Deep Learning dan Penerapannya dalam Pembelajaran

Raup, Abdul; Ridwan, Wawan; Khoeriyah, Yayah; Supiana, Supiana; Zaqiah, Qiqi Yuliati

doi:10.54371/jiip.v5i9.805

Cited by 7 publications

(5 citation statements)

References 15 publications

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“…Most teaching staff or educational institutions have widely used automatic assessment to check questions automatically or online. By utilizing one of these technological advances, teaching staff or educational institutions can work effectively and efficiently (Raup et al, 2022).…”

Section: Technological Developments That Can Help Improve the Quality...mentioning

confidence: 99%

Education Transformation in Palangka Raya: Optimizing Technology Management through Artificial Intelligence Towards Quality Improvement

Berkat

2024

JTP

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The aim of this research is to determine the role of artificial intelligence (AI) in education, especially in the field of institutional education. Specifically, the aim of this research is to answer the role of AI in helping students and teachers find new teaching materials that are more efficient and effective in increasing student competence. The method used is a literature study using a systematic literature review approach. In a systematic literature review, all reading is analyzed and placed in the preparation of background, theory and discussion. The number of journals used was 35 journals, some of which were books and other online manuscripts. Data were analyzed using five steps, namely tracing primary and secondary sources; data processing/citation of references; presenting data; interpret data; and draw conclusions. The research results found that artificial intelligence has gained widespread acceptance and use in the field of education, especially in the field of institutional education which is the main topic of this research. The research also found that AI robots can now be used as stand-alone co-teachers or educators, as well as robots to perform similar tasks to educators or instructors. Utilization of these resources has been able to increase the efficiency and effectiveness of educators, so that the quality of teaching is richer or better. Furthermore, the research results found that, artificial intelligence has given students access to a better learning experience because Artificial Intelligence allows the adjustment of learning resources according to students' needs and abilities. In general, the research results found that, artificial intelligence has influenced education significantly, especially in the fields of management, teaching and learning both in the educational sector or personal situations teaching educational institutions.

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Section: Technological Developments That Can Help Improve the Quality...mentioning

confidence: 99%

Education Transformation in Palangka Raya: Optimizing Technology Management through Artificial Intelligence Towards Quality Improvement

Berkat

2024

JTP

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“…Pengenalan pola mencakup berbagai bidang seperti, pengenalan wajah, pengenalan sidik jari, pengenalan gambar, pengenalan karakter, pengenalan angka, dan sebagainya [1]. Pola tulisan tangan menjadi semakin umum dalam kehidupan, misalnya untuk mengenali berkas penting yang menggunakan tulisan tangan menjadi suatu tulisan digital yang bisa diakses secara mudah melalui perangkat elektronik.…”

Section: Pendahuluanunclassified

Recognition of Real-Time Handwritten Characters Using Convolutional Neural Network Architecture

Gumilang,

Avianto

2023

J. Tek. Inform. (JUTIF)

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Pattern recognition, including handwriting recognition, has become increasingly common in everyday life, as is recognizing important files, agreements or contracts that use handwriting. In handwriting recognition, there are two types of methods commonly used, namely online and offline recognition. In online recognition, handwriting patterns are associated with pattern recognition to generate and select distinctive patterns. In handwritten letter patterns, machine learning (deep learning) is used to classify patterns in a data set. One of the popular and accurate deep learning models in image classification is the convolutional neural network (CNN). In this study, CNN will be implemented together with the OpenCV library to detect and recognize handwritten letters in real-time. Data on handwritten alphabet letters were obtained from the handwriting of 20 students with a total of 1,040 images, consisting of 520 uppercase (A-Z) images and 520 lowercase (a-z) images. The data is divided into 90% for training and 10% for testing. Through experimentation, it was found that the best CNN architecture has 5 layers with features (32, 32, 64, 64, 128), uses the Adam optimizer, and conducts training with a batch size of 20 and 100 epochs. The evaluation results show that the training accuracy is between 85, 90% to 89.83% and testing accuracy between 84.00% to 87.00%, with training and testing losses ranging from 0.322 to 0.499. This research produces the best CNN architecture with training and testing accuracy obtained from testing. The developed CNN model can be used as a reference or basis for the development of more complex handwriting pattern recognition models or for pattern recognition in other domains, such as object recognition in computer vision, facial recognition, and other object detection.

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“…Deep Learning is part from intelligence artificial and machine learning which is development of a multiple layer neural network to give accuracy task like detection object, introduction sound, translation language and others. Deep Learning is different from traditional machine learning techniques, due to deep learning automatic do representation from data like pictures, videos or text without introduce rule code or human domain knowledge [11] .…”

Section: Deep Learningmentioning

confidence: 99%

Design And Development Of Karo Traditional Music Instrument Recognition Application Based On Digital Image Using Convolutional Neural Network Method

Tarigan,

Achmad Fauzi

2023

j. of artif. intell. and eng. appl.

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In this modern era, multimedia technology has role important in various field like education, health, and publications. Thesis This focused on development application introduction tool music traditional Karo tribe based digital image use Convolutional Neural Network (CNN) method. Karo music has characteristic typical unique and important for culture of North Sumatra. Study This use method Squeezenet and MobileNetV2 for compare accuracy in introduction object tool music Karo tribe. The Convolutional Neural Network (CNN) method is used in the introduction process. Steps covers convolution, function Activation ReLU, pooling, layers connected full, and the output layer with function Activation Soft max. Image data tool music Karo tribe gathered from Google Images. System This own steps like preprocessing image, model training with CNN method, and analysis results training. Research results This give comparison accuracy between method Squeezenet and MobileNetV2 in recognize tool music Karo tribe. Supporting data used in analysis, especially image tool music obtained Karo tribe from Google Images, with structured design and implementation of CNN, applications This succeed recognize type tool music with level good accuracy.

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Deep Learning dan Penerapannya dalam Pembelajaran

Cited by 7 publications

References 15 publications

Education Transformation in Palangka Raya: Optimizing Technology Management through Artificial Intelligence Towards Quality Improvement

Education Transformation in Palangka Raya: Optimizing Technology Management through Artificial Intelligence Towards Quality Improvement

Recognition of Real-Time Handwritten Characters Using Convolutional Neural Network Architecture

Design And Development Of Karo Traditional Music Instrument Recognition Application Based On Digital Image Using Convolutional Neural Network Method

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