Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

p-Index From 2020 - 2025

0.23

P-Index

This Author published in this journals

All Journal Jurnal Optimasi Sistem Industri Jurnal Teknologi Infomasi, Komunikasi dan Elektronika (JTIKE)

Prafitia, Harnum Annisa

Unknown Affiliation

Author-ID : 1495837

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Mechanical Engineering

Published : 2 Documents Claim Missing Document

Claim Missing Document

Articles

RANCANGAN APLIKASI ANDROID PENERJEMAH WICARA KE WICARA DENGAN KOMUNIKASI DUA ARAH Santosa, Agung; Jarin, Asril; Aini, Lyla Ruslana; Ayuningtyas, Fara; Gunarso, Gunarso; Gunawan, Made; Uliniansyah, Mohammad Teduh; Latief, Andi Djalal; Puspita, Gita Citra; Nurfadhilah, Elvira; Prafitia, Harnum Annisa
Jurnal Teknologi Infomasi, Komunikasi dan Elektronika (JTIKE) Vol 1, No 1 (2018)
Publisher : Badan Pengkajian dan Penerapan Teknologi

Dengan ketersediaan sumber daya kebahasaan dan sistem Pengolahan Bahasa Alami yang sudah dikembangkan sebelumnya, kegiatan-kegiatan kerekayasaan Teknologi Bahasa BPPT melakukan pengembangan sebuah aplikasi penerjemah wicara-ke-wicara untuk dua Bahasa (Bahasa Indonesia dan Bahasa Inggris) yang memanfaatkan layanan dari server pengenal wicara, mesin penerjemah, dan sintesis wicara. Aplikasi ini dikenal sebagai speech-to-speech translation (S2ST). Di makalah ini, kami deskripsikan rancangan aplikasi S2ST tersebut dengan fokus pengembangan pada aplikasi mobile android yang dapat melayani percakapan antara dua pengguna. Teknik-teknik yang diterapkan antara lain adalah WebSocket, RESTful service, JSON, dan OkHttp3.Keywords: Penerjemah wicara ke wicara, S2ST, NLP, ASR, MT, TTS, WebSocket, RESTful Service.

Feature Selection and Performance Evaluation of Buzzer Classification Model Afra, Dian Isnaeni Nurul; Fajri, Radhiyatul; Prafitia, Harnum Annisa; Arief, Ikhwan; Mantau, Aprinaldi Jasa
Jurnal Optimasi Sistem Industri Vol. 23 No. 1 (2024): Published in July 2024
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

In the rapidly evolving digital age, social media platforms have transformed into battleground for shaping public opinion. Among these platforms, X has been particularly susceptible to the phenomenon of 'buzzers', paid or coordinated actors who manipulate online discussions and influence public sentiment. This manipulation poses significant challenges for users, researchers, and policymakers alike, necessitating robust detection measures and strategic feature selection for accurate classification models. This research explores the utilization of various feature selection techniques to identify the most influential features among the 24 features employed in the classification modeling using Support Vector Machine. This study found that selecting 11 key features yields a remarkably effective classification model, achieving an impressive F1-score of 87.54 in distinguishing between buzzer and non-buzzer accounts. These results suggest that focusing on the relevant features can improve the accuracy and efficiency of buzzer detection models. By providing a more robust and adaptable solution to buzzer detection, our research has the potential to advance social media research and policy. This enabling researchers and policymakers to devise strategies aimed at mitigating misinformation dissemination and cultivating an environment of trust and integrity within social media platforms, thus fostering healthier online interactions and discourse.

Co-Authors Afra, Dian Isnaeni Nurul Aini, Lyla Ruslana Ayuningtyas, Fara Fajri, Radhiyatul GUNARSO GUNARSO Gunawan, Made Ikhwan Arief Jarin, Asril Laksono Trisnantoro Latief, Andi Djalal Mantau, Aprinaldi Jasa Puspita, Gita Citra Santosa, Agung Uliniansyah, Mohammad Teduh

Title

Found 2 Documents
Search

Abstract

Abstract

Title Search

Found 2 Documents Search

Abstract

Abstract

Title

Found 2 Documents
Search