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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Informatika CommIT (Communication & Information Technology) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Telematika JUITA : Jurnal Informatika Seminar Nasional Informatika (SEMNASIF) POSITIF Annual Research Seminar JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Ilmiah Matrik Jusikom : Jurnal Sistem Komputer Musirawas Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Ilmiah Media Sisfo JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Informatika Global Journal of Information Systems and Informatics Jurnal Teknologi Dan Sistem Informasi Bisnis Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknologi Informatika dan Komputer Jurnal Restikom : Riset Teknik Informatika dan Komputer Journal of Computer and Information Systems Ampera Jurnal Pengembangan Sistem Informasi dan Informatika Journal of Applied Computer Science and Technology (JACOST) Jurnal Mahasiswa Sistem Informasi (JMSI) Jurnal Nasional Pengabdian Masyarakat J-SAKTI (Jurnal Sains Komputer dan Informatika) International Journal Software Engineering and Computer Science (IJSECS) Jurnal Bina Komputer International Journal of Scientific and Professional Jurnal Ilmu Komputer dan Sistem Informasi Ngabdimas Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Journal of Computer Science and Technology Application
Yesi Novaria Kunang
Universitas Bina Darma
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Other

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BUKU DIGITAL INTERAKTIF JEJAK WARISAN KERAJAAN SRIWIJAYA MENGGUNAKAN METODE MDLC Putri Ramadhani, Nasywa; Yesi Novaria Kunang; Novri Hadinata
Jurnal Mahasiswa Sistem Informasi (JMSI) Vol. 7 No. 1 (2025): Jurnal Mahasiswa Sistem Informasi (JMSI)
Publisher : Program Studi DIII Sistem Informasi - Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/jmsi.v7i1.10843

Abstract

Pemanfaatan teknologi digital dapat menjadi solusi dalam menyampaikan informasi sejarah dan melestarikan budaya secara lebih menarik. Selama ini, informasi mengenai warisan budaya Kerajaan Sriwijaya masih disajikan melalui media konvensional yang kurang interaktif, sehingga minat generasi muda relatif rendah. Penelitian ini bertujuan untuk mengembangkan buku digital interaktif Jejak Warisan Kerajaan Sriwijaya sebagai media pembelajaran berbasis web. Metode yang digunakan adalah Multimedia Development Life Cycle (MDLC) yang mencakup tahap concept, design, material collecting, assembly, testing, dan distribution. Buku digital dikembangkan dalam bentuk flipbook dengan memadukan teks, gambar, audio, video, serta kuis interaktif berbasis chatbot. Hasil pengujian menggunakan metode black box menunjukkan bahwa seluruh fitur berjalan sesuai dengan perancangan. Media ini diharapkan dapat menjadi alternatif pembelajaran yang efektif serta mendukung pelestarian warisan budaya Kerajaan Sriwijaya di era digital.
Enhancing Student Anxiety Detection: A Multimodal Transformer Approach to Video-Based Screening Yunike; Kunang, Yesi Novaria; Muzakir, Ari; Kusumawaty, Ira
International Journal Scientific and Professional Vol. 5 No. 1 (2026): December 2025 - February 2026
Publisher : Yayasan Rumah Ilmu Professor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56988/chiprof.v5i1.158

Abstract

This study developed and applied a multimodal Transformer model for student anxiety screening through video analysis of short interviews that included facial expressions, speech, and numerical data. Student anxiety is a problem that often affects mental health and academic performance, so early detection is important. The model combines three main data sources: facial expression features, speech analysis (including speech speed, intonation, and negative word count), and demographic information. The data used came from 500 students who participated in interviews lasting 20-40 seconds. The multimodal Transformer model was trained to classify anxiety levels into low, medium, and high categories, with evaluation using accuracy, precision, and recall metrics. The results showed that this model had a prediction accuracy of 88%, with a significant correlation between facial expressions and negative word counts on anxiety levels. Compared to the linear regression model used for comparison, the multimodal Transformer model shows better performance in detecting anxiety. These findings indicate that a multimodal approach using AI technology can improve accuracy and efficiency in student anxiety screening. This research opens up opportunities for the development of a more objective, non-invasive, and efficient video-based automated screening system, with potential applications in the field of mental health in higher education.
Image Segmentation of East OKU Script Using the Bounding Box Method for Cultural Heritage Digitization M Fikri; Ilman Zuhri Yadi; Yesi Novaria Kunang; Leon Andretti Abdillah
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4045

Abstract

East Ogan Komering Ulu (OKU) is distinguished by its cultural heritage, which encompasses historical artifacts such as traditional houses, crafts, and ceremonial dances. Among the most significant cultural assets are relics inscribed with ancient scripts, including Pallawa and Ulu, which offer valuable insight into the region’s historical literacy. The present study addresses the segmentation of OKU Timur script images through the Bounding Box method. This approach was selected based on its practicality and efficiency, particularly in the context of datasets where script characters exhibit straightforward forms and the overall data volume remains manageable. The segmentation process utilizes Python within the Google Colaboratory platform, ensuring accessible and reproducible workflows. Accurate segmentation is essential to support ongoing digitization and preservation of cultural scripts. The methodology involves gathering data from local artifacts, converting images to binary format, and isolating characters using Bounding Boxes. The results demonstrate that the method effectively separates individual script characters, laying the groundwork for dataset development and subsequent image classification tasks.
Palembang to Indonesian Language Translation Machine Using the No Language Left Behind Approach Muhammad Finaldo; Yesi Novaria Kunang
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 2 (2025): AUGUST 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i2.4105

Abstract

The Palembang language, deeply rooted in the cultural fabric of South Sumatra, continues to serve as a vital means of daily communication for many communities. As globalization accelerates, safeguarding such regional languages has become increasingly urgent, particularly through technological solutions that can bridge communication between local speakers and visitors. This study introduces an automatic translation system designed to convert Palembang text into Indonesian, employing the No Language Left Behind (NLLB) algorithm—a recent development in artificial intelligence for language processing. A dataset containing 7,917 pairs of Palembang and Indonesian sentences was assembled for this purpose. The translation models were trained and assessed using BLEU (Bilingual Evaluation Understudy) and chrF (Character n-gram F-score) metrics. The initial model achieved a BLEU score of 22.55 and a chrF++ score of 43.22. Subsequent improvements raised these scores to 30.72 and 55.39, respectively, reflecting a significant enhancement in translation quality and clarity for Indonesian readers. By focusing on a language with limited digital resources, this research demonstrates the potential of modern translation technologies to support both linguistic preservation and practical communication needs in diverse cultural settings.
Pengembangan Aplikasi Presensi Berbasis Deep Learning Lailatul Akmal; Ilman Zuhri Yadi; Yesi Novaria Kunang; Fatma Sari
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.354

Abstract

A facial recognition-based attendance system is a modern solution to overcome the weaknesses of manual attendance methods that are prone to manipulation and recording errors. This study uses a deep learning-based attendance application by implementing a Convolutional Neural Network (CNN) using MobileNetV2, VGG16, and ResNet50 architectures optimized for devices with limited resources. The facial dataset was collected independently and went through preprocessing stages, including normalization, resizing, augmentation, and face detection with OpenCV. The model was trained using TensorFlow and Keras on Google Colab with a GPU. It was then evaluated using a confusion matrix, which yielded accurate predictions with a low error rate. A classification report was also conducted, with an accuracy of 0.98, a precision of 1.00, a recall of 1.00, and an F1-score of 1.00, achieving a very high level of performance, indicating no prediction errors. A Flask web-based application was designed to connect the facial recognition model with the user interface, and was tested in real-time to measure the speed and accuracy of attendance. The results show that the CNN-based attendance application is able to provide a safer, faster, and more efficient attendance alternative compared to conventional methods.
PENERJEMAH BAHASA BESEMAH BERBASIS MACHINE LEARNING DENGAN ALGORITMA MODEL ENCODER-DECODER Bogy Dharma Sandi; Susan Dian Purnamasari; Yesi Novaria Kunang; Ilman Zuhri Yadi; Fatmasari Fatmasari
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 1 (2025): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i1.5252

Abstract

Regional languages are one of the cultural elements in Indonesia, reflecting the diverse traditions of various regions across the archipelago. The Besemah language, spoken by the Besemah ethnic group, is used daily by the residents of Pagar Alam City and Lahat Regency. Although there are differences in pronunciation and vocabulary between villages, the Besemah language still shares a common linguistic root. The residents of Pagar Alam, particularly those in the mountainous areas of South Sumatra Province, are among the native speakers of the Besemah language. To enhance the preservation of the Besemah language, this study utilizes a translation system between Besemah and Indonesian. The development of this translation system, in line with technological advancements, will facilitate users in understanding translations between the Besemah language and Indonesian. The researchers chose the Encoder-Decoder algorithm because this architecture has been proven effective in various translation tasks and can produce more accurate translations compared to existing methods such as the Edit Distance algorithm and Convolutional Neural Networks (CNN). This algorithm consists of two main components: the Encoder, which processes the input document and converts it into a translation for each word in the Besemah language, and the Decoder, which takes the data representation generated by the Encoder and processes it into a translation output in Indonesian and vice versa.
Augmented Reality in Preschool Enhancing Storytelling and Cognitive Development Yanti Pasmawati; Yesi Novaria Kunang; Muhammad Hatta; Jonathan Parker; Dwi Nur Ramadhan
CORISINTA Vol 2 No 2 (2025): August
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/corisinta.v2i2.104

Abstract

Augmented Reality (AR) is a technology that enables the integration of digital elements into the real world, creating more immersive and interactive learning experiences. In a study conducted at a local kindergarten, traditional storytelling methods often caused children to lose focus, particularly when the stories lacked engaging visual elements. In contrast, by using AR, stories such as the adventure of a cat could be brought to life through interactive 3D animations, allowing children not only to listen but also to interact with the characters. This study aims to examine the effectiveness of AR in enhancing storytelling and supporting the cognitive development of young children. A mixed-method approach was employed, comparing two groups: a control group using traditional methods and an experimental group using an AR application. Quantitative data were collected through pre- and post-tests, while qualitative data were obtained from direct observations and interviews with teachers and parents. The results revealed that the experimental group recorded a 32.10\% increase in post-test scores, significantly higher than the 7.34% increase in the control group. Furthermore, AR improved children’s engagement, enthusiasm, and collaboration during storytelling sessions. In conclusion, AR demonstrates considerable potential in supporting early childhood education by creating more engaging and inclusive learning experiences, although challenges such as technology accessibility and the availability of appropriate content still need to be addressed.
PENGEMBANGAN ANTAR MUKA APLIKASI MOBILE MESIN PENERJEMAH BAHASA DAERAH SUMATERA SELATAN BERBASIS MODULAR MENGGUNAKAN FRAMEWORK FLUTTER Syafaat Prasetia; Yesi Novaria Kunang; Ilman Zuhri Yadi; Susan Dian Purnamasari
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.6570

Abstract

Bahasa daerah Sumatera Selatan terdiri dari Bahasa Jawa, Kayu Agung, Komering, Lematang, Melayu, Ogan, Basemah dan Pedamaran. Setiap bahasa tersebut menjadi identitas setiap daerah di provinsi Sumatera Selatan. Akan tetapi, sudah tidak banyak khususnya anak muda yang menggunakan atau mengenal bahasa daerah Sumatera Selatan.  Penelitian ini dilakukan untuk mengembangkan antar muka aplikasi penerjemah bahasa daerah Sumatera Selatan yaitu bahasa Basemah, Palembang, Komering ke Indonesia, maupun sebaliknya. Metode yang digunakan adalah extreme programming yaitu metode pengembangan perangkat lunak yang responsif terhadap perubahan, terdiri dari beberapa iterasi yang dapat dilakukan berulang kali sesuai kebutuhan. Tools yang akan digunakan untuk membuat tampilan aplikasi yaitu Flutter yang merupakan framework untuk aplikasi mobile yang memungkinkan pengembangan aplikasi dengan kinerja tinggi. Hasil yang dari penelitian ini berupa antar muka aplikasi untuk menghubungkan model machine translator seq2seq (sequence-to-sequence) yang dikembangkan sebelumnya menggunakan API Flask. Berdasarkan hasil pengujiang menggunakan metode SUS (Systems Usability Scale) dari 20 responden, antar muka yang dikembangkan mendapat skor SUS 78 (good).
Co-Authors Adam Prasetya Afiyudi, Afiyudi Afriyudi Agus Setiawan Ahmad Zarkasi Andika, Muhamad Andri Andri Anggie Khristian Ari Muzakir Arief Algiffary Armansyah, Risky Atmojo, Toni Tri Beni Brahara Bhakti Yudho Suprapto Bogy Dharma Sandi Damayanti, Nita Rosa Darmawahyuni, Annisa Dedy Syamsuar Dedy Syamsuar Deris Stiawan Dwi Nur Ramadhan Dzakwan, Fadhlur Rahman Edi Surya Negara Egy Septian Eka Puji Agustini Endang Etriyanti Fajarino, Aldo Fatma sari Fatmasari Fatmasari Ferdiansyah Ferdiansyah Fernandy Jupiter Firdaus Firdaus Firdaus Gllen yusuf abbel Hadinata, Novri Hamanrora, Muhammad Dio Hellen Puspita Sari Hendra Marta Yudha Herdiansyah, Izman Herdiansyah, M. Izman Herdiansyah, M. Izman Herferry, Ibrahim Ade Ilman Zuhri Yadi Ilman Zuhri Yadi Ilman Zuhriyadi Inda Anggraini Irwansyah Ibrahim Jonathan Parker Kurniawan Kurniawan Kurniawan, Tri Basuki Lailatul Akmal Lang Dimas Perkasa Leon Andretti Abdillah Liza Fahreni M Fikri M Izman Herdiansyah Mahmud Mahmud Mahmud Mahmud Maria, Fitri Muhammad Fachrurrozi Muhammad Finaldo Muhammad Hatta Muhammad Izman Herdiansyah Muhammad Naufal Rachmatullah Netti Herawati Novi Yusliani Novifika, Seva Permatasari, Susan Dian Prasetya, M. Iqbal Pratiwi, Ayu Okta Prilsafira, Tania Putra, Muhammad Hatta Putri Ramadhani, Nasywa Ramadhona, Nuzulur Rianda, M. Rianda Rio Ananda Fitriansyah Sapitri, Wulan Sari, Tia Permata Siti Nurmaini Sri Murniati Suryayusra - Susan Dian Purnamasari Susan Dian Purnamasari, Susan Dian Syafaat Prasetia Taqrim Ibadi Tata Sutabri Toriko, Liu Tri Basuki Kurniawan Usman Ependi Via Sukma Cendanie Widya Cholil Widya Putri Mentari Winoto Chandra Wulandari, Intan Fitriana Yanti Pasmawati Yayuk Ike Meilani Yudi, Endang Darmawan Yunike, Yunike Yustida Bellini Ziqrullah, Muhammad Hafiz Zulkifli Harahap Zulkifli Harahap