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All Journal Jurnal Mantik Penusa Journal Technology and Implementation Bussines Jurnal Ilmu Komputer dan Desain Komunikasi Visual Jurnal Teknologi dan Terapan Bisnis Jurnal Teknologi dan Terapan Bisnis
Elsen Ronando
Universitas 17 Agustus 1945 Surabaya
Arts Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Languange, Linguistic, Communication & Media

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Sistem Pengenalan Pola Huruf Braille Berbasis Audio Menggunakan Metode Naïve Bayes Elsen Ronando; Aris Sudaryanto
Jurnal Ilmu Komputer dan Desain Komunikasi Visual Vol 3 No 1 (2018): Jurnal Ilmu Komputer dan Desain Komunikasi Visual (JIKDISKOMVIS)
Publisher : Fakultas Ilmu Komputer Universitas Nahdlatul Ulama Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Blind people currently have limitations in developing their knowledge. The limitation is due to blind people still using braille character in interacting. Thus, the information received by blind people is slower than the general public. To overcome this problem, we propose a braille character pattern recognition system. There are several steps to recognize the braille character, as follows the digital image processing and pattern recognition using the naïve Bayes method. In the digital image processing step, there are several processes, such as the image acquisition process, enhancement, filtering, segmentation, and feature extraction. In the pattern recognition phase, the naive bayes method is used to predict the results of recognizable braille character patterns. The pattern recognition result is then converted into audio form using a raspberry pi device. Based on the results of our evaluation, the system is outperformed to recognize braille character with an accuracy of 88.172% and the average response time of the device into audio form about 5 seconds. Keywords: Blind People, Braille Character, Naïve Bayes
Sistem Pengambil Keputusan Untuk Penentuan Penerima Bantuan Langsung Masyarakat PNPM Mandiri Menggunakan Simple Additive Weighting (Studi Kasus Kecamatan Ngadirojo Kabupaten Pacitan) Elsen Ronando; Enny Indasyah
Jurnal Mantik Penusa Vol. 1 No. 2 (2017): Jurnal Mantik Penusa
Publisher : Lembaga Penelitian dan Pengabdian (LPPM) STMIK Pelita Nusantara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (434.224 KB)

Abstract

Poverty is a major problem for developing countries, especially in Indonesian country. To decrease the level of poverty in society, it become the main work program of the current government. One of the work programs that have been done to reduce poverty was a direct assistance program for village’s communities. However, the existing direct assistance system is still manual and subjective. Thus, the distribution becomes inefficient and uneven. Based on this problem, this study aims to address the direct assistance problem to the community efficiently. A simple additive weighting method (SAW) was applied to analyze the determination of direct assistance for communities. The results of this research shows that the proposed method can sort receiver of direct assistance in the villages of Ngadirojo Pacitan based on priority scale. Keywords: Simple Additive Weighting, Direct Assistance, Ngadirojo
SISTEM KONVERSI UCAPAN KATA KE TEKS MENGGUNAKAN SUPPORT VECTOR MACHINE : SPEECH WORD RECOGNITION TO TEXT CONVERTER USING SUPPORT VECTOR MACHINE Elsen Ronando; Sugiono
Jurnal Teknologi dan Terapan Bisnis Vol. 2 No. 2 (2019): Vol 2 No 2 (2019): Jurnal Teknologi dan Terapan Bisnis
Publisher : UPPM Akademi Komunitas Semen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.0301/jttb.v2i2.45

Abstract

Artificial intelligence technology is developing very rapidly. Various fields have applied this technology to help human work. Speech recognition system is one of the artificial intelligence technologies that are widely applied in various fields. However, some research showed that it was still necessary to develop a method for a good speech recognition system. In addition, the development of speech recognition systems that can provide benefits needs to be developed, such as text recording. Based on this, the research focuses on developing a speech recognition system, in the form of spoken words and convert to text form. Speech words that have been recorded are then extracted features using linear predictive coding method. After that, the characteristic features of each sound are trained and tested using the Support Vector Machine (SVM) method for the process of recognition and convert it into text. Based on the evaluation results show that this system is able to recognize words with an accuracy rate of 71.875%. These percentages indicate that the system is able to recognize spoken words and transform them into text form properly.
SISTEM KONVERSI UCAPAN KATA KE TEKS MENGGUNAKAN SUPPORT VECTOR MACHINE : SPEECH WORD RECOGNITION TO TEXT CONVERTER USING SUPPORT VECTOR MACHINE Elsen Ronando; Sugiono
Jurnal Teknologi dan Terapan Bisnis Vol. 2 No. 2 (2019): Vol 2 No 2 (2019): Jurnal Teknologi dan Terapan Bisnis
Publisher : UPPM Akademi Komunitas Semen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.0301/jttb.v2i2.45

Abstract

Artificial intelligence technology is developing very rapidly. Various fields have applied this technology to help human work. Speech recognition system is one of the artificial intelligence technologies that are widely applied in various fields. However, some research showed that it was still necessary to develop a method for a good speech recognition system. In addition, the development of speech recognition systems that can provide benefits needs to be developed, such as text recording. Based on this, the research focuses on developing a speech recognition system, in the form of spoken words and convert to text form. Speech words that have been recorded are then extracted features using linear predictive coding method. After that, the characteristic features of each sound are trained and tested using the Support Vector Machine (SVM) method for the process of recognition and convert it into text. Based on the evaluation results show that this system is able to recognize words with an accuracy rate of 71.875%. These percentages indicate that the system is able to recognize spoken words and transform them into text form properly.
SISTEM KONVERSI UCAPAN KATA KE TEKS MENGGUNAKAN SUPPORT VECTOR MACHINE : SPEECH WORD RECOGNITION TO TEXT CONVERTER USING SUPPORT VECTOR MACHINE Elsen Ronando; Sugiono
Jurnal Teknologi dan Terapan Bisnis Vol. 2 No. 2 (2019): Vol 2 No 2 (2019): Jurnal Teknologi dan Terapan Bisnis
Publisher : Program Studi Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (652.896 KB) | DOI: 10.0301/jttb.v2i2.45

Abstract

Artificial intelligence technology is developing very rapidly. Various fields have applied this technology to help human work. Speech recognition system is one of the artificial intelligence technologies that are widely applied in various fields. However, some research showed that it was still necessary to develop a method for a good speech recognition system. In addition, the development of speech recognition systems that can provide benefits needs to be developed, such as text recording. Based on this, the research focuses on developing a speech recognition system, in the form of spoken words and convert to text form. Speech words that have been recorded are then extracted features using linear predictive coding method. After that, the characteristic features of each sound are trained and tested using the Support Vector Machine (SVM) method for the process of recognition and convert it into text. Based on the evaluation results show that this system is able to recognize words with an accuracy rate of 71.875%. These percentages indicate that the system is able to recognize spoken words and transform them into text form properly.
Co-Authors Aris Sudaryanto Indasyah, Enny Sugiono