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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 Jurnal Ilmiah Matrik Jusikom : Jurnal Sistem Komputer Musirawas Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Ilmiah Media Sisfo J-SAKTI (Jurnal Sains Komputer dan Informatika) JURIKOM (Jurnal Riset Komputer) 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 Indonesian Journal of Innovation Multidisipliner Research Ngabdimas Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Indonesian Journal of Innovation Multidisipliner Research Journal of Computer Science and Technology Application
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Analisis Manajemen Resiko Teknologi Informasi Perusahaan Kesehatan: Health Company Information Technology Risk Management Analysis Dinata, Aria; Kunang, Yesi Novaria
Indonesian Journal of Innovation Multidisipliner Research Vol. 2 No. 1 (2024): March
Publisher : Institute of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/ijim.v2i1.72

Abstract

Perusahaan kesehatan saat ini semakin bergantung pada teknologi informasi untuk mendukung operasional, pelayanan pasien, dan pengelolaan data. Namun, penggunaan teknologi informasi dalam lingkungan perusahaan kesehatan juga membawa risiko tertentu. Studi ini bertujuan untuk melakukan analisis mendalam terhadap manajemen risiko teknologi informasi di perusahaan kesehatan. Metodologi penelitian yang digunakan meliputi tinjauan literatur, wawancara dengan praktisi industri, dan studi kasus untuk mengidentifikasi, mengevaluasi, dan mengatasi risiko yang terkait dengan teknologi informasi dalam konteks perusahaan kesehatan. Melalui implementasi langkah-langkah proaktif seperti peninjauan kebijakan keamanan, pemantauan keamanan, pelatihan karyawan, pengujian keamanan, dan kerja sama dengan pihak eksternal. Siloam Hospital Group berhasil meningkatkan keamanan data pasien, mematuhi regulasi privasi data, dan meningkatkan kesadaran keamanan di seluruh organisasi.
Komparasi Metode Klasifikasi terhadap Data Penderita Penyakit Diabetes Menggunakan Python 3 Pratiwi, Ayu Okta; Kurniawan, Tri Basuki; Negara, Edi Surya; Kunang, Yesi Novaria
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 6 No. 4 (2023): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Diabetes is a serious challenge in the world of health, with broad impacts. In an effort to overcome this problem, it is important to analyze the classification of diabetes data to provide valuable insights. This study focuses on the comparison of the two main classification methods, namely Naive Bayes and Support Vector Machine (SVM), in analyzing diabetes data. We use the Python 3 programming language for implementation. The initial study involved the characterization of the dataset, including parameters such as blood pressure and blood glucose levels, which were important factors in the analysis. The preprocessing process is carried out to ensure data quality by overcoming missing or invalid values. After that, the dataset is divided into training and testing subsets. The Naive Bayes and SVM methods are implemented using the scikit-learn library in Python 3. Both models are trained using a training subset and tested on a test subset. The test results show that both methods have good performance in classifying diabetes data, but SVM stands out with higher accuracy. SVM has the ability to handle complex data and find optimal decision boundaries. The Naive Bayes model achieves the highest accuracy of 78.13% on 70% training data and 30% testing data, while the SVM model achieves 79.63% on 90% training data and 10% testing data. Overall, this study provides an in-depth understanding of the effectiveness of both methods in the context of classifying data on diabetics.
Pendampingan Pengembangan Sistem Pengarsipan di Kantor Camat Pedamaran Kabupaten Ogan Komering Ilir Ziqrullah, Muhammad Hafiz; Kunang, Yesi Novaria; Yadi, Ilman Zuhri; afriyudi, afriyudi
Jurnal Nasional Pengabdian Masyarakat Vol. 5 No. 1 (2024): Jurnal Nasional Pengabdian Masyarakat
Publisher : Training & Research Institute - Jeramba Ilmu Sukses

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jnpm.v5i1.1611

Abstract

Archives are an essential system that must be possessed by an organization, serving as evidence, evaluation material, and planning material for future activities. Disorganized and undocumented archives in an institution will result in difficulties in searching for archives when needed. The Pedamaran Sub-district office in South Sumatera is facing challenges in rechecking archives due to the stacking of physical documents. To help address this issue, the writing team provides a solution by designing and developing a web-based archiving system. This system is organized based on categories to facilitate the input and checking of documents. After the development of the archiving system for the Pedamaran Sub-district office, further assistance is provided to ensure that officials at the Pedamaran Sub-district office can utilize the created archiving system
Augmented Reality in Preschool Enhancing Storytelling and Cognitive Development Pasmawati, Yanti; Kunang, Yesi Novaria; Hatta, Muhammad; Parker, Jonathan; Ramadhan, Dwi Nur
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.
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.
Co-Authors Adam Prasetya Afiyudi, Afiyudi Afriyudi Agus Setiawan Agus Setiawan Ahmad Zarkasi Andika, Muhamad Andri Andri Anggie Khristian Ari Muzakir Arief Algiffary Armansyah, Risky Atmojo, Toni Tri Beni Brahara Bhakti Yudho Suprapto Damayanti, Nita Rosa Darmawahyuni, Annisa Dedy Syamsuar Dedy Syamsuar Deris Stiawan Dinata, Aria Dzakwan, Fadhlur Rahman Edi Surya Negara Egy Septian Eka Puji Agustini Endang Etriyanti Fajarino, Aldo 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 Zuhriyadi Inda Anggraini Irwansyah Ibrahim Kurniawan Kurniawan Kurniawan, Tri Basuki 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 Parker, Jonathan Permatasari, Susan Dian Prasetya, M. Iqbal Pratiwi, Ayu Okta Prilsafira, Tania Putra, Muhammad Hatta Putri Ramadhani, Nasywa Ramadhan, Dwi Nur Ramadhona, Nuzulur Rianda, M. Rianda Rio Ananda Fitriansyah Sapitri, Wulan Sari, Tia Permata Siti Nurmaini Sri Murniati Suryayusra - Susan Dian Purnamasari, Susan Dian 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