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All Journal Jurnal Masyarakat Informatika SAINS DAN MATEMATIKA JURNAL SISTEM INFORMASI BISNIS Journal of Informatics and Technology TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Information Systems Engineering and Business Intelligence E-Dimas: Jurnal Pengabdian kepada Masyarakat JURNAL EKONOMI MANAJEMEN AKUNTANSI Jurnal Pasopati : Pengabdian Masyarakat dan Inovasi Pengembangan Teknologi Jurnal Pelayanan dan Pengabdian Masyarakat Indonesia
Satriyo Adhy
Universitas Diponegoro
Religion Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences

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Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

 1 
WCLOUDVIZ: Word Cloud Visualization of Indonesian News Articles Classification Based on Latent Dirichlet Allocation Retno Kusumaningrum; Satriyo Adhy; Suryono Suryono
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.8194

Abstract

Latent Dirichlet Allocation (LDA) is a widely implemented approach for extracting hidden topics in documents generated by soft clustering of a word based on document co-occurrence as a multinomial probability distribution over terms. Therefore, several visualizations have been developed, such as matrices design, text-based design, tree design, parallel coordinates, and force-directed graphs. Furthermore, based on a set of documents representing a class (category), we can implement classification task by comparing topic proportion for each class and topic proportion for the testing document by using Kullback-Leibler Divergence (KLD). Therefore, the purpose of this study is to develop a system for visualizing the output of LDA as a classification task. The visualization system consists of two parts: bar chart and dependent word cloud. The first visualization aims to show the trend of each category, while the second visualization aims to show the words that represent each selected category in a word cloud. This visualization is subsequently called WCloudViz. It provides clear, understandable and preferably shared the result.
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.
Co-Authors Adieb, M. Risqi Amirul Agus Setyawan Agus Subagio Agustha, Emmanuel Bagas Alamsyah, Alsio Rachmad Anakotta, Garry Leonard Aretama, Lucky Barga Ari Bawono Putranto Aris Sugiharto Arsyaningrum, Aurellia Putri Budi Ashari, Yeva Fadhilah Cahya Setya Utama Defa Hanifta Putra, Defa Hanifta Dharmawan, Bagus Dwiky Dinar Mutiara Kusumo Nugraheni Djalal Er Riyanto Eka Triyana Guruh Aryotejo, Guruh Hasbi Yasin Helmie Arif Wibawa Helmie Arif Wibawa Hermawan Ardiyanto Hidayat Rizal I Gusti Ngurah Antaryama Jatmiko Endro Suseno Kamila, Syabina Kushartantya Kushartantya Moch. Abdul Mukid Muhammad Iqbal Rizqon Bahaudin Muhammad Malik Hakim, Muhammad Malik Muhammad Mukhtar Muhammad Nur Mustafid Mustafid Mutiara, Dinar NURUL AZIZAH Nurul Mutiani Sukarno, Nurul Mutiani Panji Wisnu Wirawan Pradieva, Christenta Tirta Priyo Sidik Sasongko Priyo Sidik Sasongko Priyono, Aziiza Yvelliechia Ragil Saputra Ragil Saputra Redemtus Heru Tjahjana Retno Kusumaningrum Ririn Sulpiani RISMIYATI RISMIYATI Rizki, Femas Arianda Roihan Auliya Ulfattah Sadewo, Wisnu Salman Alfarisi Salsabila, Safira Septiandika Saputra, Aditya Lutfian Sonia, Putrisya Novatiara Sudarno Sudarno Sukmawati Nur Endah Sukmawati Nur Endah Sunarno Sunarno Suryono Suryono Sutikno . Sutikno Sutikno Sutikno Sutikno Titik Ekowati Udi Harmoko Wicaksono, Muhammad Tsaqif WIDOWATI widowati widowati Widyatna, Nicolaus Evan Yundari, Yundari