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All Journal Jurnal Ilmu Komputer dan Informasi JUTI: Jurnal Ilmiah Teknologi Informasi
Yuna Sugianela
Sepuluh Nopember Institute of Technology
Computer Science & IT Dentistry Education Library & Information Science

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CHARACTER IMAGE SEGMENTATION OF JAVANESE SCRIPT USING CONNECTED COMPONENT METHOD Yuna Sugianela; Nanik Suciati
Jurnal Ilmu Komputer dan Informasi Vol 12, No 2 (2019): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (607.599 KB) | DOI: 10.21609/jiki.v12i2.677

Abstract

Automation of Javanese script translation is needed to make it easier for people to understand the meaning of ancient Javanese script. By using Javanese script image as input, the translation system generally consists of character segmentation, character recognition, and combining the recognized characters as a meaningful word. The segmentation which obtains region of interest of each character, is an important process in the translation system. In the previous research, segmentation using projection profile method can separate each character well. The method can overcome characters overlapping, but it still produces truncated characters. In this study, we proposed a new segmentation to reduce the truncated character. The first step of the proposed method is pre-processing that consists of converting input into binary image and cleaning noises. The next step is to determine the connected component labels, which further perform as candidate of characters. Some of the candidates are still represented by more than one labels, so that we need a process to merge the connected component labels that have centroid distance less than threshold. We evaluate the proposed method using Intersection over Union (IoU). The evaluation shows the best accuracy 93,26%.
EEG CLASSIFICATION FOR EPILEPSY BASED ON WAVELET PACKET DECOMPOSITION AND RANDOM FOREST Yuna Sugianela; Qonita Luthfia Sutino; Darlis Herumurti
Jurnal Ilmu Komputer dan Informasi Vol 11, No 1 (2018): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (360.748 KB) | DOI: 10.21609/jiki.v11i1.549

Abstract

EEG (electroencephalogram) can detect epileptic seizures by neurophysiologists in clinical practice with visually scan long recordings. Epilepsy seizure is a condition of brain disorder with chronic noncommunicable that affects people of all ages. The challenge of study is how to develop a method for signal processing that extract the subtle information of EEG and use it for automating the detection of epileptic with high accuration, so we can use it for monitoring and treatment the epileptic patient. In this study we developed a method to classify the EEG signal based on Wavelet Packet Decomposition that decompose the EEG signal and Random Forest for seizure detetion. The result of study shows that Random Forest classification has the best performance than KNN, ANN, and SVM. The best combination of statisctical features is standard deviation, maximum and minimum value, and bandpower. WPD is has best decomposition in 5th level.
EKSTRAKSI FITUR PADA PENGENALAN KARAKTER AKSARA JAWA BERBASIS HISTOGRAM OF ORIENTED GRADIENT Yuna Sugianela; Nanik Suciati
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 17, No. 1, Januari 2019
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v17i1.a819

Abstract

Buku-buku kuno Bahasa Jawa memiliki konten kekayaan intelektual Indonesia seperti agama, linguistik, filosofi, mitos, pelajaran moral, hukum dan norma adat, kerajaan, cerita rakyat, sejarah, dan lain sebagainya. Tidak banyak yang mempelajari karya tersebut karena ditulis dengan Aksara Jawa dan tidak banyak yang memahami. Untuk membantu penerjemahan dokumen berbahasa Jawa dilakukan otomatisasi sistem penerjemahan. tahap penerjemahan terdiri dari segmentasi untuk mendapatkan karakter dari citra tulisan dalam naskah Aksara Jawa. Kemudian tiap karakater dikenali sebagai abjad. Dan yang terakhir adalah mengkombinasikan tulisan latin yang telah dikenali menjadi kata yang berarti. Penelitian yang membahas tentang pengenalan Aksara Jawa telah dilakukan, seperti fokus pada segmentasi karakter dan pengenalan Aksara Jawa. Pada penelitian sebelumnya dilakukan perbaikan pada metode segmentasi namun tetap mendapatkan hasil yang sama dalam hal akurasi kebenaran. Pada penelitian kali ini diusulkan metode baru pada tahap ekstraksi fitur, yaitu menggunakan metode Histogram of Oriented Gradient (HOG). Metode HOG banyak digunakan pada pengenalan wajah, hewan, dan deteksi citra kendaraan, dan lain-lain. Penelitian ini juga pernah diusulkan untuk mengenali tulisan tangan berbahasa Inggris dan Huruf Bengali dan mendapatkan hasil yang optimal. Pada penelitian ini didapatkan hasil akurasi pengenalan karakter Aksara Jawa sebesar 89,7%.Ekstraksi Fitur, Histogram of Oriented Gradient, Aksara Jawa
Co-Authors Darlis Herumurti Nanik Suciati Nanik Suciati Qonita Luthfia Sutino