Objective Analysis Of Data Research Articles

Combined GIS, FR and AHP approaches to landslide susceptibility and risk zonation in the Baso Liben district, Northwestern Ethiopia

In mountainous places, landslides pose severe environmental threats, weakening infrastructure, resulting in death and costing the economy. This article assesses landslide susceptibility and risk in the Baso Liben district of Northwestern Ethiopia using an analytical hierarchy process (AHP) and Geographic Information System (GIS)-based Frequency Ratio (FR). Eleven key environmental and geological components— height, slope, lithology, soil type, and land use—were studied. After field research and Google Earth photos, 342 landslide incidents were collated and separated into validation (30%) and training (70%) datasets. ROC curves provide a technique for analyzing the efficacy of the FR and AHP models. With an Area Under the Curve (AUC) value of 83.4%, the AHP model exhibited superior accuracy than the FR model, with an AUC value of 74.4%. Very low, low, moderate, high, and very high vulnerability are five categories defined as landslide hazard zones. The AHP model assessed 10.5% of the area as very high risk, 19.8% as high danger, 25.6% as moderate risk, 28% as medium risk, and 16.1% as very low risk. The FR model meanwhile assessed 10.16% of the area as very high risk, 21.3% as high risk, 28.9% as moderate risk, 22.5% as low risk, and 17.04% as very low risk. The results reveal that slope angle, lithology, and elevation are key factors impacting landslide vulnerability. These findings equip a practical framework for land-use planning and disaster risk reduction, providing decision-makers with appropriate instruments to help lessen landslide hazards. The research underscores the significance of combining objective data analysis with expert knowledge to enhance the accuracy and reliability of landslide susceptibility models.

Relationship between temporomandibular and sleep disorders in adults: An overview of systematic reviews

ObjectiveThis study emphasizes the general relevance of sleep disorders (SD) and temporomandibular disorders (TMD), explores their bidirectional relationship, and describes the importance of systematic reviews in the critical analysis of the literature. This review aimed to comprehensively summarize the relationship between SD and TMD in adults while ensuring a reliable and objective analysis of data from the existing literature. MethodsSystematic reviews were evaluated to investigate this association between two conditions in adults. The study was registered with Prospero and followed the PECOT structure in identifying the research question. Searches in multiple databases were conducted until February 2024 using relevant keywords. The risk of bias was assessed using the Risk of Bias in Systematic Reviews tool, involving two independent reviewers. ResultsData were extracted using different evaluation instruments, and results were analyzed and presented through the synthesis of information collected in selected systematic reviews. The selection included seven systematic reviews of observational studies, with exclusion criteria defined to ensure methodological quality. The results showed that reviewed studies presented clarity and relevance in defining the eligibility criteria, but that the identification and selection of studies, data collection, and synthesis of results varied. Most studies considered the potential risks, but some require greater transparency and methodological rigor. ConclusionsThis review points out the association between SD and TMD in adults, with most studies presenting a low risk of bias, although some uncertainties were observed.

Effectiveness of Sciatic Nerve Gliding with Hip Abductor Muscle Strengthening in Software Professionals Suffering from Piriformis Syndrome

Background: Piriformis syndrome is a neuromuscular disorder where the sciatic nerve is compressed or irritated by the inflammation of piriformis muscle representing pain, tingling and numbness in the buttock region and in the course of sciatic nerve. Piriformis syndrome can be painful, but it is very rarely alarming and needs surgical interventions. It can be managed effectively by conservative means such as NSAIDS, analgesics and physiotherapy interventions like stretching, electro therapeutic modalities, myofascial release, thermo therapies, etc. The purpose of this study is to compare the effect of sciatic nerve gliding exercise with hip abductor strengthening exercises versus piriformis stretching exercises in software professionals who are sitting for prolong hours in office and diagnosed with piriformis syndrome. Materials & Methods: 30 patients with piriformis syndrome, reporting at the OPD of Physiotherapy Department were evaluated according to the inclusion and exclusion criteria and were divided into Group A (experimental) N=15, Group B (control) N=15 randomly. Their baseline data with respect to age, sex, pain in VAS, hip internal rotation range by goniometer, and disability evaluation by MODQ were taken on day 1 of the treatment and day 15 of the treatment. Data analysis was done by Mann Whitney ‘u’ test for subjective data and unpaired ‘t’ test for objective data analysis with 95%confidence interval. Results: The patients treated with sciatic nerve sliding exercise and abductor strengthening (Group A) showed statistically significant decrease in pain (p=0.00), increase in range of motion for hip internal rotation (p=0.00) and decrease in disability level according to MODQ (p=0.00) after 15 days of interventions as compared to Group B who were treated by piriformis stretching exercises. Conclusion: This study has shown significant improvement in the experimental group (group A) in respect to pain relief, hip internal rotation range of motion, and .......

Data extension of high-resolution wind speed database by fusing meteorological observation and local objective analysis data with POD–LSE

Newly generated high-resolution meteorological reanalysis data have been published over the past few years on short records. Producing high-resolution data in long-term time scales is challenging due to high computational costs and complex weather models. In contrast, urban meteorological observations have been continuously recorded for decades, although at a low spatial resolution. This study proposes a data fusion method using Proper Orthogonal Decomposition (POD) and Linear Stochastic Estimation (LSE). It fuses meteorological observations and high spatial resolution local objective analysis (LA) data to reproduce a high-resolution and long-term fusion database for urban areas without observations. First, the accuracy of LA data was verified by comparison with meteorological observations. Subsequently, the accuracy of the generated fusion data was investigated by comparison with Doppler lidar observations. Finally, the performance of single- and multi-time LSE in data fusion is discussed. These results indicate that the proposed method generates high-resolution and long-term fusion wind speed data that are similar to the Doppler lidar observations. In addition, the fusion model built using hourly data can accurately generate a highly sampled database at 10-min intervals. The single-time LSE method is recommended to be applied over the multi-time delay method for data fusion.

Oral Hygiene Profile of Schoolchildren from Bucharest, Romania-How It Can Be Used and Improved for Better Prevention of Oral Diseases.

Oral hygiene is essential for low caries or gingivitis prevalence in children. This study aimed to determine the oral hygiene profile of children from secondary schools (10-17 years) in Bucharest, Romania, and to explore options for preventing their future oral diseases. The study was cross-sectional, with a sample of n = 1595 pupils. The sample was stratified by clusters in city areas, grades, and the criterion of the presence/absence of in-school dental service. Dental check-ups were performed by using a commune dental examination kit. The oral hygiene simplified index (OHI; Silness and Löe) was used to assess the children's oral hygiene status. Five questions were used to determine oral hygiene habits. The mean value of the OHI was 1.04. Some differences in oral hygiene scores were found for different socioeconomic variables, such as parents' education (p < 0.05): parents with vs. without a university degree-0.95/0.94 (male/female) vs. 1.06. Most of the children used manual toothbrushes (88%). The analysis of objective data (OHI) revealed a good level of oral hygiene, with many socioeconomic disparities.

The influence of rural tourism landscape perception on tourists’ revisit intentions—a case study in Nangou village, China

Rural tourism development has an important impact on optimizing the rural industrial structure and stimulating local economic growth. China’s Rural Revitalization Strategy has promoted the development of rural tourism nationwide and emphasized Chinese characteristics in the process of local development. Based on the theoretical analysis of landscape perception, this article uses the external Landscape Perception→Satisfaction→Revisit Intention influence path as a theoretical research framework to construct a structural equation model to analyze the willingness of tourists to revisit rural tourism destinations. We selected Nangou Village, Yan’an City, Shaanxi Province, as a key model village for rural revitalization, and conducted an empirical analysis. The empirical analysis results show that landscape perception has a significant positive impact on satisfaction and revisit intention. Tourist satisfaction has a significant positive impact on revisit intention and plays an intermediary role between landscape perception and revisit intention. The five dimensions of natural ecology, historical culture, leisure recreation, research experience, and integral route under landscape perception are all significantly positively correlated with revisit intention, with historical culture and integral route having the greatest impact on landscape perception. The survey about Nangou Village verifies the relationship between landscape perception, satisfaction, and tourists’ revisit intention. Based on the objective data analysis results, this study puts forward suggestions for optimizing Nangou Village’s tourism landscapes and improving tourists’ willingness to revisit from three aspects: deeply excavating rural historical and cultural resources, shaping the national red culture brand, and creating rural tourism boutique routes. It is hoped that the quantitative research method of landscape perception theory in Nangou Village can also provide a reference and inspiration for similar rural tourism planning.

도시의 공간 패턴 분석을 통한 메타버스 기반 근접성 향상 실용화 방안 연구

This study proposes a method for addressing the limitations of physical proximity in real-world walking environments and focusing on Metaverse-based solutions. The first phase of the research entailed a community analysis centered on locations in Daejeon, through which problematic areas were identified and defined. The second phase involved conducting a survey among users of the Metaverse environment to explore methods of enhancing proximity. Based on these findings, the study developed three approaches to improve proximity in a Metaverse-based environment. It emphasizes the importance of objective data analysis and precise problem definition, underscoring the necessity of developing and designing solutions within the Metaverse environment. Moreover, the study suggests that to enhance user experiences in the Metaverse, a thorough analysis of regional characteristics is essential, followed by the development of tailored Metaverse solutions.

TRANSFORMASI MANAJEMEN SDM MELALUI SISTEM DATABASE TERINTEGRASI (STUDI KASUS YAYASAN PENDIDIKAN X BANDUNG)

This research aims to provide insights into the role of systems in transforming the operational business processes of the foundation. In the increasingly advanced digital era, integrated database systems have become a key infrastructure in the operations of various industrial sectors, including the education sector. The X Education Foundation in Bandung utilizes a database system to transform business processes and optimize efficiency in Human Resource (HR) management. This research uses a descriptive quantitative approach with data collection methods in the form of systematically designed questionnaires using proportional purposive sampling techniques. The research results show that there has been a significant increase in terms of work time efficiency, ease of data input and processing, and the presentation of relevant information for decision-making based on objective data analysis results. This research will also provide guidelines and benefits for other Education Foundations related to the utilization of integrated database systems in better HR management.&#x0D;

Atlantic Niño induced sea surface salinity variability as observed from the satellite

The Atlantic Niño exerts great impact on surrounding weather and climate anomalies, leading to anomalous wind, temperature, precipitation, etc. However, the impact of Atlantic Niño on ocean salinity in the tropical Atlantic has not been well disclosed. The present study examines the Atlantic Niño induced sea surface salinity (SSS) distribution in both boreal summer and winter seasons by using the satellite data as well as various reanalysis and objective analysis data sets. It concludes that the summer Atlantic Niño leads to large fresh SSS anomalies in the eastern equatorial basin, while the winter Atlantic Niño leads to a meridional dipole structure of SSS anomalies. The former is mostly controlled by the dynamical processes of ocean, while the latter is largely controlled by the atmospheric processes. Accordingly, two SSS indices are developed to describe the relationships in the two seasons. The present study advances our understanding of the Atlantic Niño and its associated SSS variability and reveals the possible deficiencies of current reanalysis and objective analysis data sets in the tropical Atlantic Ocean.

Theoretical and methodological foundations for studying the problems of developing social resources of territorial communities

The article is devoted to the development of theoretical and methodological foundations for studying the problems of developing social resources of territorial communities. The relevance of the research is due to the social order formed in modern society for the effective and optimal use of the social resources available in the territory as the basis for development. The purpose of the research is to determine theoretical and methodological foundations for studying the problems of developing social resources of territorial communities. Theoretical substantiation and research methods were laid by the works of domestic and foreign sociologists who substantiated the importance of the resource approach for the development of socio-economic systems. The application of system analysis made it possible to reveal the interdependence of the development of social resources and the territory. The totality of the components of the social resources of an individual, proposed by V.A. Yadov, most meaningfully reflects the targets of this research. In this regard, it has been proposed to use this material for the formation of sociological tools for obtaining primary information (questionnaires). The use of statistical data makes it possible to obtain an objective idea of the state of the environment and the main trends in territorial development. The systematization of factual and evaluative data has significant potential, which will be realized as part of the construction of a research construct. Summarizing, it can be said that the complexity and diversity of the concept of «social resources» is projected onto the process of forming the methodological foundations of the research. A systematic approach allows us to turn to the analysis of subjective and objective data and compare the received materials. Relying on the resource approach, it is possible to formulate measures to improve the development efficiency of both the territorial community as a whole and individual component of social resources.

The importance of appearing trustworthy in the workplace: performance analysts’ perspectives

ABSTRACT The discipline of performance analysis is founded upon the collection and analysis of objective and reliable data to support the coaching process. While research has begun to identify the potential importance of trust in applied sporting environments, there remains a paucity of inquiry that seeks to explicitly investigate trustworthiness in the work of performance analysts. To redress this situation Jisc online survey data was collected from performance analysts (n = 88, age: 37 ± 11 years, experience: 8 ± 6 years) practising across sporting contexts and geographic areas. Findings showed that: (1) appearing trustworthy to a range of working others was an important goal for performance analysts, (2) trustworthiness was considered essential for building positive working relationships, respect and perceptions of role-related competence (3) being perceived as trustworthy can generate desirable as well as help to avoid undesirable working conditions, including career progression and employment security, (4) analysts often seek to influence others perceptions of their trustworthiness by demonstrating important characteristics such as technical and tactical knowledge, being friendly and approachable, being punctual and hardworking, and evidenced-based, (5) an important facet of this was, often in conjunction with the coaching staff, concealing known information, particularly to athletes regarding poor performance to avoid psychological damage or where the data did not fit the coach’s approach, and (6) most performance analysts suggested the professional preparation and development of performance analysts needs to place greater emphasis on facilitating social sensibilities that practitioners can use to enhance perceptions about their workplace trustworthiness. The findings of this study generate new knowledge regarding the social features of performance analysis work, thus contributing to a growing critical social analysis of sport work in performance environments, as well as raising important practical implications for those responsible for educating the performance analysis workforce.

A Deep Learning Neural Network Method Using Linear Eigenvalue Statistics for Schizophrenic EEG Data Classification

Electroencephalography (EEG) signals can be used as a neuroimaging indicator to analyze brain-related diseases and mental states, such as schizophrenia, which is a common and serious mental disorder. However, the main limiting factor of using EEG data to support clinical schizophrenia diagnosis lies in the inadequacy of both objective characteristics and effective data analysis techniques. Random matrix theory (RMT) and its linear eigenvalue statistics (LES) can provide an effective mathematical modeling method for exploring the statistical properties of non-stationary nonlinear systems, such as EEG signals. To obtain an accurate classification and diagnosis of schizophrenia, this paper proposes a LES-based deep learning network scheme in which a series of random matrixes, consisting of EEG data sliding window sampling and their eigenvalues, are employed as features for deep learning. Due to the fact that the performance of the LES-based scheme is sensitive to the LES’s test function, the proposed LES-based deep learning network is embedded with two ways of combining LES’s test functions with learning techniques: the first is to have the LES’s test function assigned, while, using the second way, the optimal LES’s test function should be solved in a functional optimization problem. In this paper, various test functions and different optimal learning methods were coupled in experiments. Our results revealed a binary classification accuracy of nearly 90% in distinguishing between healthy controls (HC) and patients experiencing the first episode of schizophrenia (FES). Additionally, we achieved a ternary classification accuracy of approximately 70% by including clinical high risk for psychosis (CHR). The LES-embedded approach yielded notably higher classification accuracy compared to conventional machine learning methods and standard convolutional neural networks. As the performance of schizophrenia classification is strongly influenced by test functions, a functional optimization problem was proposed to identify an optimized test function, and an approximated parameter optimization problem was introduced to limit the search area of suitable basis functions. Furthermore, the parameterization test function optimization problem and the deep learning network were coupled to be synchronously optimized during the training process. The proposal approach achieved higher classification accuracy rates of 96.87% between HC and FES, with an additional 89.06% accuracy when CHR was included. The experimental studies demonstrated that the proposed LES-based method was significantly effective for schizophrenic EEG data classification.

Uniaxial constitutive model for fiber reinforced concrete: A physics-based data-driven framework

Fiber reinforced concrete (FRC) has improved strength and ductility, making it suitable for a wider range of engineering structures. The development of a constitutive model is crucial for analyzing mechanical behavior of these structures, while this still remains challenging as the complex composition of FRC makes it difficult to formulate explicit relationships among a range of critical material parameters. With the latest development of data and digital technologies, data-driven approaches have emerged as a powerful alternative that are capable of solving advanced and complex engineering problems. Developing data-driven methods based on objective data analysis and decision-making to predict mechanical behavior of engineering structures is an important direction of such development. In this paper, a uniaxial constitutive model of fiber-reinforced concrete is developed by a physics-based data-driven framework. The framework consists of three important parts, including construction of experimental database, parameters calibration of physical models, and implementation of neural network. From the experimental data collected from published literature, an experimental database is built first. A physical model is proposed by modifying the uniaxial constitute model for normal concrete, so that it is more convenient and straightforward to consider the effect of fibers on fiber reinforced concrete subjected to compression, tension and repeat loading conditions. The parameters of the model are calibrated against experimental data by the swarm intelligence optimization algorithms. With the calibrated parameters of the physical model, a Fully Connected Neural Network (FCNN) is trained to be used to predict the physical parameters of fiber reinforced concrete. By comparing with independent experimental data, the proposed fiber-reinforced concrete uniaxial constitutive model constructed using the physics-based data-driven framework can accurately predict the stress–strain relationships of a range of FRC, which suggests that the FRC material model can be used in the numerical simulation and design of FRC components and structures. In addition, the proposed model is applicable to multiple loading conditions.

The Relationship Of Online Games With The Disciplinary Character Of Elementary School Students

This quantitative descriptive research investigates the intensity of online gaming among Grade V students at SD Negeri 4 Bandungrejo, Bantur District, Malang Regency, aiming to assess its relationship with students' disciplinary character. Data was collected using questionnaires and documentation from a sample of 8 students, and analyzed through descriptive statistical methods. The findings reveal a negative and insignificant correlation between online gaming and students' disciplinary character, indicating that online gaming might not significantly influence their discipline. This study provides valuable insights for educators, parents, and policymakers on understanding and addressing potential challenges related to online gaming and its impact on students' behavior. Highlights: Importance of Disciplinary Character: This research focuses on assessing the disciplinary character of Grade V students in relation to their engagement in online gaming, shedding light on its significance for their overall development. Quantitative Descriptive Approach: The study employs a quantitative research design to provide an overview of the intensity of online gaming among Grade V students, allowing for objective data analysis and inference. Correlational Analysis: By utilizing a correlative model, the research examines the relationship between online gaming and students' discipline, presenting insights into any potential connections or lack thereof. Keywords: Online gaming, Grade V students, Discipline, Quantitative research, Correlational analysis.

Analysis of Accounting Information Systems on Receipts, Expenses &amp; Cash Transparency At Banjar Serasan Village Office

The purpose of this study was to understand the implementation of the Accounting Information System on Cash Receipts, Disbursements, and Transparency in the Banjar Serasan Village Office. This study uses a qualitative approach to gain a comprehensive understanding. The research data consists of primary data obtained through interviews with informants involved in the financial management process, as well as secondary data obtained through observation and documentation studies. Data collection techniques used include interviews, observation, and documentation studies. The analytical method used in this study adopts a postpositivism philosophy, which focuses on objective understanding and objective data analysis. The data collected was analyzed thematically, identified emerging patterns and themes, and given an in-depth interpretation. The results showed that the accounting information system implemented in the Banjar Serasan Village Office made a significant contribution to the mechanism of cash receipts and disbursements. However, research also finds that transparency to the public is limited due to local regulations that prohibit public disclosure of financial information. Informants in this study revealed that these limitations are the result of policies that have been set and must be followed.

Factors Influencing Jajar Legowo Innovation Decisions: (Case Study Of Budi Sepakat Farmer Group, Koto Tangah District, Padang City)

This study aims to describe the diffusion of legowo jar innovation in the Budi Sepakat farmer group and find out the factors that influence the decision of legowo jajar innovation in the Budi Agree farmer group, Koto Tangah District, Padang City. This research method uses qualitative and descriptive quantitative with a case study approach in Budi Sepakat's farmer group. The analysis of the first objective data was carried out by interactive analysis of Miles and Huberman in [1] The data used in this study are primary data and secondary data. The results showed that the innovation of legowo rows is an innovation regarding rice planting spacing with alternating planting patterns between two or more rice planting rows and one empty row. The legowo jajar innovation was first introduced by the Department of Agriculture through the 2017 Penas event in Aceh. Communication runs smoothly with the communication channel used, namely interpersonal communication channels. This innovation was communicated in 2017 and implemented in 2021. This innovation does not oppose customs and culture and is fully supported by the community. The factors that influence farmers' decisions on legowo line innovation are the nature of successive innovations, namely: Compatibility, complexity, relative advantage, trialability, and observability. And factors that do not influence farmers' decisions on legowo line innovation are age, land area, and education.

Kemampuan Siswa Kelas X SMA Sentosa Bhakti Baturaja Menentukan Frasa Adjektival dalam Paragraf Deskriptif

The purpose of this study was to describe the ability of students of class X SMA Sentosa Bhakti Baturaja determine adjective phrases in the descriptive paragraphs. The population in this study were all students of class X SMA Sentosa Bhakti Baturaja by the number of 39 students, the sample size of 39 students. The method used in this research is descriptive method. Data collection techniques are objective testing and data analysis techniques are descriptive qualitative data analysis techniques. Based on the results of research and discussion, it can be concluded that Traditionally, the average percentage of high school students' skills class X SMA Sentosa Bhakti Baturaja in determining phrase descriptive adjectives in the paragraph above the 66 scored as many as 23 people or 74.36%. Meanwhile, students who receive an excellent rating categories as many as 12 people or 30.77%, well as many as 17 people or 43.59%, quite as much as 3 or 7.69%, much less 4 people or 10.26%, and very less as much as 3 or 7.69%. Thus, it can be concluded that the students of class X SMA Sentosa Bhakti Baturaja was able to determine the adjective phrase descriptive paragraphs well. Therefore, it is recommended that no further research effort to make this study for comparison.

Highly automatic and universal approach for pure ion chromatogram construction from liquid chromatography-mass spectrometry data using deep learning

Feature extraction is the most fundamental step when analyzing liquid chromatography-mass spectrometry (LC-MS) datasets. However, traditional methods require optimal parameter selections and re-optimization for different datasets, thus hindering efficient and objective large-scale data analysis. Pure ion chromatogram (PIC) is widely used because it avoids the peak splitting problem of the extracted ion chromatogram (EIC) and regions of interest (ROIs). Here, we developed a deep learning-based pure ion chromatogram method (DeepPIC) to find PICs using a customized U-Net from centroid mode data of LC-MS directly and automatically. A model was trained, validated, and tested on the Arabidopsis thaliana dataset with 200 input-label pairs. DeepPIC was integrated into KPIC2. The combination enables the entire processing pipeline from raw data to discriminant models for metabolomics datasets. The KPIC2 with DeepPIC was compared against other competing methods (XCMS, FeatureFinderMetabo, and peakonly) on the MM48, simulated MM48, and quantitative datasets. These comparisons showed that DeepPIC outperforms XCMS, FeatureFinderMetabo, and peakonly in recall rates and correlation with sample concentrations. Five datasets of different instruments and samples were used to evaluate the quality of PICs and the universal applicability of DeepPIC, and 95.12% of the found PICs could precisely match their manually labeled PICs. Therefore, KPIC2+DeepPIC is an automatic, practical, and off-the-shelf method to extract features from raw data directly, exceeding traditional methods with careful parameter tuning. It is publicly available at https://github.com/yuxuanliao/DeepPIC.

Investigation of spatial variability in power law index of wind profiles above the urban area around Tokyo Bay based on local objective analysis data

By utilizing meteorological local objective analysis (LA) data on a local scale, this study investigated the spatial distribution of the power law index (PLI) of the mean wind speed profile in an urban area around Tokyo Bay in Japan. First, the reliability of the LA data was verified by comparison with observational data. The PLIs of the area for the 16 wind directions at a spatial resolution of 5 km were then estimated using LA data. Under neutral atmospheric conditions, the effects of the roughness length and terrain elevation on the PLI were investigated, and the spatial distribution characteristics of the PLI were analyzed. The results showed that the LA data were consistent with the observational data, indicating that high-precision LA data produced by data assimilation can be a practical supplement to observational data over urban areas. The influence of wind direction on the PLI was evident in the urban area. Furthermore, the metropolis appeared to affect the wind profile significantly when it was within the fetch of other cities, resulting in a larger PLI in the surrounding area. Because the PLI has complex spatial heterogeneity, in addition to urban substrate roughness, changes in terrain elevation and wind direction are thought to affect the PLI significantly. Therefore, generalizing the wind profile characteristics of large-area urban regions using local on-site observational data is not recommended.

Implementasi Supervisi Klinis dalam Meningkatkan Profesionalisme Guru

Teachers are professional educators. To carry out their duties in educating students, teachers must have sufficient competence. This study aims to improve the teaching and learning process carried out by teachers through a series of systematic improvements to improve professional competence. This study examines the characteristics of clinical supervision, procedures in carrying out clinical supervision and the strengths and weaknesses of clinical supervision. This research is library research by collecting data by analyzing books related to the research topic. The results of the study show the formation of professionalism from teachers who intend to support education reform and to "combat" educational decline, especially starting with teaching teachers in the classroom. With repairs and improvements, it is hoped that students can study well so that educational and teaching goals can be achieved optimally. especially in teaching performance based on observation and analysis of accurate and objective data as a guide for changing teaching behavior. This supervision puts emphasis on the process of "professional development and development" with the intention of responding to the main understanding and needs of teachers related to their duties.