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All Journal Pendidikan Bahasa Indonesia Jurnal Edukasi dan Penelitian Informatika (JEPIN)
Erlina Susanti
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Computer Science & IT Education Languange, Linguistic, Communication & Media

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KEMAMPUAN MENULIS PUISI SISWA KELAS VIII SMPN 1 LEMBAH GUMANTI DENGAN MENGGUNAKAN MEDIA POSTER Susanti, Erlina; Bahardur, Iswadi; Zulfitriyani, Zulfitriyani
Pendidikan Bahasa Indonesia Vol 2, No 2 (2013): Jurnal Wisuda Ke 47, Genap 2013-2014 Pendidikan Bahasa dan Sastra Indonesia
Publisher : Pendidikan Bahasa Indonesia

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Abstract

This research was motivated by three issues, namely (1) lack of students interest in learning to write poetry, (2) the delivery of learning materials of writing poetry was less interesting, (3) the inapropriate selection and use of instructional media. This research was aimed to describe the ability to write poetry of class VIII students of SMPN 1 Lembah Gumanti using media poster. This research was quantitative using descriptive methods. Research object were class VIII students of SMPN 1 Lembah Gumanti. Samples were class VIII students of SMPN1 Lembah Gumanti amounted to 33 people. The ability to write poetry class VIII students of SMPN1 Lembah Gumanti using combined media posters for both indicators is classified as Good. Based on the results of research, it can be summarized as follows: First, the use of media posters in learning to write poetry in class VIII students of SMP 1 Lembah Gumanti is classified as Good. Second, in general the average value of the ability to write poetry class VIII students of SMPN 1 Lembah Gumanti valley is 79,1 with Good qualification. The Conclusion were relevant to research, two things are recommended. First, the ability to write poetry class VIII students of SMPN1 Lembah Gumanti required further improvement. Second, the use of instructional media, should be used functionally in learning to write poetry.
Penerapan Convolutional Neural Network (CNN) pada Pengenalan Aksara Lampung Berbasis Optical Character Recognition (OCR) Mulyanto, Agus; Susanti, Erlina; Rossi, Farli; Wajiran, Wajiran; Borman, Rohmat Indra
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 7, No 1 (2021): Volume 7 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v7i1.44133

Abstract

Provinsi Lampung memiliki bahasa dan aksara daerah yang disebut juga dengan Had Lampung atau KaGaNga yang merupakan aksara asli lampung. Melihat bagaimana pentingnya nilai akan eksistensi sebuah budaya dan pentingnya pelestarian aksara lampung maka dibutuhkan teknologi yang membantu dalam mengenalkan aksara lampung, salah satunya dengan teknologi optical character recognition (OCR) yang digunakan untuk merubah citra kedalam teks. Untuk mengenali pola citra Aksara Lampung dan klasifikasi model maka digunakan Convolutional Neural Network (CNN). CNN memiliki lapisan convolution yang terbentuk dari beberapa gabungan lapisan konvolusi, lapisan pooling dan lapisan fully connected. Pada peneilitian yang dilakukan dataset dikembangkan dengan pengumpulan hasil tulis tangan dari sampel responden yang telah ditentukan, kemudian dilakukan scanning gambar. Selanjutnya, dilakukan proses pelabelan dan disimpan dengan format YOLO yaitu TXT. Dari asitektur CNN yang dibangun berdasarkan hasil evaluasi menunjukan loss, accuracy menghasilkan nilai training accuracy mendapatkan nilai sebesar 0.57 dan precision mendapatkan nilai sebesar 0.87. Dari hasil nilai accuracy dan precision menunjukkan bahwa model training sudah baik karena mendekati angka 1.
Co-Authors Agus Mulyanto Heni Pujiastuti Iswadi Bahardur Rohmat Indra Borman Rossi, Farli Zulfitriyani