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All Journal Journal of Informatics and Technology TELKOMNIKA (Telecommunication Computing Electronics and Control)
Sukmawati Nur Endah
Diponegoro University
Computer Science & IT

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Comparison of Feature Extraction Mel Frequency Cepstral Coefficients and Linear Predictive Coding in Automatic Speech Recognition for Indonesian Sukmawati Nur Endah; Satriyo Adhy; Sutikno Sutikno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.3605

Abstract

Speech recognition can be defined as the process of converting voice signals into the ranks of the word, by applying a specific algorithm that is implemented in a computer program. The research of speech recognition in Indonesia is relatively limited. This paper has studied methods of feature extraction which is the best among the Linear Predictive Coding (LPC) and Mel Frequency Cepstral Coefficients (MFCC) for speech recognition in Indonesian language. This is important because the method can produce a high accuracy for a particular language does not necessarily produce the same accuracy for other languages, considering every language has different characteristics. Thus this research hopefully can help further accelerate the use of automatic speech recognition for Indonesian language. There are two main processes in speech recognition, feature extraction and recognition. The method used for comparison feature extraction in this study is the LPC and MFCC, while the method of recognition using Hidden Markov Model (HMM). The test results showed that the LPC method is better than MFCC in Indonesian language speech recognition.
Integrated System Design for Broadcast Program Infringement Detection Sukmawati Nur Endah; Satriyo Adhy; Sutikno Sutikno
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 2: June 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i2.1124

Abstract

Supervision of television and radio broadcast programs by the “Komisi Penyiaran Indonesia (KPI)” Central Java was still performed manually i.e. direct supervision by humans. It certainly had some weaknesses related to the human error such as tiredness and weary eyes. Therefore, we needed intelligent software that could automatically detect broadcast infringement. Currently, research in this area had not been studied. This research was to design an integrated system to detect broadcast infringement including data design, architecture design and main module interface design. Two main stages in this system are the Indonesian language speech recognition and detection of infringements of the broadcast program. With the method of Mel Frequency cepstral Coefficients (MFCC) and Hidden Markov Model (HMM) speech recognition application that used the 1050 sample data produces about 70% accuracy rate. This research would continue to implement the plan that had been created using speech recognition applications that had been built.
Continuous speech segmentation using local adaptive thresholding technique in the blocking block area method Roihan Auliya Ulfattah; Sukmawati Nur Endah; Retno Kusumaningrum; Satriyo Adhy
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 1: February 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i1.13958

Abstract

Continuous speech is a form of natural human speech that is continuous without a clear boundary between words. In continuous speech recognition, a segmentation process is needed to cut the sentence at the boundary of each word. Segmentation becomes an important step because a speech can be recognized from the word segments produced by this process. The segmentation process in this study was carried out using local adaptive thresholding technique in the blocking block area method. This study aims to conduct performance comparisons for five local adaptive thresholding methods (Niblack, Sauvola, Bradley, Guanglei Xiong and Bernsen) in continuous speech segmentation to obtain the best method and optimum parameter values. Based on the results of the study, Niblack method is concluded as the best method for continuous speech segmentation in Indonesian language with the accuracy value of 95%, and the optimum parameter values for such method are window = 75 and k = 0.2.
PENGEMBANGAN APLIKASI LEARNING MANAGEMENT SYSTEM (LMS) PADA SEKOLAH MENENGAH PERTAMA ISLAM TERPADU (SMP IT) HARAPAN BUNDA SEMARANG Syaakir Ni’am; Helmie Arif Wibawa; Sukmawati Nur Endah
Journal of Informatics and Technology Vol 2, No 1 (2013): Wisuda Januari 2013
Publisher : Jurusan Ilmu Komputer / Informatika, FMIPA UNDIP, Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1487.461 KB)

Abstract

Sekolah Menengah Pertama Islam Terpadu (SMP IT) Harapan Bunda Semarang adalah salah satu institusi pendidikan swasta yang memiliki kewajiban menyelenggarakan pembelajaran terbaik untuk siswanya. Seperti halnya sekolah pada umumnya, selama ini pembelajaran di sekolah terkendala kurang banyaknya waktu dan tempat untuk melaksanakan pembelajaran. Pemanfaatan teknologi informasi berupa electronic learning diharapkan bisa memberikan kemudahan dalam menjalankan aktifitas pembelajaran dengan melakukan pengelolaan aplikasi yang membantu pembelajaran secara online. Learning Management System (LMS) merupakan salah satu bentuk perangkat lunak yang mengimplementasikan konsep electronic learning. Pembangunan LMS ini menggunakan alat bantu PHP sebagai bahasa pemrograman dan MySQL sebagai pengelola basis data. Sedangkan model proses pembangun perangkat lunak yang dipakai adalah model waterfall.Tugas akhir ini menghasilkan LMS Harbun berbasis web yang dapat memberikan kemudahan untuk murid dan guru dalam melakukan interaksi untuk menunjang aktifitas pembelajaran secara online.
Co-Authors Helmie Arif Wibawa Retno Kusumaningrum Roihan Auliya Ulfattah Satriyo Adhy Sutikno Sutikno Sutikno Sutikno Syaakir Ni’am