data on the costs incurred by each state — especially by individuals, families and communities — from untreated mental illnesses in the United States. Policymakers, clinicians and employers need this sort of data to determine how we should allocate our societal resources.”

IIFS: An improved incremental feature selection method for protein sequence processing

MotivationDiscrete features can be obtained from protein sequences using a feature extraction method. These features are the basis of downstream processing of protein data, but it is necessary to screen and select some important features from them as they generally have data redundancy. ResultHere, we report IIFS, an improved incremental feature selection method that exploits a new subset search strategy to find the optimal feature set. IIFS combines nonadjacent sorting features to prevent the drawbacks of data explosion and excessive reliance on feature sorting results. The comparative experimental results on 27 feature sorting data show that IIFS can find more accurate and important features compared to existing methods.The IIFS approach also handles data redundancy more efficiently and finds more representative and discriminatory features while ensuring minimal feature dimensionality and good evaluation metrics. Moreover, we wrap this method and deploy it on a web server for access at http://112.124.26.17:8005/.

Directional sources and distributed acoustic sensing deployments for near-surface characterization

Active near-surface surveys using distributed acoustic sensing (DAS) have been practically limited to 2D inline acquisitions followed by Rayleigh-wave dispersion analysis. In this study, we analyze different acquisition setups and the subsurface properties that can be estimated from them. First, we find a surface survey dedicated to Love-wave acquisition. We use a horizontal source and common-receiver sorting of the DAS data for a pure Love-wave velocity dispersion analysis yielding an S-wave velocity profile. Common-receiver sorting has the added benefit of practically eliminating the effect of the gauge length. Next, downhole DAS is used in a vertical seismic profile-type survey to recover a 1D P-wave velocity through checkshot analysis. Finally, we find that the horizontal portion of a fiber deployed in a deviated borehole records high-frequency data from surface sources. We use first arrivals for diving-wave tomography, yielding a 2D P-wave velocity model above and below the fiber. We validate the inversion results of all acquisitions through a comparison with geophone-derived velocity models. We conclude that source orientation plays a crucial role and should be considered during survey planning in conjunction with DAS directivity. As anticipated, fiber coupling can strongly influence the signal-to-noise ratio and needs to be adequately planned. In vertical boreholes, infilling offers a viable solution for deployment in existing wells. For deviated boreholes, installation inside the casing yields suboptimal coupling, but more adequate deployment protocols may yield high-frequency data useful for velocity model building and imaging. From a practical point of view, the acquisitions that we describe are difficult to justify due to their operational costs and limitations. Nonetheless, they highlight the potential of DAS in going beyond traditional analysis.

BACKPROPAGATION ARTIFICIAL NEURAL NETWORKS PREDICTION OF ELEMENTARY SCHOOL STUDENT GRADUATION WITH EXAMINATION PRACTICE SCORE

Backpropagation method is a computer technique to help predict and sort data. This method is usually used to change the connection between parts of the computer's brain in the hidden layer. Meanwhile, the Nervous System Network (ANN) is an information processing system that is very similar to the function of human brain cells. Value is a benchmark for a student's graduation, if the student'sscore is getting better, the more opportunities for the student's graduation. In predicting this pass using the method of Artificial Neural Networks (ANN), namely Backpropagation and using Matlab software with the MSE (Mean Square Error) result of 0.099512. Keywords: Graduation Prediction, Backpropagation, Examination Practice Value, Artificial Neural Networks, Matlab

Detection of 3D Object in Point Cloud: Cloud Semantic Segmentation in Lane Marking

Managing a city efficiently and effectively is more important than ever as growing population and economic strain put a strain on infrastructure like transportation and public services like keeping urban green areas clean and maintained. For effective administration, knowledge of the urban setting is essential. Both portable and stationary laser scanners generate 3D point clouds that accurately depict the environment. These data points may be used to infer the state of the roads, buildings, trees, and other important elements involved in this decision-making process. Perhaps they would support "smart" or "smarter" cities in general. Unfortunately, the point clouds do not immediately supply this sort of data. It must be eliminated. This extraction is done either by human specialists or by sophisticated computer programmes that can identify objects. Because the point clouds might represent such large locations, relying on specialists to identify the things may be an unproductive use of time (streets or even whole cities). Automatic or nearly automatic discovery and recognition of essential objects is now possible with the help of object identification software. In this research, In this paper, we describe a unique approach to semantic segmentation of point clouds, based on the usage of contextual point representations to take use of both local and global features within the point cloud. We improve the accuracy of the point's representation by performing a single innovative gated fusion on the point and its neighbours, which incorporates the knowledge from both sets of data and enhances the representation of the point. Following this, we offer a new graph point net module that further develops the improved representation by composing and updating each point's representation inside the local point cloud structure using the graph attention block in real time. Finally, we make advantage of the global structure of the point cloud by using spatial- and channel-wise attention techniques to construct the ensuing semantic label for each point.

Machine learning based data collection protocol for intelligent transport systems: a real-time implementation on Dublin M50, Ireland

The continuous global urbanization with rapid and dynamic transitioning in traffic situations among highly populated cities results in difficulty for data collection and communication. Data collection for millions of vehicles hinders by various problems, i.e., higher cost of energy, time, space, and storage resources. Moreover, higher data traffic results in higher delays, larger throughput, excessive bottlenecks, and frequent repetition of data. To better facilitate the aforementioned challenges and to provide a solution, we have proposed a lightweight Machine Learning based data collection protocol named ML-TDG to effectively deal with higher data volumes in a real-time traffic environment capable of bringing the least burden on the network while utilizing less space, time, and energy. ML-TDG is functional based on Apache Spark, an effective data processing engine that indexes the data based on two logs, i.e., old commuters or frequent/daily commuters and second new/occasional commuters. The proposed protocol’s main idea is to utilize real-time traffic, distinguish the indexes in parallel based on two assigned logs criteria to train the network, and collect data with the least sources. For energy and time optimization, dynamic segmentation switching is introduced which is an intelligent road segments division and switching for reducing bottlenecks and replication. ML-TDG is tested and verified on Dublin, Ireland’s busiest motorway M50. ML-TDG performs the data collection, data sorting, and network training to decide the next execution altogether for better optimization every time. The experimental results verify that our proposed protocol is attaining higher performance with lower resource requirements along with rich and time-efficient sustainable data collection clusters in comparison with baseline protocols.

Description of the Role of Islamic Religious Education Teachers in Developing Students' Akhlakul Karimah

Purpose of the study: The purpose of this study was to find out the description of the teacher's role in shaping the akhlakul karimah students at the Junior High School Methodology: The method in this research is a quantitative method. Data analysis is the process of organizing and sorting data into patterns, categories, and basic descriptive units so that hypotheses can be found and formulated as suggested by the data. Main Findings: The results showed that the teacher's role is very important to form students' akhlakul karimah. The importance of having akhlakul karimah for students is to be able to always coexist and be harmonious. By having good morals, of course someone will not dare to do damage. Good morals will be a fortress, will be a shield or protector in every step of life. Novelty/Originality of this study: The teacher's efforts in instilling akhlakul karimah to students through several methods, namely, exemplary, advice, motivation, punishment, habituation, gift giving, and supervision. The teacher supervises student behavior both in the school environment and outside the school environment. So that the role of the teacher is very important in shaping student morality.

Approach to Evaluate the Data of Moss Biomonitoring Studies: Preprocessing and Preliminary Ranking

This paper, dedicated to Acad. Florin Gheorghe Filip, at his 15th anniversary as the Chairman of the Information Science and Technology Section of the Romanian Academy, suggests an approach to describe the data obtained in biomonitoring studies using mosses, on the example of the Republic of Moldova. In total, 33 moss samples were collected on the territory of Moldova, the elemental composition of which was determined by neutron activation analysis and atomic absorption spectrometry. At the first stage of the work, a correlation analysis was carried out with the ranking of data in the order of decreasing total correlation, which made it possible to preliminarily reduce the number of elements to two factors. At the stage of data sorting, iron, the content of which in the environment can be associated with anthropogenic activity, was chosen as the element determining the rank. The next stage of work was data smoothing using a discrete cosine transform, for which the codes were rewritten and the algorithm was ported to the Excel-VBA environment, which is most suitable for preprocessing and graphical display of experimental data. Also, an algorithm was developed for determining the number of linearly independent (basis) vectors in which the matrix itself can be decomposed. Two principal roots were identified, of which the larger one is several thousand units, and three lower roots, which are less than unit were excluded, since their absolute values differ by two to three or more orders of magnitude downward from the eigenvalues of the influencing components. The paper is dedicated to Acad. Florin Gheorghe Filip, at his 15th anniversary as the Chairman of the Information Science and Technology Section of the Romanian Academy, and at his 75th anniversary.

O.4.5-4 What do young people want in a sport program: formative evaluation using Concept Mapping

Abstract Purpose Engaging young people in sport and physical activity (PA) requires awareness of their preferences and priorities. This study provided less active young people (14–17 years of age) with an opportunity to articulate their perspective on an ideal sport program. Methods We used online concept mapping, involving qualitative data collection and quantitative data analysis. Forty-eight less active young people in regional Victoria, Australia brainstormed 65 relevant, unique and single-focus statements in response to the prompt: The features of a sport program that I would really like to participate in are…. Twenty-four participants then sorted these statements into groups based on similarity of meaning, and 37 participants rated each statement on 5 point Likert scales for its importance (1 = completely unimportant; 5 = very important) in a program and how common (1 = never; 5 = always) it is in the programs they participate in. We analysed sorting data using multi-dimensional scaling and hierarchical cluster analysis, and rating data using descriptive statistics. Results We identified a map with the following nine clusters (in order of relative mean importance ratings)—access and convenience (mean importance rating = 4.11 out of 5; mean common rating 3.83 out of 5); social connection (3.98; 3.78); inclusion and belonging (3.98; 3.53); confidence (3.86; 3.46); design and structure (3.85; 3.65); skill development and goals (3.84; 3.60); cost and time (3.80; 3.30); age and gender (3.61; 3.41); and specific features (3.53; 3.25)—as the most appropriate representation of the participants’ sorting data. The two single statements—both in the inclusion and belonging cluster—rated most important were a sport program where you are accepted (4.57) and in which you do not feel judged (4.51). Conclusions Young people want affordable, accessible, convenient, safe, welcoming, socially engaging and inclusive sport and PA programs. They want programs to be well organised, delivered by experienced coaches with flexible content that builds their confidence, fitness and skills through challenging and fun activities. Youth sport and PA program designers can use this data to inform program development and delivery planning. Support/Funding Source Victorian Health Promotion Foundation (VicHealth).

Cognition, attitude and abuse tendency for new type drugs and influencing factors in middle school students in Hainan Province

Objective: To investigate the cognition, attitude, abuse tendency for new type drugs and influencing factors in middle school students in Hainan Province, and evaluate the effect of health education about drug use prevention in teenagers. Methods: A cross-sectional survey design and stratified cluster random sampling method were used to select 36 middle schools in Hainan to conduct an anonymous questionnaire survey in students of all grades. The estimated sample size was 1 680.The information collected by the questionnaire included students' basic information, attitude to new drugs, abuse tendency and acceptance of prevention education. EpiData 3.1 software was used for data entry and sorting, and SPSS 22.0 software was used for statistical analysis. Results: A total of 45 919 students were surveyed, averagely, they knew 2.87 kinds of new type drugs. The students' cognition of traditional drugs was higher than that of new type drugs. Friends or close friends using new type drugs, the low cognition level of new drug types were the risk factor for new type drug abuse. The acceptance rate of health education against drug use was 90.33% (41 480/45 919), and averagely, the students participated in 3.36 kinds of health education activities against drug abuse. The main channel for the students to acquire anti-drug knowledge was anti-drug lectures (80.00%, 33 186/41 480). Conclusions: Middle school students have low cognition level of new type drugs in Hainan. Health education can effectively curb the tendency of substance abuse in Hainan Province. It is necessary to further improve the health education activities in aspects of stage, form and timeliness to help more students to recognize the harm of drugs.

Usulan Perbaikan Tata Letak Fasilitas Pada Area Produksi Menggunakan Metode From to Chart (Studi Kasus: PT. Ibrahim Bin Manrapi)

An industry, both in the help and assembling areas, unquestionably has a few offices to help its creation cycle. Office design connects with the area, format, floor plan, equipment, and exercises related with the work environment. Different sorts of data from research led by finishing direct discernments and assessments made by areas on organizations taking part in the assembling of woven sarong materials at PT. Ibrahim Bin Manrapi which is situated on Jl. Malik Ibrahim Gresik, 24-26. in view of the discoveries of the examination of PT. In terms of format prior to design planning, PT. Ibrahim Bin Manrapi 's container is that there are still many areas that are not utilized to their full potential, and there are still many distances between offices that must be expanded as much as possible. From the technique for making the stream before the platform, there is a material conveyance distance of 102 m. Given the effect of information the board from the issues seen by PT. Ibrahim Bin Manrapi saw a lack in the plan so the gathering cycle went poorly and the conveyed item couldn't be anticipated to be great. This course of action should be possible by arranging the arrangement of the assembling office utilizing the From To Chart (FTC) procedure to restrict forward and backward during the assembling cooperation (Backtracking).

Data Trustees – They Do Work! The Example of Research Data Centers

This contribution presents the long established system of accredited Research Data Centers (RDCs). Created in the data-landscape of the social, behavioral, educational, and economic sciences, they enable access to restricted data and bridge interests of data providers and researchers. A distinctive feature of most research data in the above disciplines is the coverage of real persons. Such sensitive data require specific safeguards. The focus of this contribution is on the institutionalized processes of connecting and securing appropriate research data management strategies for this sort of data. It includes quality assurance measures through the accreditation of RDCs, a monitoring system and the regular cooperation of accredited RDCs.

“Technically an abortion”: Understanding perceptions and definitions of abortion in the United States

Anti-abortion legislation in the United States exploits misinformation and ignores medical definitions to curtail access to essential healthcare. Little is known about how individuals most likely to need this care define abortion, in general or as distinct from miscarriage, and how this might impact access to, utilization of, and experiences of care. Using mixed-method card sort and vignette data from cognitive interviews (n = 64) and a national online survey (n = 2009), we examined individuals’ understandings of pregnancy outcomes including abortion and miscarriage.Our findings show that people hold varying ideas of what constitutes an abortion. Many respondents considered ‘intent’ when classifying pregnancy outcomes and focused on intervention to distinguish between miscarriages and abortions. Particularly, medical intervention was found as a defining feature of abortion. Lack of knowledge regarding pregnancy experiences and ambiguity surrounding early stages of pregnancy also influenced respondents' understanding of abortion.We find that abortion and miscarriage definitions are socially constructed and multi-layered. Advancing our understanding of abortion and miscarriage definitions improves reproductive health research by elucidating potential areas of confusion that may lead to misreporting of reproductive experiences as well as highlighting ways that blurred definitions may be exploited by abortion opponents.

Juridical Analysis of Criminal Perpetrators of Electronic Gambling Transaction Information

The aim and use of the research is to analyze the legal regulation of gambling crimes. To analyze the Tangerang District Court Decision No.794/Pid.Sus/2018/PN.Tgn. against perpetrators of ITE crimes. To analyze legal obstacles in dealing with perpetrators of ITE crimes. The research method uses normative law which places law as a system of norms, regarding principles, norms, rules of statutory regulations, and court decisions. Data collection techniques in research include primary, secondary, and tertiary legal materials. Data analysis is the process of analyzing and sorting data into patterns, categories, and basic units of description so that themes can be found and formulated. Conclusion: The legal regulations for gambling crimes in Indonesia are regulated in the provisions of Articles 303 and 303 bis of the Criminal Code, Law no. 7 of 1974 concerning the Control of Gambling. analysis of the evidentiary system in force in Indonesia is that the Tangerang District Court judge in decision no. 794/Pid.Sus/2018/ PN.Tgn. Obstacles to law enforcement for perpetrators of special gambling crimes committed online consist of internal factors such as lack of mastery and understanding of information technology, means and facilities for finding evidence, and servers created by online bookies which are often located in countries where it is legal. gambling, as well as the ease of downloading VPN applications by online gambling players

PENDIDIKAN PLURALISME DALAM MEMBANGUN JATI DIRI BANGSA (Perspektif Agama Hindu)

A country that has multiethnic and multimental uniqueness like Indonesia is faced with its own dilemma, on the one hand bringing Indonesia to become a great nation as a multicultural nation-state, but on the other hand it is a threat. So it is not an exaggeration to say that multicultural conditions are like coals in husks which are easily ignited and heat up at any time. Indonesia has great potential for conflicts between groups, ethnic groups, religions and ethnic groups. One of the indications is that various social, professional, religious, and organizations or groups have started to thrive and are struggling and acting on behalf of group interests which lead to SARA (ethnic, religious, racial and inter-group) conflicts. To produce valid and reliable data, this paper uses a qualitative writing style. In producing logical data, this paper performs several stages of data sorting in the form of: 1). Data reduction, 2). Display data, 3). Verifying data, and 4). Interpreting research data. In its presentation, measurable analysis becomes the basis for processing the data obtained. The perfection of this paper cannot be separated from the library technique which is carried out through an assessment of the existing literature on Google Scholar. Education is the spearhead that is able to restrain and eradicate all harmful doctrines of non-plural and non- multicultural actions which are very appropriate to be applied in the current era in preventing interests and combinations of intolerant understandings in the name of a religion. Strategies in school and implementing a curriculum that emphasizes pluralism and multiculturalism in the current era are very important to be followed up immediately so that misleading intellectual understanding does not multiply ingrained in students' understanding. The role of parents and teachers must be able and synergized in implementing an understanding of the concept of plurality and the plurality of a life so that later students or students understand differences and are able to re-instill heterogeneity. Hinduism in the scope of analysis of pluralism education highly appreciates social diversity. The concept of Hinduism which incidentally is very plural and in its holy book contains teachings about realizing tolerance, namely Widya, Maitri, Ahimsa, and Santi.

Defining The Pattern of the Thai Osteoarthritis Movement Data Model

This study proposed an algorithm to identify the patterns of Thai osteoarthritis, a condition that has seen an increase in prevalence in recent years, significantly affecting patients' quality of life and mobility. We aimed to define the data patterns for analysis. For data collection, we employed a Razor-IMU sensor and a WIFI transmitter, allowing testers to independently perform full-range knee motions. Data collection was categorized into two groups: healthy and unhealthy. Our goal was to categorize the data and establish criteria for pattern classification. Once the patterns and criteria were established, our objective was to validate movement models for both normal individuals and osteoarthritis patients. To achieve this, we conducted statistical hypothesis testing to verify the accuracy of the data. This testing comprised three main steps: first, evaluating the accuracy of data collection and data cleaning. Second, assessing the precision of converting data from linear to angular format, including degree coordinates selection. The last, Evaluating the accuracy of data sorting and grouping using Louvain clustering. The researcher thoroughly scrutinized each step to confirm the results. Each step demonstrated an accuracy test As Thailand transitions into an aging society, the prevalence of osteoarthritis is increasing due to the natural deterioration of the body. This deterioration can be decelerated by avoiding risky behaviors. Osteoarthritis significantly impacts patients' physical and mental well-being, making it a critical health concern. The objective of this research is to develop movement prototypes for both normal individuals and osteoarthritis patients by leveraging computer knowledge. This includes data collection with motion sensor devices, enhancing data quality using data mining techniques such as data cleaning and data transformation into suitable formats, and grouping of data. Additionally, the study seeks to validate the accuracy of the algorithm using statistical hypothesis testing methods and graph pattern detection. Based on the experimental results, an accuracy rate of 97% was achieved, demonstrating a high level of reliability. This prototype can be applied in treatment analysis, monitoring treatment outcomes, and even injury prevention. Furthermore, the dataset can serve as a model for the Thai population and can be expanded to accommodate larger datasets.

DEEP MIND MAPPING MODEL IMPLEMENTATION DEVELOP CHILD CREATIVITY

<p style="margin: 0cm 0.65pt 0pt 0cm; text-align: justify;"><span style="letter-spacing: -0.05pt; font-family: 'Cambria','serif'; font-size: 12pt; mso-ascii-theme-font: major-latin; mso-hansi-theme-font: major-latin;">Children's creativity is a potential that must be developed through the educational process. This study aims to describe the implementation of the mind mapping model in developing children's creativity in akidah akhlak lessons. This study uses a qualitative approach with a descriptive study method. The background of this research is in SDN 068003. Observation techniques, interviews, and document studies are three research data acquisition techniques. Then, the data were analyzed using an interactive analysis model, through the steps of data collection, data sorting, data presentation, and drawing conclusions. The results of this study indicate that the application of the mind mapping model makes it easier for educators during the thematic learning process, because it stimulates students to develop their creativity based on the spirit of group learning. Likewise, there are obstacles in implementing the learning model, namely the low focus of students in group activities, difficulties for teachers to control student learning behavior, and some students like to disturb their friends.</span></p>