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Analysis And Voice Recognition In Indonesian Language Using MFCC And SVM Method Harvianto, Harvianto; Ashianti, Livia; Jupiter, Jupiter; Junaedi, Suhandi
ComTech: Computer, Mathematics and Engineering Applications Vol 7, No 2 (2016): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v7i2.2252

Abstract

Voice recognition technology is one of biometric technology. Sound is a unique part of the human being which made an individual can be easily distinguished one from another. Voice can also provide information such as gender, emotion, and identity of the speaker. This research will record human voices that pronounce digits between 0 and 9 with and without noise. Features of this sound recording will be extracted using Mel Frequency Cepstral Coefficient (MFCC). Mean, standard deviation, max, min, and the combination of them will be used to construct the feature vectors. This feature vectors then will be classified using Support Vector Machine (SVM). There will be two classification models. The first one is based on the speaker and the other one based on the digits pronounced. The classification model then will be validated by performing 10-fold cross-validation.The best average accuracy from two classification model is 91.83%. This result achieved using Mean + Standard deviation + Min + Max as features.
Analisis Komparatif Berbagai Teori Karakteristik Proses Pendekatan Anak dengan Tujuan Seksual untuk Mendeteksi Percakapan Teks Ashianti, Livia; Idananta, Kanyadian
JIEET (Journal of Information Engineering and Educational Technology) Vol. 7 No. 1 (2023)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jieet.v7n1.p1-9

Abstract

Teknologi internet sering disalahgunakan untuk tindakan kriminal, salah satunya adalah proses pendekatan anak untuk tujuan seksual secara online. Dalam melakukan tindakannya, pelaku melakukan pendekatan kepada korban dengan menggunakan teknologi internet. percakapan teks menjadi bukti kejahatannya. Studi sebelumnya menunjukkan bahwa teori karakteristik dapat menentukan tingkat akurasi dalam mendeteksi percakapan teks yang berisi proses pendekatan tersebut. Penelitian ini akan melakukan uji coba menggunakan teori karakteristik yang berbeda untuk mendapatkan teori karakteristik terbaik untuk mendeteksi percakapan teks mengandung proses pendekatan dengan tujuan seksual. Karakteristik tersebut akan digunakan untuk ekstraksi fitur percakapan teks. Kemudian diklasifikasikan menggunakan metode Support Vector Machine (SVM). Hasil penelitian menunjukkan bahwa penggunaan jumlah karakteristik yang berbeda berdampak pada tingkat akurasinya. Namun, menggabungkan 2 teori karakteristik berbeda menghasilkan tingkat akurasi yang lebih baik.
Development of an E-Thesis Application Using Agile Method and Azure Devops at XYZ University Idananta, Kanyadian; Mayliana, Mayliana; Ashianti, Livia
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v11i2.63830

Abstract

To adapt to rapid change in the software development landscape, organizations require a more adaptive approach than the traditional Waterfall method to better accommodate evolving user needs. The Agile methodology, characterized by its adaptive, iterative, and responsive nature, is well-suited for modern application development environments. However, Agile has notable weaknesses in operational aspects such as deployment, monitoring, and the lack of continuous testing and integration. To overcome these limitations, the implementation of Agile methods is increasingly complemented by DevOps practices. Integrating Agile and DevOps methodologies accelerates product delivery, improves communication and team collaboration, and automates development processes. Universitas XYZ developed a web-based e-Thesis application to integrate and monitor all stages of thesis supervision using the Agile methodology, specifically the Scrum framework, supported by DevOps practices implemented through the Azure DevOps platform. Azure DevOps supports a collaborative culture and provides a set of integrated processes that bring together developers, project managers, and contributors. This study demonstrates that the integration of the Agile methodology with the Azure DevOps platform in the development of the e-Thesis system has proven effective in enabling faster, more reliable, and responsive system development aligned with user requirements.