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Apriyanto, Apriyanto
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Journal : journal of computer science advancements

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Implementation of Augmented Reality Technology in History Learning: Experimental Study Apriyanto, Apriyanto; Maharjan, Kailie; Wei, Zhang
Journal of Computer Science Advancements Vol. 2 No. 4 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i4.1321

Abstract

The integration of technology into education continues to evolve, with augmented reality (AR) emerging as a promising tool in enhancing learning experiences. In the context of history education, traditional methods often struggle to engage students and provide immersive experiences. This study investigates the implementation of augmented reality technology in history learning to assess its impact on student engagement and understanding. The research aims to determine whether AR can effectively improve students' comprehension of historical events and concepts compared to conventional teaching methods. A mixed-methods experimental design was employed, involving a sample of high school students who were divided into an experimental group using AR technology and a control group following traditional teaching methods. Data were collected through pre- and post-intervention assessments, surveys, and interviews. The analysis focused on comparing learning outcomes and engagement levels between the two groups. Results indicated that the experimental group demonstrated significantly higher scores on post-intervention assessments and reported greater engagement and interest in the subject matter compared to the control group. These findings suggest that AR technology can enhance students' understanding of historical content by providing interactive and immersive learning experiences. The study concludes that incorporating AR technology into history education can significantly improve student learning outcomes and engagement. The use of AR provides a novel approach to teaching history, offering immersive experiences that can complement traditional methods. Future research should explore the long-term effects of AR on learning and its applicability across various educational contexts.
Implementation of Deep Learning in a Voice Recognition System for Virtual Assistants Apriyanto, Apriyanto; Sahirin, Rohmat; Bradford, Snyder
Journal of Computer Science Advancements Vol. 2 No. 6 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v2i6.1533

Abstract

Voice recognition technology has become a vital component in virtual assistants, enabling more natural and efficient user interactions. However, traditional voice recognition systems face challenges in accurately interpreting diverse accents, dialects, and background noise, which can limit their usability. This study investigates the implementation of deep learning techniques to improve the accuracy and adaptability of voice recognition systems within virtual assistant applications. The research aims to enhance voice recognition performance by leveraging deep learning models that can process complex speech patterns and adapt to varied linguistic nuances. A convolutional neural network (CNN) architecture combined with recurrent neural networks (RNN) was used to train the voice recognition model on a large, diverse dataset of audio samples. The dataset included multiple languages, accents, and noisy environments to test the robustness of the model. Results indicate a 25% improvement in word error rate (WER) and a significant increase in recognition accuracy across diverse voice inputs compared to traditional voice recognition systems. The model demonstrated high adaptability, accurately interpreting speech in varying acoustic conditions, thus improving user experience with virtual assistants. These findings suggest that deep learning can significantly enhance voice recognition systems, offering more reliable performance in real-world applications. Implementing deep learning models in voice recognition systems can bridge the gap between human and machine communication, making virtual assistants more accessible and user-friendly.
Co-Authors Abduh, Hisma Abed, Yara Abrar Hiswara Adiazmil, Aan Agil, Ibnu Aini, Apriyanti Albadri, Albadri Alhamdani, Abdul Kodir Alnisari, Alnisari Amariansah, Widayat Andiani, Paramita Anggara, Reddy Antari, Laila Ardiansyah, Fasyah Arief Yanto Rukmana Arifin , Zainal Arini, Rani Eka Arisondha, Edy Astuti - Aulia, Sofi Azhiman, Fauzan Azmi, Riska Nurul Bobby Ferly Bradford, Snyder Bunyamin, Ilham Akbar Chrisdiana, Yulvia Dana Budiman Dasmen, Rahmat Novrianda Dedy Wahyudi Diah Isnaini Asiati Edi Sutanto Edison, Rizki Edmi FAIZAL FAIZAL FAIZAL Fardinah, Fardinah Fasli Jalal Febriansah, M Doni Fitiria, Zakiatul Frans Sudirjo Gamar Al Haddar, Gamar Al Gustin, Nindi Riyan Hamzan Wadi Hanim, Saidatul Harun, Lalu Ahmad Hidayat, Deddy Hikmah Hikmah Himawan Sutanto, Himawan Homiswadi, Homiswadi Hossam, Ahmed Ibnusina, Fedri Ihwanudin Ma’ruf Ika Nur Fitriani Ilham, M Indriwati Indriwati Intes, Amina Irfansyah Irfansyah Ismiati, Riska Jaswan, Jaswan Judijanto, Loso Katjong, Rizky Wisudawan Khadijah Khadijah Lamdayani, Rinda Latifa Dinar Rahmani Hakim Lesmana, Tera Lestari, Sri Dian Maharjan, Kailie Mardiati Mardiati Marius Masri Sadipun Marlina Marlina Mauliana, Yunita Maulina, Fina Mirahwati, Mirahwati Monica, Poppy Muflih Adi Laksono Muhallim, Muhlis Muhammad Nadjib, Muhammad Muhibbatun, Muhibbatun Muhtadi, Muhamad Ammar Mukhta, Diniwati Murniawan, Muhammad Wahid Musa Hefer Smas Nampira, Ardi Azhar Nila Sari Novitasari, Salwa Aulia Nugroho, Agung Yuliyanto Nur Handoko Nurhaliza, Ellys Nurhasanah, Dila Padila Nurhidayah Nurhidayah Nursyam Anaguna NURUL AZIZAH Pangaribuan, Hotma Priyana, Yana Purnomo, Adi Dwi Purwinahyu, Purwinahyu Putra, M. Willie Aidillio Rahmawati, Sri Andlina Rasyid, Herlina Riana Riana, Riana Rifandi, Muhammad Rinto Suppa Rismayanti Rismayanti Rissa Megavitry Rohana Nur Aini Roni Afrizal Rosadi, Elda Mnemonica Sahirin, Rohmat Saifullah Saifullah Salam, Ananda Azhara As Saputri, Mila Oktalia Setiani, Dwi Aluh setiawati, rahmi Sitepu, Ediaman Siti Annisa Wahdiniawati, Siti Annisa Siti Badriyah Siti Maria Siti Mudawanah Sitti Hasnah Slamet Haryadi Sono, Mohammad Gifari Suherna, Nana Sukarsih Sukarsih, Sukarsih Sunardi Sunardi Supriandi Supriandi, Supriandi Susi Susilowati, Susi Susilo, Anton Syahrir, Nur Hilal A. Tria Anggraini Utami, Andi Syahri Utami, Eva Yuniarti Vandan Wiliyanti Wahyudi Wahyudi Wahyuni, Ester Dwi Wardani, Chyntia Ayu Wibowo, Teguh Setiawan Wiji Utami, Wiji Winata, Rizki Hardian Yahya, Sitti Rachmawati Yanti, Septa Affifa Virgi Yayan Febriyanto Yuli Purwanti Zakaria Habib Al-Ra’zie Zelpiana, Zelpiana Zhang Wei