Article Per Year (5 Year)
p-Index From 2021 - 2026
1.325
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of ICT Research and Applications Binus Business Review JUTIK : Jurnal Teknologi Informasi dan Komputer SINTECH (Science and Information Technology) Journal Jurnal Kridatama Sains dan Teknologi Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Ilmiah Telsinas Elektro, Sipil dan Teknik Informasi International Journal of Management Science and Information Technology (IJMSIT) Technologica International Journal of Accounting & Finance in Asia Pasific Jurnal Teknik Informatika dan Teknologi Informasi
Ngakan Nyoman Kutha Krisnawijaya
Universitas Pendidikan Nasional
Agriculture, Biological Sciences & Forestry 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences

Published : 15 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 15 Documents
Search

 1   2 
Analisis Determinan Karakter Siswa Menggunakan Explainable Machine Learning (SHAP) dan Klasterisasi Profil Sekolah Studi Kasus Rapor Pendidikan Provinsi Bali Dananjaya, Md. Wira Putra; Krisnawijaya, Ngakan Nyoman Kutha; Prathama, Gede Humaswara; Paramartha, I Gusti Ngurah Darma; Gama, Adie Wahyudi Oktavia
Jurnal Kridatama Sains dan Teknologi Vol 7 No 02 (2025): Jurnal Kridatama Sains dan Teknologi
Publisher : Universitas Ma'arif Nahdlatul Ulama Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53863/kst.v7i02.1988

Abstract

Strengthening student character is a key performance indicator in the Merdeka Belajar curriculum, but the identification of the school environment's most influential determinants of character achievement is often assumed. This study aims to quantitatively deconstruct the relationship between school climate and student character quality in Bali Province. Using the Indonesian Education Report dataset released by the Ministry of Primary and Secondary Education (Kemendikdasmen) for the 2023-2025 period with a total of 727 data entries, this study applies the Educational Data Mining methodology with the Random Forest algorithm enhanced by the Synthetic Minority Over-sampling Technique (SMOTE) to address data inequality. The novelty of this study lies in the use of SHapley Additive exPlanations (SHAP) for model transparency and K-Means Clustering for zoning mapping. Experimental results show the model is able to predict character achievement with 77.03% accuracy. The SHAP analysis revealed the interesting finding that Climate for Diversity (influence score of 0.45) and Climate for Gender Equality (0.22) were the strongest predictors, far exceeding the influence of Climate for Security (0.13). This finding challenges the common assumption that physical security is the single most important factor. Furthermore, the clustering analysis identified three school typologies in Bali, including one "Vulnerable" cluster that scored critically on gender equality and diversity despite having adequate security scores. This study recommends shifting the focus of education policy in Bali from a physical security approach to strengthening tolerance and gender equality programs, which have been shown to have a more statistically significant impact
Data Management System in Agriculture: A Bibliometric Analysis Krisnawijaya, Ngakan Nyoman Kutha
Technologica Vol. 5 No. 1 (2026): Technologica
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/technologica.v5i1.495

Abstract

Pertanian yang didasari oleh pemanfaatan dan manajemen data yang baik, dapat membantu petani dalam menyelesaikan permasalahan yang dihadapi dan juga dapat lebih tepat dalam mengambil sebuah keputusan. Menelusuri pengimplementasian data management system di literatur menjadi hal yang krusial dikarenakan sangat penting untuk mempelajari kesulitan dan tantangan yang dihadapi para peneliti sebelumnya guna meningkatkan kualitas dari sistem terdahulu. Dalam penelitian ini, metode analisis bibliometrik digunakan dengan tujuan untuk mengevaluasi literatur yang membahas terkait data management system di pertanian. Penggunaan metode ini dalam meninjau literatur pada topik data management di bidang pertanian masih terbatas, meskipun metode ini mampu memodelkan penelitian-penelitian yang paling signifikan dalam memberikan pengaruhnya pada perkembangan data management system di pertanian. Sehingga, studi ini bertujuan untuk mengisi gap penelitian dengan menggunakan analisis bibliometrik untuk mengidentifikasi penerapan data management system di bidang pertanian sebagai panduan untuk melihat tren dan arah dalam pengembangan pertanian cerdas. Secara keseluruhan, hasil analisis bibliometrik dengan teknik analisis co-word menunjukkan bahwa penelitian manajemen data di bidang pertanian adalah bidang multidisiplin. Penelitian ini berakar kuat pada manajemen data dan informasi untuk mendukung pengambilan keputusan dilihat dari 373 kemunculan kata kunci “information management” dan 192 kemunculan kata kunci “data management”. Bidang ini secara aktif mengintegrasikan teknologi baru seperti IoT dan blockchain untuk beralih menuju sistem pertanian yang lebih cerdas, efisien, dan transparan. Hasil dari analisis pada literatur memberikan pengetahuan yang cukup untuk melihat pola tren terkini pada penelitian data management system di pertanian.
The Impact of Perceived Risk and Trust on Electric Vehicle Adoption in Sustainable Tourism Regions Komang Bagus Lanang Prabawa; Putu Purnama Dewi; Ngakan Nyoman Kutha Krisnawijaya; A.A. Ngr. Eddy Supriyadinata Gorda
International Journal of Accounting and Finance in Asia Pasific (IJAFAP) Vol 8, No 3 (2025): October 2025
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/ijafap.v8i3.4494

Abstract

The influence of perceived risk and marketing communication on electric motorcycle purchase choices in Bali is examined in this study, with technological trust serving as the mediating factor. Despite Bali's global acclaim as an eco-tourism hub dedicated to sustainable progress, electric vehicle uptake among residents lags behind official benchmarks. A quantitative survey methodology is employed, drawing data from local inhabitants and subjecting it to Partial Least Squares–Structural Equation Modeling (PLS-SEM) grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT 3). Significant direct and indirect effects on purchase determinations channeled through trust in technology are revealed for both perceived risk and marketing communication. A pivotal mediation function is fulfilled by technological trust, whereby the adverse sway of perceived risk is attenuated and the favorable impact of marketing outreach amplified. Transparent, educational, and confidence-enhancing promotional tactics, coupled with enabling infrastructure and regulatory measures, are underscored by the outcomes as vital for hastening electric vehicle integration in tourism-centric sustainable locales.
Determinants of LMS Continuance Intention: An Extended UTAUT Approach Ngakan Nyoman Kutha Krisnawijaya; Ni Made Dhian Rani Yulianti; Ni Putu Dhanan Kumaradewi M; Anak Agung Adi Wiryya Putra
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.7403

Abstract

This study aims to analyze the factors influencing user satisfaction and continuance intention of Learning Management Systems (LMS) among international students in a mandatory academic ecosystem. This study has significant significance in bridging the theoretical gap between the cognitive adoption model (UTAUT) and the affective post-adoption evaluation (ECM) in a tech-savvy cross-cultural user segment. Using a causal-associative quantitative design, data were collected through a structured online questionnaire from 71 International Undergraduate Program (IUP) student respondents selected through a purposive sampling method. Data analysis was conducted using the Partial Least Squares–Structural Equation Modeling (PLS-SEM) method with the assistance of SmartPLS software version 4.0. The results of the path analysis showed that effort expectancy and social influence had a positive and significant effect on satisfaction, while performance expectancy and facilitating conditions did not show a significant effect. Furthermore, satisfaction was proven to exclusively mediate the effect of effort expectancy on continuance intention of LMS. The implications of this research confirm that in institutionally mandated systems, user motivation shifts to academic compliance. Therefore, higher education institutions are advised to prioritize eliminating everyday technical barriers through intuitive interface design to foster genuine international student satisfaction.
Deteksi Penyakit Daun Cabai Menggunakan Teknik Augmentasi Leafgan dan Deep Learning Model Ni Wayan Ariningsih; Ngakan Nyoman Kutha Krisnawijaya; Ni Luh Putu Ika Candrawengi; Adie Wahyudi Oktavia Gama
Jurnal Teknik Informatika dan Teknologi Informasi Vol. 6 No. 2 (2026): Agustus : Jurnal Teknik Informatika dan Teknologi Informasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jutiti.v6i2.7756

Abstract

Leaf diseases in chili plants, such as leaf spot and yellow virus, pose a significant threat to agricultural productivity in Indonesia, often leading to substantial economic losses for farmers. Traditional manual identification remains inefficient and highly dependent on individual expertise, which frequently results in inconsistent diagnosis. This research proposes an automated detection system utilizing the YOLOv8n deep learning architecture to provide a more reliable and real-time solution. A major hurdle in developing robust AI models for agriculture is the scarcity of balanced field dataset s and the presence of complex natural backgrounds. To address this, the study employs Leafgan , a generative augmentation technique capable of transforming healthy leaf images into realistic diseased samples while preserving the original field environment. By leveraging an attention mechanism, Leafgan  maintains high-frequency textural details, allowing the YOLOv8n model to generalize better across diverse environmental conditions. Data management is streamlined through the Roboflow platform to ensure consistent integration of primary and synthetic dataset s. The primary goal of this integration is to enhance model stability, aiming for a minimum mean Average Precision  (mAP) within actual plantation settings.
Co-Authors Adie Wahyudi Oktavia Gama Adrama, I Nyoman Gede Anak Agung Adi Wiryya Putra Anak Agung Ngurah Eddy Supriyadinata Gorda Bib Paruhum Silalahi Cokorda Pramartha Dananjaya, Md. Wira Putra Gede Humaswara Prathama Gusi Putu Lestara Permana I Gusti Ayu Agung Pradnya Dewi I Gusti Ayu Agung Pradnya Dewi I Gusti Ayu Agung Pradnya Dewi, I Gusti Ayu Agung I Gusti Ngurah Darma Paramartha I Nyoman Gede Adrama I Nyoman Kusuma Wardana I Wayan Aditya Suranata Komang Bagus Lanang Prabawa Ni Luh Putu Ika Candrawengi Ni Made Dhian Rani Yulianti Ni Putu Dhanan Kumaradewi M Ni Wayan Ariningsih Putu Dyah Permatha Korry Putu Irma Yunita Putu Purnama Dewi Putu Riska Indah Mentari