Perangkat Lunak Mobile Pendeteksi Huruf Abjad untuk Sistem Edukasi pada Anak

Puspitasari, Putri Endah (2021) Perangkat Lunak Mobile Pendeteksi Huruf Abjad untuk Sistem Edukasi pada Anak. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Adanya pandemic COVID-19, muncul suatu kebijakan pemerintah yaitu Pembatasan Sosial Berskala Besar (PSBB) yang menyebabkan ditutupnya sekolah dari Taman Kanak-Kanak (TK) hingga perguruan tinggi. Pembelajaran kini dilakukan secara daring/online. Hal ini membuat banyak problematika yang muncul dalam pelaksanaan pembelajaran daring. Pendidik, orang tua hingga anak merasa kesulitan dalam mengembangkan dan menerima pembelajaran. Terlebih lagi anak usia TK sangat membutuhkan pembelajaran menulis sebagai bekal mereka menuju jenjang Pendidikan berikutnya.
Berdasarkan uraian di atas, diciptakannya aplikasi berbasis website dan mobile Bernama Welearn. Aplikasi website digunakan oleh administrator untuk melakukan manajemen user dan soal. Sedangkan aplikasi mobile digunakan untuk user anak sebagai pendeteksi tulisan huruf abjad. Welearn menyediakan soal penulisan huruf abjad kemudian akan mendeteksi apakah jawaban yang ditulis benar atau salah yang ditandai dengan adanya notifikasi. Penulis memanfaatkan teknologi Transfer Learning MobileNet untuk melakukan deteksi tulisan tangan huruf (handwriting recognition). Untuk proses klasifikasi penulis menggunakan algoritma Convolutional Neural Network (CNN). Aplikasi ini diharapkan dapat membantu proses belajar pada anak terutama belajar menulis huruf abjad.
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With the COVID-19 pandemic, a government policy emerged, namely Large-Scale Social Restrictions (PSBB) which led to the closure of schools from Kindergarten to universities. Learning is now done online. This makes many problems that arise in the implementation of bold learning. Educators, parents, and children find it difficult to develop and accept learning. What’s more, kindergarten-age children need learning to write as their provision for the next level of education.
Based on the description above, the creation of a website and a mobile-based application called Welearn. The website application is used by administrators to manage users and questions. While the mobile application is used for child users as a detector for writing letters of the alphabet. Welearn provides questions for writing the letters of the alphabet and will then detect whether the answers written are correct or incorrect, which is indicated by a notification. The author uses MobileNet Transfer Learning technology to detect handwriting letters. For the classification process, the author uses the Convolutional Neural Network (CNN) algorithm. This application is expected to help the learning process in children, especially learning to write the letters of the alphabet.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Daring, TK, Welearn, Deteksi Huruf Abjad, Transfer Learning, CNN, Online, Kindergarten, Welearn, Handwriting Letters, Transfer Learning, CNN
Subjects:	L Education > L Education (General) Q Science > QA Mathematics > QA76.76.A65 Application software. Enterprise application integration (Computer systems) T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK6570_iPhone (Smartphone). RFID. Mobile communication systems.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55201-(S1) Undergraduate Thesis
Depositing User:	Putri Endah Puspitasari
Date Deposited:	03 Aug 2021 03:38
Last Modified:	03 Aug 2021 03:38
URI:	http://repository.its.ac.id/id/eprint/84716

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