Article Per Year (5 Year)
p-Index From 2021 - 2026
7.335
P-Index
This Author published in this journals
All Journal (JELIKU) Jurnal Elektronik Ilmu Komputer Udayana Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Ilmiah Kursor Jurnal Sistem dan Informatika Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) CESS (Journal of Computer Engineering, System and Science) Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi) Journal of Information Technology and Computer Science (JOINTECS) Jurnal Ilmiah FIFO Informatics for Educators and Professional : Journal of Informatics Jurnal Informatika Universitas Pamulang SISFO WIDYABHAKTI Jurnal Ilmiah Populer @is The Best [Accounting Information System & Information Technology Business Enterprise] Jurnal Pengabdian Masyarakat Borneo bit-Tech Reswara: Jurnal Pengabdian Kepada Masyarakat Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Ilmiah Pengabdian dan Inovasi Seminar Ilmiah Nasional Teknologi, Sains, dan Sosial Humaniora (SINTESA) Jurnal Pengabdian Informatika (JUPITA) SEMNASTERA (Seminar Nasional Teknologi dan Riset Terapan) Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) Jurnal Nasional Teknologi Informasi dan Aplikasinya
I Gede Surya Rahayuda
Universitas Udayana
Religion 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 Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Nursing Social Sciences Other

Published : 66 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 66 Documents
Search

 3   4   5   6   7 
Aplikasi Pendidikan Dan Pelatihan Koperasi Di Koperasi Simpan Pinjam Bada Lestari I Ketut Santa Wijaya; Cokorda Rai Adi Pramartha; I Gede Surya Rahayuda
Jurnal Pengabdian Informatika Vol. 2 No. 3 (2024): JUPITA Volume 2 Nomor 3, Mei 2024
Publisher : Jurusan Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana

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

Abstract

In an era of ever-evolving technology, using applications has become an integral part of our daily lives. Information technology plays an important role in human life, especially in the field of small and medium enterprises such as cooperatives. However, co-operative development remains stagnant, with only 13% of all co-operatives having digital systems in place. This study therefore aims to develop an educational and training application for co-operative members to improve their knowledge and skills on co-operative principles and related undertakings. Through this application, cooperatives are expected to improve the accessibility, effectiveness and efficiency of their members' education, thereby increasing awareness of cooperative principles and the sustainability of cooperative activities as a whole.
Perancangan Sistem Handwriter Aksara Bali untuk Latihan Menulis Menggunakan Enterprise Architecture Berbasis Zachman Framework Linda Santiari, Ni Putu; I Gede Surya Rahayuda
CESS (Journal of Computer Engineering, System and Science) Vol. 10 No. 2 (2025): Juli 2025
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v10i2.67183

Abstract

Pelestarian aksara daerah, khususnya aksara Bali, merupakan tantangan penting di era digital. Salah satu upaya yang dapat dilakukan adalah dengan mengembangkan sistem informasi yang dapat mendukung proses belajar menulis aksara Bali secara interaktif. Penelitian ini bertujuan untuk merancang sistem Handwriter Aksara Bali untuk latihan menulis, dengan pendekatan Enterprise Architecture berbasis Zachman Framework. Metode yang digunakan adalah studi kasus dengan tahapan analisis kebutuhan dan perancangan arsitektur sistem. Perancangan dilakukan dengan memetakan enam perspektif utama dalam Zachman Framework, yaitu Planner, Owner, Designer, dan Builder, yang mencakup aspek data, proses, lokasi, pelaku, waktu, dan motivasi sistem. Evaluasi sistem dilakukan secara konseptual menggunakan pendekatan validasi arsitektur dan skenario penggunaan sistem. Secara kualitatif, rancangan dievaluasi berdasarkan kelengkapan, kesesuaian dengan kebutuhan pengguna, serta keterwakilan artefak dalam setiap sel Zachman. Hasil dari penelitian ini berupa rancangan arsitektur sistem yang terstruktur, mencakup model data, desain antarmuka, arsitektur jaringan, dan spesifikasi teknis sistem. Dengan perancangan ini, diharapkan pengembangan sistem Handwriter Aksara Bali dapat dilakukan secara lebih terarah, efisien, dan sesuai dengan kebutuhan pengguna, serta menjadi langkah awal dalam mendukung pelestarian aksara Bali melalui inovasi digital. 
Analisis Perbandingan XGBoost dan LightGBM dalam Prediksi Penjualan Ritel Walmart Store Sales I Gusti Ayu Riyani Astarani; I Gede Surya Rahayuda
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 3 No. 4 (2025): JNATIA Vol. 3, No. 4, Agustus 2025
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2025.v03.i04.p01

Abstract

Sales prediction is a crucial aspect in the retail industry for optimizing business strategies and inventory management. As a global retail company with a large-scale operation, Walmart faces significant challenges in efficiently managing its supply chain and inventory. This study conducts a comparative analysis between the Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM) algorithms in the context of retail sales prediction using the Walmart Store Sales dataset. The dataset consists of 6,436 records with 8 attributes. The research methodology implements a comprehensive machine learning approach, including data preprocessing, feature selection, dataset splitting (80:20), model training, and evaluation using standard metrics. The analysis results show that LightGBM provides superior prediction performance, with an MSE of 0.0341, MAE of 0.1120, RMSE of 0.1847, and R² of 0.9663. In comparison, XGBoost yields an MSE of 0.0408, MAE of 0.1194, RMSE of 0.2021, and R² of 0.9596. The consistent superiority of LightGBM across all evaluation metrics indicates that this algorithm is more optimal for the Walmart sales prediction case. Additionally, feature analysis shows that the variable Store contributes the most to the predictive model, while Fuel Price has a relatively minor impact. This study emphasizes that selecting the appropriate machine learning algorithm significantly affects optimal prediction outcomes, particularly in a complex, data-driven retail industry.
Desain Aplikasi MindSpare sebagai Media Literasi dan Dukungan Kesehatan Mental dengan Metode Design Thinking Asa Prameswari Karso; I Gede Surya Rahayuda
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 1 (2025): JNATIA Vol. 4, No. 1, November 2025
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2025.v04.i01.p11

Abstract

Mental health is a global issue that needs attention, especially for adolescents aged 16-24 years. Previous research shows that the mental health of adolescents of this age affects how their well-being is. Then, based on preliminary research that has been conducted on adolescents of that age, 83% of respondents have never used a mental health application with one of the reasons is that they feel they don't need the application. Therefore, in this study, a mental health application design was made as a medium of support for someone experiencing mental health problems and as a literacy medium for someone who is mentally healthy to be more aware of the surrounding environment. This research process is carried out using the Design Thinking method so that the application built can meet user needs. The design that has been made is tested using the UEQ scale and most aspects shows Excellent rating, with the highest score in the Attractiveness aspect, with an average value of 2.29.
IMPLEMENTASI APLIKASI ALTHEAD CHECKER UNTUK OTOMATISASI PEMERIKSAAN SEO PADA ALT TAG IMAGE DAN HEADING TAG (STUDI KASUS DI PT TIMEDOOR) Ni Komang Ayu Juliana; Made Agung Raharja; I Gede Surya Rahayuda
Jurnal Pengabdian Informatika Vol. 4 No. 1 (2025): JUPITA Volume 4 Nomor 1, November 2025
Publisher : Jurusan Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana

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

Abstract

Optimasi mesin pencari (SEO) menjadi faktor penting dalam meningkatkan visibilitas dan daya saing sebuah website. Struktur headings dan alt tag image yang tepat merupakan komponen krusial dalam SEO yang efektif. Kegiatan ini bertujuan mengimplementasikan AltHead Checker sebagai solusi otomatisasi dalam proses Quality Assurance (QA) untuk meningkatkan efisiensi dan akurasi optimasi website. Pengembangan aplikasi mencakup perancangan prototipe hingga implementasi penuh di PT Timedoor Indonesia. Hasil evaluasi menunjukkan peningkatan efisiensi waktu sebesar 85-90% untuk pengecekan struktur heading dan 78-80% untuk alt tag image. Akurasi pengecekan juga meningkat signifikan dengan penurunan tingkat kesalahan dari rata-rata 15% menjadi 3,5%, menghasilkan peningkatan akurasi sebesar 77%. Implementasi AltHead Checker terbukti efektif dalam meningkatkan kualitas dan kecepatan proses QA, serta memastikan konsistensi standar SEO di setiap proyek PT Timedoor.
RANCANG BANGUN SISTEM MANAJEMEN SOAL UNTUK LEARNING MANAGEMENT SYSTEM DI PT TIMEDOOR INDONESIA Kadek Belvanatha Gargita Satwikananda; I Gede Surya Rahayuda; Made Agung Raharja
Jurnal Pengabdian Informatika Vol. 4 No. 2 (2026): JUPITA Volume 4 Nomor 2, Februari 2026
Publisher : Jurusan Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana

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

Abstract

Kegiatan ini bertujuan untuk merancang dan menerapkan fitur penilaian otomatis berbasis kecerdasan buatan pada Learning Management System PT Timedoor Indonesia, guna memfasilitasi penilaian soal isian singkat dan esai yang sebelumnya dilakukan secara manual. Metode yang digunakan meliputi pengembangan sistem manajemen soal dengan modul kecerdasan buatan yang mampu mengevaluasi kesamaan makna antara jawaban pengguna dan kunci jawaban. Hasil kegiatan ini berupa laman login, laman daftar soal, laman tambah dan edit soal, serta laman penilaian oleh kecerdasan buatan yang menampilkan skor dan alasan penilaian secara otomatis. Dengan adanya fitur ini, learning management system diharapkan dapat mengurangi beban tenaga manusia, meningkatkan efisiensi penilaian, dan memperluas variasi soal. Implementasi kecerdasan buatan ini tidak hanya menawarkan solusi praktis, tetapi juga peluang untuk pengembangan lebih lanjut dalam peningkatan layanan learning management system di masa depan.
PELATIHAN FOTO DAN VIDEO UNTUK PEMASARAN MEDIA SOSIAL IRT JAMU HERBAL KELOMPOK KOLOK DESA BENGKALA Ni Putu Linda Santiari; I Putu Ramayasa; I Wayan Kayun Suwastika; Sindyawati Rari Duli Goran Tokan; Ni Nyoman Supuwiningsih; I Gede Surya Rahayuda
Jurnal Pengabdian Informatika Vol. 4 No. 1 (2025): JUPITA Volume 4 Nomor 1, November 2025
Publisher : Jurusan Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana

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

Abstract

This community service activity aimed to enhance the digital marketing capacity of home-based herbal drink enterprises operated by the deaf community in Bengkala Village, Buleleng Regency. The main problems faced by the partner were low digital marketing literacy and limited skills in producing attractive visual product content, resulting in reliance on conventional promotion methods and limited market reach. The implementation employed a descriptive-participatory approach, including initial observation, brief interviews, offline training on basic product photography and video recording using smartphones, and online training on the use of Facebook as a digital marketing platform. The results indicated an improvement in the partner’s understanding of social media functions for marketing purposes and basic competencies in product photography and video techniques, such as lighting, shooting angles, and product arrangement. Although consistent promotional content has not yet been produced, the training successfully built initial readiness and awareness of the importance of digital marketing. This activity contributes to strengthening the capacity of home-based enterprises by utilizing local potential and supporting the inclusive values of Bengkala Village.
Analisis Sentimen Gemini AI Menggunakan Multinomial Naïve Bayes dengan TF-IDF dan BoW Yeremi Kornelius Purba; I Gede Surya Rahayuda
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 4 No. 2 (2026): JNATIA Vol. 4, No. 2, Februari 2026
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2026.v04.i02.p03

Abstract

The development of artificial intelligence Large Language Models, such as Gemini AI, has attracted widespread public attention. The advanced development of Gemini AI is inseparable from valuable public reviews for product evaluation, but the massive amount of reviews makes manual analysis inefficient. This study aims to conduct sentiment analysis on Gemini AI application reviews using the Multinomial Naïve Bayes classification algorithm. The primary focus is to compare the performance of two feature extraction methods: Term Frequency-Inverse Document Frequency (TF-IDF) and Bag-of-Words (BoW). A total of 1,000 reviews were collected from the Google Play Store, which, after undergoing preprocessing and data labelling, resulted in 438 data points for analysis. The model evaluation results show that TF-IDF feature extraction provides superior performance with an accuracy of 88% and an F1-Score of 93%, compared to BoW, which produces an accuracy of 84% and an F1-Score of 91%. These results indicate that the TF-IDF feature extraction method is more effective in analysing the sentiment of Gemini AI app reviews using Multinomial Naïve Bayes.
Memanfaatkan Motion Sensor untuk Pencegahan Pencurian Barang Rafly Shaquille Subhan; I Gede Surya Rahayuda
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 2 No. 1 (2023): JNATIA Vol. 2, No. 1, November 2023
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2023.v02.i01.p02

Abstract

In response to escalating security concerns, this research investigates the potential of motion sensors as a cutting-edge technology for theft prevention. The study employs experimental and quantitative methods to evaluate the efficacy of motion sensors in diverse settings, focusing on the prevention of helmet theft, a significant issue in various regions. Utilizing Packet Tracer simulation, the implementation of motion sensors is explored, emphasizing factors such as placement, sensitivity settings, and effective monitoring. The findings demonstrate a substantial reduction in theft incidents, attributing this success to the swift detection of suspicious movements and prompt alerts to authorities. The research underscores the importance of proper usage and maintenance in maximizing the anti-theft capabilities of motion sensors. By simulating the implementation through Packet Tracer, the study not only leverages conceptual and theoretical aspects but also provides practical testing replicable and analyzable through simulations. The research aims to contribute valuable insights into the application of motion sensor technology for preventing helmet theft and encourages the widespread adoption of quality helmets for enhanced safety. 
Optimasi C4.5 Berbasis PSO untuk Prediksi Kanker Payudara dengan Data BC Wisconsin Tun Pasek Sarwiko Dipranoto; I Gede Surya Rahayuda
Jurnal Nasional Teknologi Informasi dan Aplikasinya Vol. 3 No. 3 (2025): JNATIA Vol. 3, No. 3, Mei 2025
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JNATIA.2025.v03.i03.p07

Abstract

Breast cancer is a type of cancer that often arises from the development of abnormal cells in breast tissue, which then grow uncontrollably. In Indonesia, breast cancer cases are the highest compared to other types of cancer and are one of the main causes of death. This research aims to optimize the C4.5 algorithm using Particle Swarm Optimization (PSO) to predict breast cancer using the Wisconsin Breast Cancer dataset. Breast cancer remains one of the leading causes of death in women worldwide, emphasizing the importance of early detection and accurate classification. Previous research has demonstrated the effectiveness of various algorithms, including Decision Tree, Naive Bayes, and K-Nearest Neighbors, in diagnosing breast cancer, with K-Nearest Neighbors often demonstrating superior accuracy. This research evaluates the performance of the C4.5 algorithm, both before and after being optimized with PSO. Preliminary results show that the C4.5 algorithm without optimization achieves 94% accuracy. After optimization with PSO, the accuracy increased to 96%, highlighting the potential of PSO in improving prediction models for breast cancer diagnosis. 
Co-Authors A. A. Ayu Meitridwiastiti Agus Muliantara Ahmad Royyan Fath Anggrek, Denise Valeria Arituddiniyah, Ira Asa Prameswari Karso Buce Trias Hanggara Cokorda Pramartha Cokorda Rai Adi Pramartha Dadang Hermawan Dananjaya, I Gede Agastya Dewi Yanti Liliana Diah Priharsari Dwi Cahya Astriya Nugraha Fath, Ahmad Royyan Gde Agung Mandala Bendesa Haposan Simangunsong I Dewa Made Bayu Atmaja Darmawan I Gede Hendra Suputra I Gede Satria Wibawa I Gusti Ayu Riyani Astarani I Gusti Bagus Agung Kusuma Atmaja I Gusti Bgs Darmika Putra I Gusti Ngurah Anom Cahyadi Putra I Kadek Dwi Adnyana I Ketut Gede Suhartana I Ketut Santa Wijaya I Komang Ari Mogi I Made Widhi Wirawan I Nyoman Sunda I Putu Gede Hendra Suputra I Putu Ramayasa, I Putu I Wayan Jepriana Indira Putri Hendini Ira Arituddiniyah Ismiarta Aknuranda Jamrud Ivan Hartono Kadek Belvanatha Gargita Satwikananda Kesuma, Arya Dharma Ketut Agus Cahyadi Nanda Kevin Moses Waleleng Komang Bhargo Bhaskara Komang Kartika Noviyanti Linda Santiari Linda Santiari, Ni Putu Luh Gede Astuti M. Gilvy Langgawan Putra Made Putra Teguh Pramana Ngakan Made Alit Wiradhanta Ni Kadek Sukerti Ni Komang Ayu Juliana Ni Komang Purnami Ni Luh Gede Pivin Suwirmayanti Ni Made Dwijayani Ni Nyoman Muryatini Ni Nyoman Supuwiningsih Ni Putu Anita Dewi Ni Putu Linda Santiari Ni Putu Linda Santiari Noveria Anggraeni Fiaji Pramathana, Raindra Pratami, Ni Wayan Cahya Ayu Prathama, Hammam Akmal Putu Adi Guna Permana Putu Arya Dharma Kesuma Putu Vidi Nararia Ningrat Rafly Shaquille Subhan Raharja, Made Agung Santiari, Linda Simamora, Monika Hermiani Yolanda Sindyawati Rari Duli Goran Tokan Subhan, Rafly Shaquille Suwastika, I Wayan Kayun Suwastika, I Wayan Kayun Teguh Pramana, Made Putra Tun Pasek Sarwiko Dipranoto Yeremi Kornelius Purba Zulvarina, Prima