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2021 ◽  
Vol 2021 ◽  
pp. 1-7
Chan Sun ◽  
Xiaojuan Li

HRMS is a very critical tool for companies. The recruitment text contains rich information that can provide strong information support for the company’s recruitment work and also improve the efficiency of job seekers in finding job opportunities. To this end, for the problem of multilabel text classification of recruitment information, this paper provides two algorithms for multilayer classification based on supported SVM. First, the same learning subclass method is used for text sorting subclass acquisition, and then, the class of the text is determined. Second, the hemispherical support SVM is used to find the smallest hypersphere in the feature space that contains the most text of that class and segment the text of that class from other texts. For the text to be classified, the distance from it to the center of each hypersphere is used to determine the class of the text. Experimental results on recruitment data demonstrate that the algorithm in this paper has a high check-all rate, check-accuracy rate, and F1. And, the relationship between HRM activities and corporate performance is discussed.

2021 ◽  
Vol 20 (11) ◽  
pp. 132-153
Nadri Taja ◽  
Encep Syarief Nurdin ◽  
Aceng Kosasih ◽  
Edi Suresman ◽  
Tedi Supriyadi

The social distancing policy in the COVID-19 outbreak has influenced the non-holistic learning process, causing several moral problems. The learning process tends to promote the cognitive aspect, while the affective aspect tends to be neglected. This research aims at offering a learning model that promotes religious ethical values through religious education in junior high schools (SMP/Sekolah Menengah Pertama) in an effort to develop effective attitudes. The development of the model is carried out in five stages of research, namely analysis, design, development, implementation, and evaluation (ADDIE). This research involved two groups of participants consisting of 376 students and 45 Islamic Education (PAI/Pendidikan Agama Islam) teachers in junior high schools in West Java. The research results explore the PAI learning model that develops religious ethical values as learning objectives. The process of internalizing these values is developed through the processes of knowing, of doing, and of being. Religious ethical values that are developed in students are the crystallization of four prophetic characters, namely fathonah, siddiq, amanah, and tabligh. The test results of two junior high schools, both public schools and religious-based schools, concluded that the application of the religious ethical learning model was able to improve students' religious ethical character at a high level. This research contributes to the development of PAI learning designs in the pandemic era based on the development of prophetic characters. In addition, this research can be a guideline for teachers or academics in developing research related to student character within the framework of character education.

2021 ◽  
Rifdah Ibtisam El-Ghifary ◽  
Nurul Istiqomah ◽  
Abdullah Sakka

The purpose of this classroom action research is to enhance the result study of moral aqidah education with Contextual Teaching and Learning learning in 2nd grade students of MI Raden Rahmat. The form of this research is classroom action research consisting of two cycles, each cycle consists of four stages, namely planning, implementation, observation and reflection. As the research subject is a 2nd grade students of MI Raden Rahmat. In data collection, the method used as the main method is observation and test. Based on the results of research on the learning models application of Contextual Teaching and Learning to 2nd grade students of MI Raden Rahmat, with a total of 13 students have enhancement on the study result, which is before the action, only 30.81% of students studied thoroughly, and after the action became 100% of students studied thoroughly. Thus, it can be concluded that the learning model application of the Contextual Teaching and Learning is proven to be able to improve study result of moral aqidah education in 2nd grade students of MI Raden Rahmat

2021 ◽  
Vol 11 (1) ◽  
Gahyung Ryu ◽  
Kyungmin Lee ◽  
Donggeun Park ◽  
Sang Hyun Park ◽  
Min Sagong

AbstractAs the prevalence of diabetes increases, millions of people need to be screened for diabetic retinopathy (DR). Remarkable advances in technology have made it possible to use artificial intelligence to screen DR from retinal images with high accuracy and reliability, resulting in reducing human labor by processing large amounts of data in a shorter time. We developed a fully automated classification algorithm to diagnose DR and identify referable status using optical coherence tomography angiography (OCTA) images with convolutional neural network (CNN) model and verified its feasibility by comparing its performance with that of conventional machine learning model. Ground truths for classifications were made based on ultra-widefield fluorescein angiography to increase the accuracy of data annotation. The proposed CNN classifier achieved an accuracy of 91–98%, a sensitivity of 86–97%, a specificity of 94–99%, and an area under the curve of 0.919–0.976. In the external validation, overall similar performances were also achieved. The results were similar regardless of the size and depth of the OCTA images, indicating that DR could be satisfactorily classified even with images comprising narrow area of the macular region and a single image slab of retina. The CNN-based classification using OCTA is expected to create a novel diagnostic workflow for DR detection and referral.

Anuranjan Pandey

Abstract: In the tropical jungle, hearing a species is considerably simpler than seeing it. The sounds of many birds and frogs may be heard if we are in the woods, but the bird cannot be seen. It is difficult in this these circumstances for the expert in identifying the many types of insects and harmful species that may be found in the wild. An audio-input model has been developed in this study. Intelligent signal processing is used to extract patterns and characteristics from the audio signal, and the output is used to identify the species. Sound of the birds and frogs vary according to their species in the tropical environment. In this research we have developed a deep learning model, this model enhances the process of recognizing the bird and frog species based on the audio features. The model achieved a high level of accuracy in recognizing the birds and the frog species. The Resnet model which includes block of simple and convolution neural network is effective in recognizing the birds and frog species using the sound of the animal. Above 90 percent of accuracy is achieved for this classification task. Keywords: Bird Frog Detection, Neural Network, Resnet, CNN.

2021 ◽  
Andres Sanchez-Ruiz ◽  
Gonzalo Colmenarejo

Positive outcomes in biochemical and biological assays of food compounds may appear due to the well-described capacity of some compounds to form colloidal aggregates that adsorb proteins, resulting in their denaturation and loss of function. This phenomenon can lead to wrongly ascribing mechanisms of biological action for these compounds (false positives), as the effect is non-specific and promiscuous. Similar false positives can show up due to chemical (photo)reactivity, redox cycling, metal chelation, interferences with the assay technology, membrane disruption, etc., which are more frequently observed when the tested molecule has some definite interfering substructures. Although discarding false positives can be achieved experimentally, it would be very useful to have in advance a prognostic value for possible aggregation and/or interference, based only in the chemical structure of the compound tested, in order to be aware of possible issues, help in prioritization of compounds to test, design of appropriate assays, etc. Previously, we applied cheminformatic tools derived from the drug discovery field to identify putative aggregators and interfering substructures in a database of food compounds, the FooDB, comprising 26457 molecules at that time. Here we provide an updated account of that analysis based on a current, much-expanded version of the FooDB, comprising a total of 70855 compounds. In addition, we also apply a novel machine learning model (the SCAM Detective) to predict aggregators with 46%-53% increased accuracies over previous models. In this way, we expect to provide the researchers in the mode of action of food compounds with a much improved, robust, and widened set of putative aggregators and interfering substructures of food compounds.

2021 ◽  
Vol 2 (4) ◽  
pp. 559-572
Juni Agus Simaremare ◽  
Nancy Angelia Purba

This study aimed to improve the professional competence of Indonesian language teachers in applying the Problem-Based Learning (PBL) learning model at State Senior High School 1 Muara. This research is a Classroom Action Research involving 6 Indonesian language teachers. The research was conducted in two cycles, namely: planning, implementation, observation, and reflection. Aspects measured in the observations were teacher teaching performance, teacher interaction with researchers, interaction with other Indonesian language subject teachers, collaboration with other teachers, making lesson plans, learning processes, evaluating the implementation of Problem-Based Learning (PBL). From the data analysis, it was found that there was an increase in teacher activity and competence in implementing the PBL model. In the initial condition, from 54.00 (criteria for poor score) increased to 66.00 (criteria for sufficient value) and 76.00 (criteria for good value). In the aspect of learning implementation, the average score of 55.21 (criteria for low scores) increased to 65.43 (sufficient value criteria) and 75.43 (good value criteria) in the second cycle. In the aspect of assessment of learning outcomes, from an average of 53.58 (criteria for poor scores) to 65.42 (criteria for good scores) and 77.42 (criteria for good scores). Also, in the aspect of classroom management from 54.00 enough and 75.83 ( good grade criteria). From the results above, it can be concluded that the implementation of the Problem-Based Learning model with academic supervision has been proven to improve the professional competence of teachers in managing the learning process

2021 ◽  
Vol 1 (4) ◽  
pp. 178-185

This study aims to determine the increase in student learning outcomes after using the Contextual Teaching and Learning learning model. Based on student learning outcomes in the previous school year, it was seen that the learning outcomes were low, especially on Mawaris material. Therefore, the authors conducted classroom action research by changing the learning model that previously used lectures and discussions into Contextual Teaching and Learning. CTL (Contextual Teaching and Learning) learning is a learning concept that emphasizes the relationship between learning materials and the real world of students' lives, so that students are able to connect and apply learning outcomes competencies in everyday life. This study uses two cycles of action research consisting of four steps, namely: planning, implementing, observing and reflecting. The subjects of this study were students of class XII.IPA.1 for the academic year 2020/2021. Data were obtained from formative test results, activity observation sheets, and interview sheets. From the results of the analysis, it was found that the learning outcomes of Mawaris material increased from 69.23% in cycle 1 to 92.30% in cycle 2. The conclusion of this study is that Contextual Teaching and Learning learning can improve student learning outcomes. ABSTRAKPenelitian ini bertujuan untuk mengetahui peningkatan hasil belajar siswa setelah penggunaan model pembelajaran Contextual Teaching and Learning. Berdasarkan hasil belajar siswa pada tahun pelajaran sebelumnya terlihat rendahnya hasil belajar terutama pada materi Mawaris. Oleh karena itu penulis melakukan penelitian tindakan kelas dengan mengganti model pembelajaran yang tadinya menggunakan ceramah dan diskusi menjadi Pembelajaran Contextual Teaching and Learning. Pembelajaran CTL (Contextual Teaching and Learning) merupakan konsep pembelajaran yang menekankan pada keterkaitan antara materi pembelajaran dengan dunia kehidupan siswa secara nyata, sehingga siswa mampu menghubungkan dan menerapkan kompetensi hasil belajar dalam kehidupan sehari-hari. Penelitian ini menggunakan penelitian tindakan sebanyak dua siklus yang terdiri dari empat langkah yaitu: perencanaan, pelaksanaan, pengamatan dan refleksi. Subjek penelitian ini adalah siswa kelas XII.IPA.1 tahun pelajaran 2020/2021. Data diperoleh dari hasil tes formatif, lembar observasi kegiatan, dan lembar wawancara. Dari hasil analisis didapatkan bahwa hasil belajar materi mawaris mengalami peningkatan ketuntasan belajar dari 69,23% pada siklus 1 menjadi 92,30% pada siklus 2. Kesimpulan dari penelitian ini adalah bahwa pembelajaran Contextual Teaching and Learning dapat meningkatkan hasil belajar siswa.

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