Article Per Year (5 Year)
p-Index From 2021 - 2026
5.332
P-Index
This Author published in this journals
All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Pendidikan Vokasi Jurnal Jurusan Pendidikan Teknik Elektro Jurnal Pendidikan Teknologi dan Kejuruan Jurnal Sains dan Teknologi JOIV : International Journal on Informatics Visualization JUTIK : Jurnal Teknologi Informasi dan Komputer JUTIM (Jurnal Teknik Informatika Musirawas) Journal of Educational Research and Evaluation WIDYA LAKSANA Journal of Education Technology Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal EDUTECH Undiksha Indonesian Journal of Data and Science Jurnal Pengabdian kepada Masyarakat Nusantara Unri Conference Series: Community Engagement JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia) Jurnal Profesi Insinyur Universitas Lampung YASIN: Jurnal Pendidikan dan Sosial Budaya MASALIQ: Jurnal Pendidikan dan Sains Al-DYAS : Jurnal Inovasi dan Pengabdian kepada Masyarakat Asian Journal of Science, Technology, Engineering, and Art International Journal of Artificial Intelligence in Medical Issues ALSYSTECH Journal of Education Technology Mikailalsys Journal of Advanced Engineering International International Journal of Education, Management, and Technology COUNS-EDU: The International Journal of Counseling and Education
Agus Aan Jiwa Permana
Universitas Pendidikan Ganesha
Religion Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

Published : 69 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 69 Documents
Search

 3   4   5   6   7 
Implementasi Mobile Homecare Berbasis User Centered Desain (UCD) I Made Bayu Sastra Wiguna; Ketut Agus Suputra; Agus Aan Jiwa Permana
MASALIQ Vol 6 No 1 (2026): MASALIQ: Jurnal Pendidikan dan Sains
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/masaliq.v6i1.8737

Abstract

Homecare services have become an important alternative in healthcare delivery because they allow patients to receive medical care directly at home with a higher level of comfort. However, the use of web-based homecare services still faces limitations when accessed via mobile devices, particularly in terms of usability and accessibility. This study aimed to develop a mobile-based homecare platform that focuses on enhancing user experience through a User-Centered Design (UCD) approach. A Research and Development (R&D) method was employed, following UCD stages that include understanding the context of use, identifying user needs, designing solutions, and evaluating the design. The application was developed using Flutter for the frontend and Laravel for the backend with a REST API architecture. Usability evaluation was conducted using the System Usability Scale (SUS) method involving 20 respondents. The evaluation results showed that the developed application obtained a SUS score of 86, which falls into the good usability category, indicating that the application is easy to use and well accepted by users. The application improves users’ ease of accessing homecare services and obtaining real-time service information. This study is expected to provide a practical solution for developing mobile-based healthcare applications and to serve as a reference for future research on usability and the application of User-Centered Design.
Pengembangan Media Pembelajaran Berbasis Augmented Reality Mata Pelajaran Bahasa Sunda untuk Siswa Sekolah Dasar Rissa Nurmalasari; Ni Ketut Kertiasih; Agus Aan Jiwa Permana
YASIN Vol 6 No 2 (2026): YASIN: Jurnal Pendidikan dan Sosial Budaya
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/yasin.v6i2.9451

Abstract

Sundanese language learning in elementary schools plays an important role in maintaining the continuity of the regional language and script, but students’ interest in and understanding of the material remain relatively low because the learning process tends to be conventional and has not optimally utilized technology. In addition, the development of Augmented Reality (AR)-based learning media that specifically contain material introducing pets and ornamental plants in the Sundanese language and script for elementary school students is still limited. This study aims to design learning media as a means of introducing the Sundanese language and script to elementary school students. This study used the Research and Development (R&D) method with the Multimedia Development Life Cycle (MDLC) model, which includes the stages of conceptualization, design, material collection, development, testing, and distribution. Material validation was carried out by two content experts using the Gregory method with a result of 0.93, which falls into the very high validity category, while the assessment of media aspects by one media expert obtained a score of 93.64% in the very good category. The user test involved four teachers and 20 students in Grades III to VI of elementary school using the System Usability Scale (SUS) questionnaire, with the teachers’ SUS score of 75 categorized as good (Grade C) and the students’ score of 80.25 categorized as good (Grade B). To measure the improvement in learning outcomes, a pretest and posttest were administered to 20 students using 10 question items, and the results of the Paired T-Test analysis showed a sig. (2-tailed) value of 0.01 < 0.05, indicating a significant improvement in learning outcomes after the use of the media. The developed media takes the form of an Android application that can be used offline and functions as an alternative interactive learning tool to support the preservation of the Sundanese language and script.
TETUN NEWS CLASSIFICATION: A MACHINE LEARNING APPROACH FOR TIMOR-LESTE'S DIGITAL MEDIA LANDSCAPE Ivonia Fatima Viegas; Agus Aan Jiwa Permana; Ni Ketut Kertiasih
Jurnal Pendidikan Teknologi dan Kejuruan Vol. 23 No. 1 (2026): Edisi Januari 2026
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jptk-undiksha.v23i1.112770

Abstract

This research addresses automated news classification for the Tetun language, Timor-Leste's national language, which remains underrepresented in NLP research. We constructed a machine learning framework to categorize Tetun news headlines from Tatoli.tl and DiliPostNews.com. Our contributions encompass: a specialized Tetun stopwords collection (85 words); a multi-source dataset of 37 articles across 5 categories; and comparative evaluation of four algorithms. Our optimal model attained 75% accuracy, exceeding the majority class baseline (70.27%) and random guessing (14.29%). Analysis revealed language mixing (51.4% Tetun, 32.4% mixed, 16.2% Portuguese). This study provides a proof-of-concept foundational groundwork for Tetun NLP applications.
Pengembangan Aplikasi untuk Mendiagnosa Gangguan Mental Pada Mahasiswa Berbasis Sistem Pakar agus aan jiwa permana
Jurnal Profesi Insinyur Universitas Lampung Vol. 7 No. 1 (2026)
Publisher : Fakultas Teknik Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpi.v7n1.389

Abstract

Gangguan kesehatan mental pada mahasiswa menjadi isu yang semakin penting di lingkungan pendidikan tinggi, khususnya pada mahasiswa Fakultas Teknik dan Kejuruan Universitas Pendidikan Ganesha yang menghadapi tuntutan akademik, praktikum, proyek, serta persaingan kompetensi yang tinggi. Keterbatasan layanan konseling dan rendahnya kesadaran mahasiswa untuk melakukan pemeriksaan psikologis menyebabkan banyak kasus gangguan mental tidak terdeteksi sejak dini. Penelitian ini bertujuan mengembangkan aplikasi diagnosis gangguan mental berbasis sistem pakar yang dapat membantu proses deteksi dini secara mandiri. Metode penelitian yang digunakan adalah Research and Development (R&D) yang meliputi analisis kebutuhan, akuisisi pengetahuan dari psikolog dan konselor, perancangan sistem, implementasi metode berbasis aturan, serta pengujian akurasi dan usability aplikasi. Sistem dikembangkan untuk mengidentifikasi beberapa kondisi kesehatan mental yang umum dialami mahasiswa, seperti stres akademik, kecemasan, depresi ringan, burnout, dan gangguan penyesuaian diri. Hasil penelitian berupa prototipe aplikasi yang mampu memberikan diagnosis awal beserta tingkat keyakinan dan rekomendasi tindak lanjut sesuai kondisi pengguna. Pengujian menunjukkan bahwa sistem mampu merepresentasikan pengetahuan pakar dan memberikan hasil diagnosis yang sesuai dengan kebutuhan skrining awal. Penelitian ini diharapkan dapat mendukung layanan kesehatan mental mahasiswa serta meningkatkan efektivitas deteksi dini gangguan mental di lingkungan perguruan tinggi.
Perancangan Desain High Fidelity User Interface pada Prototype Game Role-Playing Game 2D Top-Down Ainan Fajar Fatcha; Agus Aan Jiwa Permana; Ketut Agus Seputra
YASIN Vol 6 No 4 (2026): YASIN: Jurnal Pendidikan dan Sosial Budaya
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/yasin.v6i4.10723

Abstract

The rapid growth of the global game industry has increased competition among developers, making the quality of user interface (UI) design an important factor in shaping an optimal gaming experience. Although indie game development continues to grow, studies that specifically address high-fidelity UI design for 2D top-down role-playing game (RPG) prototypes remain limited. This study aimed to design and evaluate a high-fidelity UI prototype for a 2D top-down RPG game titled Dungeon Realm. This study employed a design and development approach guided by the Game Development Life Cycle (GDLC) methodology, which includes the initiation, preproduction, production, and testing phases. The design process began with capturing environment screenshots from Godot Engine as contextual background references, followed by the development of a high-fidelity prototype using Figma. The resulting prototype consisted of six UI screens, namely Main Menu, In-Game HUD, Pause Menu, Game Over, Settings, and How to Play. The evaluation was conducted through black box testing to verify the functional navigation flow across all interface screens, involving the researcher and two additional testers. The results showed that all defined navigation scenarios functioned according to the predetermined expected outputs, thereby confirming the structural integrity of the prototype design. These findings contribute to the application of user-centered design principles in game UI development and expand understanding of high-fidelity prototyping in indie RPG projects. This study concludes that systematic UI prototype design using the GDLC methodology can produce a coherent, navigable game interface with a validated design foundation before full implementation in Godot Engine.
Sistem Pendukung Keputusan Program Keluarga Harapan (PKH) Berbasis Analytic Network Process (ANP) Desa Sepang Kelod Ni Ketut Deni Julia Marlina; Agus Aan Jiwa Permana; I Nyoman Wahyu Wijaya Kusuma
MASALIQ Vol 6 No 4 (2026): MASALIQ: Jurnal Pendidikan dan Sains
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/masaliq.v6i4.11159

Abstract

The Family Hope Program is one of the government social assistance programs aimed at helping underprivileged communities. However, the process of determining recipients of Family Hope Program assistance in Sepang Kelod Village is still carried out manually through deliberation or village meetings, which has the potential to create subjectivity in decision-making. This study aims to design and implement a Decision Support System for Family Hope Program assistance recipients using the Analytic Network Process method. This study developed a web-based system used to manage community data and conduct the eligibility calculation process for prospective assistance recipients based on ten predetermined assessment criteria. The calculations were performed using Super Decisions software to determine criterion weights and the priority of alternative assistance recipients. The results show that the developed Decision Support System was able to generate rankings of prospective Family Hope Program assistance recipients based on scores from the calculation process using the Analytic Network Process method. This method was able to produce priority alternatives for assistance recipients more systematically based on the weight of each criterion. The conclusion of this study affirms that the implementation of a web-based Decision Support System using the Analytic Network Process method can assist Sepang Kelod Village officials in determining Family Hope Program assistance recipients more objectively, efficiently, and based on data. The implications of this study show the importance of utilizing decision-making technology to improve the accuracy, transparency, and accountability of social assistance management at the village level.
Comparison of CNN and CNN-LSTM Performance in Facial Expression Classification Based on FER2013 Dataset Putu Ananda Adi Savitri; Agus Aan Jiwa Permana; Ni Putu Novita Puspa Dewi
Asian Journal of Science, Technology, Engineering, and Art Vol 4 No 1 (2026): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v4i1.8252

Abstract

Although facial expression recognition (FER) using deep learning has received increasing attention in prior studies, research specifically addressing the comparative effectiveness of sequential modeling on static image data remains limited. This study aims to evaluate and compare the performance of a pure Convolutional Neural Network (CNN) model and a hybrid CNN–Long Short-Term Memory (CNN-LSTM) model in classifying seven basic facial expressions using the static FER2013 dataset. A quantitative experimental approach with a comparative study design was employed, utilizing the publicly available FER2013 dataset and two custom deep learning architectures. Data were obtained from FER2013 and model performance was evaluated using accuracy, precision, recall, F1-score, and AUC-ROC metrics. The findings indicate that the pure CNN model significantly outperformed the CNN-LSTM model, achieving a testing accuracy of 63.25% compared to 46.82% for the hybrid model; the CNN provided strong discrimination for visually distinct classes but continued to struggle with visually similar expressions. These results contribute to the theoretical development of deep learning architecture selection and expand understanding of the application of sequence models to static data. The study concludes that data characteristics (static versus temporal) play a crucial role in determining model effectiveness, and that for static datasets such as FER2013, a pure CNN constitutes the more appropriate choice. The implications of this research include theoretical contributions to the growing literature on deep learning-based FER and practical recommendations for developers to prioritize CNN architectures for non-temporal image classification tasks, while also highlighting opportunities for future research on transfer learning and attention mechanisms to better capture subtle expression nuances.
Sistem Pakar Pemilihan Menu Diet Sesuai Kondisi Kesehatan Pasien Ni Putu Ari Kusumadewi; Agus Aan Jiwa Permana; Gusti Putu Ayu Mas Meita Pradnya Swari; Kadek Prasta Yudhantara; Komang Adi Satya Mahagangga; I Komang Windra Artha
MASALIQ Vol 5 No 3 (2025): MASALIQ: Jurnal Pendidikan dan Sains
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/masaliq.v5i3.5439

Abstract

Expert Systems, a branch of artificial intelligence, are designed to replicate decision-making capabilities of human experts. This study focuses on developing an Expert System for Diet Menu Selection Based on Health Conditions. The system aims to assist users in planning nutritious and balanced diets tailored to individual health profiles, thereby enhancing health management through clear and practical guidelines. The Forward Chaining inference method is employed to derive conclusions from known health data, while the Agile development methodology supports iterative progress, adaptability to changes, and active stakeholder involvement to ensure optimal functionality. Given the rising public awareness of healthy living, this system presents a practical and innovative alternative for individuals seeking to manage their dietary habits effectively—without the need for constant consultations with nutritionists.
Machine Learning-Based Prediction of HIV/AIDS Infection and Treatment Effectiveness: A Clinical Dataset Analysis Agus Aan Jiwa Permana; I Gusti Ngurah Wikranta Arsa; Ahmad Naswin; Sumiyatun
International Journal of Artificial Intelligence in Medical Issues Vol. 3 No. 2 (2025): International Journal of Artificial Intelligence in Medical Issues
Publisher : Yocto Brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijaimi.v3i2.362

Abstract

The early and accurate prediction of HIV/AIDS infection is critical to improving clinical decision-making and ensuring effective patient management. This study presents a comprehensive machine learning-based approach to predict HIV/AIDS infection status and evaluate the effectiveness of antiretroviral treatments using a well-documented clinical dataset from 1996, comprising 2,139 patient records and 34 features. Through rigorous preprocessing, exploratory data analysis, and feature engineering, several new clinically relevant attributes were constructed, such as CD4/CD8 ratios and immunological change metrics. Four machine learning models—Logistic Regression, Support Vector Machine, Random Forest, and Gradient Boosting—were trained and evaluated. Among these, the Gradient Boosting classifier achieved the highest ROC-AUC score of 0.9335, while Random Forest provided strong predictive performance with a ROC-AUC of 0.9180 and was selected for further evaluation due to its model transparency. Key features influencing infection prediction included CD4+ and CD8+ dynamics, baseline immunological levels, and treatment history. Additionally, the study examined treatment effectiveness by analyzing CD4+ cell count responses across different therapy types. The combination of ZDV and ddI emerged as the most effective regimen, improving immune outcomes and lowering infection rates, while ZDV monotherapy showed the least favorable results. This work underscores the potential of machine learning as a clinical decision support tool in HIV/AIDS care and provides data-driven insights into treatment optimization. Future studies should incorporate longitudinal patient data and real-world clinical environments for broader applicability.
Co-Authors A. A. Gede Yudhi Paramartha Agus Halid, Agus Agus Seputra I Ketut Ahmad Naswin Ainan Fajar Fatcha Alkautsar, Yoga Rizky Artha, I Kadek Bayu Danu Darmayasa, Ngakan Nyoman DIATMIKA, KETUT TUTUR Elly Herliyani Erma Susanti Gede Aditra Pradnyana Gede Arya Ardivan Pratama Saputra Gede Nanda Ageng Nugraha Gede Saindra Santyadiputra Gede Wahyu Purnama Gede Wahyu Purnama Gunawan, I Gede Made Deny Surya Gusti Putu Ayu Mas Meita Pradnya Swari I Gd Ny Werdyana Guna Mertha I Gusti Agung Putu Bagus Satria Wicaksana I Gusti Ayu Purnamawati I Gusti Ngurah Wikranta Arsa I Gusti Ngurah Wikranta Arsa, I Gusti Ngurah I Kadek Nicko Ananda I Kadek Suranata I Ketut Gading I Ketut Purnamawan I Komang Windra Artha I Made Ardwi Pradnyana I Made Bayu Sastra Wiguna I Made Pageh I Made Putrama I Made Sukarsa I Made Sukarsa I Nyoman Laba Jayanta I Nyoman Saputra Wahyu Wijaya I Nyoman Saputra Wahyu Wijaya I Nyoman Wahyu Wijaya Kusuma I Putu Dion Arditya Ida Bagus Sebali Mahesa Yogi Ifdil Ifdil Ika Arfiani Ivonia Fatima Viegas Joe Aqilla Vandyta Kadek Prasta Yudhantara Kadek Wirahyuni Ketut Agus Suputra Komang Adi Satya Mahagangga Komang Setemen Kusuma, I Komang Arya Adi Made Padmi Wirayani Made Sudarma Made Sudarma Marta Dinata, Kadek Prima Giant Ni Ketut Deni Julia Marlina Ni Ketut Kertiasih Ni Luh Ita Purnami Ni Putu Ari Kusumadewi Ni Putu Dwi Sucita Dartini Ni Putu Novita Puspa Dewi Ni Wayan Marti Nugraha, I Gusti Bagus Baskara Octavia, I Gusti Ayu Adiani Okthen Orlanda Naitboho pande sindu Pande, Satria Imawan Adi Putra Pande Pracasitaram, Gede Made Surya Bumi Pracasitaram, I Gede Made Surya Bumi Prakoso, Paholo Iman Pramudya, Dewa Gede Bhaskara Pranadi Sudhana, I G P Fajar Puridiasta, I Gede Deindra Dwija Putrama, Made Putu Ananda Adi Savitri Putu Ony Andewi PUTU SUGIARTAWAN Rezania Agramanisti Azdy, Rezania Agramanisti Rissa Nurmalasari Rukmi Sari Hartati Rukmi Sari Hartati Saputra Wahyu Wijaya Siami, M. Ikbal Sindu, I Gede Partha Sumiyatun Sunia Raharja, I Made Tarigan, Thomas Edyson Widodo Prijodiprodjo Wijaya, I Gede Saputra Wahyu Winata, I Gede Arya Wirayani, Made Padmi Witjaksana, Putu Gede Dimas Yoga Rizky Alkautsar Yoga Sucipta, Gede