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Jurnal Krisnadana
Published by Yayasan Sinergi Widya Nusantara
ISSN : 28083520     EISSN : 28083563     DOI : 10.58982
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering
Jurnal Krisnadana merupakan jurnal yang dapat menjadi wadah bagi civitas akademika dan kalangan profesional dalam mempublikasikan karya ilmiah ataupun hasil penelitiannya dengan tetap mengutamakan orisinalitas karya, pengembangan kelimuan dan kontribusi dalam berbagai bidang. Jurnal Krisnadana berfokus pada bidang Ilmu Komputer, Sistem Kendali, dan Jaringan. Fokus dan Ruang lingkup pada Jurnal Krisnadana (Komputer, Sistem Kendali, & Jaringan) yang dapat menjadi topik makalah atau penelitian meliputi berbagai bidang minat, diantaranya: 1) Rekayasa perangkat lunak; 2)Sistem Informasi; 3) Sistem Pendukung Keputusan (SPK); 4) Sistem Pakar; 5) Kecerdasan Buatan; 6) Aplikasi Mobile; 7) Pengolahan Citra; 8) Robotika; 9) Smarts System; 10) Cloud Technology; 11) Image Processing; 12) Internet Of Things (IOT); 13) Jaringan Komputer; 14) Komputasi Paralel; 15) Sistem Terdistribusi; 16) Data Analytic; 17) Audit Teknologi Informasi; 18) Telekomunikasi dan Pemrosesan Sinyal; 19) Otomasi kontrol (Control Automation); 20) Topik studi relevan lainnya.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 145 Documents
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Comparison of Deep Learning Methods for Product Sales Forecasting at The Catur Sasih Cooperative Four Seasons Hotel I Putu Agus Eka Darma Udayana; Putu Yoka Angga Prawira; Ni Made Jeni Aprilia Dewi
Jurnal Krisnadana Vol 5 No 3 (2026): Jurnal Krisnadana May - July 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/avs92s73

Abstract

This study aims to assist Koperasi Catur Sasih Hotel Four Seasons in determining the most appropriate sales forecasting method based on the characteristics of the cooperative’s sales data, as fluctuating demand creates challenges in determining optimal inventory levels. The methods compared in this study are Long Short-Term Memory (LSTM) and Autoformer, using monthly sales data from January 2020 to December 2024 for three products, namely Yakult, Bavarois Roti Pizza/Sisir, and Marlboro Lights 20. The results indicate that the Autoformer method provides more accurate sales predictions than the LSTM method in forecasting product sales at Koperasi Catur Sasih, as evidenced by the lowest error values according to the RMSE, MAE, and MAPE metrics. For the Yakult product, the Autoformer method achieved an RMSE of 82.4660, an MAE of 72.2140, and a MAPE of 9.65%. For the Bavarois Roti Pizza/Sisir product, the Autoformer method produced an RMSE of 18.2666, an MAE of 15.4194, and a MAPE of 11.37%. Furthermore, for the Marlboro Lights 20 product, the Autoformer method resulted in an RMSE of 44.3490, an MAE of 37.0785, and a MAPE of 12.36%. In addition, noise reduction testing by removing the first three months of 2020 as an anomalous data period resulted in a decrease in error values for both methods. Nevertheless, Autoformer consistently outperformed LSTM in sales forecasting, both before and after the noise removal process.
Sentiment Analysis of Public Opinion on Danantara Via Social Media X Welda Welda; Aniek Suryanti Kusuma; I Putu Robin Laksamana Putra
Jurnal Krisnadana Vol 5 No 3 (2026): Jurnal Krisnadana May - July 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/ha2x2j34

Abstract

Social media has become a primary channel for the public to express opinions on various issues, including public services. One topic that has been widely discussed on platform X is Daya Anagata Nusantara (DANANTARA), a government-owned strategic investment management agency. Public sentiment toward DANANTARA is divided into three categories—positive, negative, and neutral—which may influence broader public perception. This study aims to analyze public sentiment toward DANANTARA using data obtained from platform X. The methods employed include web scraping for automated data collection and the Naïve Bayes algorithm for classifying sentiment into three labels: positive, negative, and neutral. Platform X was selected because it has over 19.5 million active users in Indonesia, making it a representative data source. From the 930 data points analyzed, it was found that public sentiment toward DANANTARA is predominantly neutral. This research is expected to provide an objective overview of public perception regarding DANANTARA.
Interactive Solar System Media as Teacher's Aid for Elementary Students Aniek Suryanti Kusuma; Welda Welda; I Ketut Agus Sanjaya Damu
Jurnal Krisnadana Vol 5 No 3 (2026): Jurnal Krisnadana May - July 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/qxnfk086

Abstract

The primary challenge in teaching science on the topic of the solar system at the elementary school level lies in the abstract nature of its concepts, which are difficult to visualize using conventional media. This condition may lead to monotonous learning and student misconceptions. This study aims to develop an interactive multimedia-based teaching medium to address these issues. The research employed the Research and Development (R&D) method utilizing the ADDIE model (Analyze, Design, Develop, Implement, Evaluate), with the implementation focused up to the Development and Formative Evaluation stages. The medium was developed based on a needs analysis conducted at SD Pelangi Jimbaran, resulting in a prototype with a complete structure comprising an opening page, main menu, instructions, video materials, and an evaluation quiz. Validation results from subject matter experts and media experts indicated a very high level of feasibility, with scores of 84% and 86%, respectively. The study concludes that the developed interactive teaching medium for solar system introduction is highly valid, feasible, and ready for implementation. This research contributes to the provision of an innovative teaching aid for teachers and serves as a foundation for further studies to empirically examine the medium’s effectiveness in classroom settings.
A Decision Support System for Selecting High-Achieving Students at SDN 3 Montong Baan Using the Weighted Product Method Izzul Anshori; Hendriawan Hadi; Lalu Puji Indra Kharisma; Sarita Sarita
Jurnal Krisnadana Vol 5 No 3 (2026): Jurnal Krisnadana May - July 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/mc5fjx04

Abstract

The assessment of outstanding students is essential to recognize their achievements and motivate them to improve their academic and non-academic abilities. At SDN 3 Montong Baan, the manual selection process is considered inefficient and tends to be subjective. This study aims to design a decision support system (DSS) using the Weighted Product (WP) method to evaluate students based on criteria such as academic grades, attendance, and personality. The system was developed using the Waterfall model through observation, interviews, and a literature review. As a result, the system can provide recommendations objectively, systematically, and transparently, helping the school make more accurate and efficient decisions in selecting outstanding students.
Implementation of Containerization on Village Information Systems (OpenSID) Using Docker for Server Resource Efficiency I Wayan Yudik Pradnyana; I Wayan Ady Juliantara
Jurnal Krisnadana Vol 5 No 3 (2026): Jurnal Krisnadana May - July 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/4dj8p556

Abstract

The digitalization of village governance in Indonesia faces significant challenges in the form of inconsistencies in the server environment (environment drift) that hinder the stability and scalability of the Village Information System (OpenSID). This research aims to implement the Container-Based Deployment method as an operational approach based on the DevOps paradigm to standardize village digital infrastructure. The method used is Infrastructure as Code (IaC) by integrating OpenSID applications and MariaDB databases into isolated Docker containers, with service access through specific port mapping for both primary application access and database management. The results showed that the use of containerization successfully overcame the complexity of manual configuration, with a 100% success rate of meeting system dependencies. This architecture allows for identical system replication, deployment time efficiency, and ease of service access. This research produces a reliable, portable, and efficient system architecture model for village governments in supporting the transformation of digital public services that are more stable and accessible.
Adaptive UI/UX Evaluation of BufferSee AR Using SUS Ketut Sepdyana Kartini; I Nyoman Tri Anindia Putra
Jurnal Krisnadana Vol 5 No 3 (2026): Jurnal Krisnadana May - July 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/fbyb4b90

Abstract

This study aimed to develop and evaluate an adaptive UI/UX design for BufferSee AR, an augmented reality-based mobile learning application designed to support chemistry learning, particularly buffer solution material. The initial version of BufferSee AR already provided several learning features, including AR Camera, learning materials, practice questions, quizzes, user guidance, marker download, and 3D visualization. However, usability issues were identified in the early interface, particularly in navigation clarity, icon consistency, learning flow, user guidance, and accessibility for students with different levels of digital literacy. This research employed the ADDIE development model consisting of Analysis, Design, Development, Implementation, and Evaluation. The usability evaluation was conducted using the System Usability Scale (SUS) involving 30 student respondents. The evaluation results showed that the initial version obtained an average SUS score of 55, categorized as Marginal. After adaptive UI/UX redesign, the average SUS score increased to 82.5, categorized as Acceptable/Good. These findings indicate that adaptive UI/UX design improved efficiency, effectiveness, and user satisfaction in using BufferSee AR as an interactive chemistry learning medium.
Sentiment Analysis of the National Capital Relocation to IKN Using TF-IDF and Logistic Regression Ni Wayan Jeri Kusuma Dewi; Indra Pratistha; Tasya Alifah; Ni Komang Sri Wahyuni
Jurnal Krisnadana Vol 5 No 3 (2026): Jurnal Krisnadana May - July 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/yhck9073

Abstract

The relocation of the national capital from Jakarta to East Kalimantan has sparked various reactions from the public, many of which have been expressed through social media platforms such as YouTube. This study aims to analyze public responses from the perspective of sentiment and emotion toward the policy. The methodology employed involves keyword weighting using TF-IDF and Logistic Regression techniques. The data was then processed through preprocessing stages and labeled using the EmoLex Dictionary. Out of a total of 5,835 comments analyzed, the results showed that 2,180 comments (37.4%) were neutral in sentiment, followed by 2,077 comments (35.6%) with positive sentiment and 1,578 comments (27.0%) containing negative sentiment. In emotion classification, anger was the most dominant emotion, with 2,525 comments (43.3%), followed by trust with 897 comments (15.4%), anticipation with 750 comments (12.9%), and other emotions, such as disgust, neutral, sadness, fear, joy, and surprise, with smaller proportions. The results of the model performance evaluation for sentiment classification showed an accuracy of 93,9%, a precision of 94,6%, a recall of 93,0%, and an F1-score of 93,5%.  
Adaptive User Interfaces: A Systematic Literature Review I Gusti Ngurah Darma Paramartha; Md. Wira Putra Dananjaya; Adie Wahyudi Okatavia Gama; Gusi Putu Lestara Permana
Jurnal Krisnadana Vol 5 No 3 (2026): Jurnal Krisnadana May - July 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/6msy0m84

Abstract

Adaptive User Interfaces (AUIs) dynamically adjust interface elements based on user behavior, context, and preferences to enhance usability and performance. This systematic literature review, conducted following PRISMA 2020 guidelines, synthesizes evidence from 44 studies across five major academic databases. The review examines methodologies, adaptation techniques, implementation platforms, and the impact of AUIs on user experience. Results demonstrate that machine learning—particularly reinforcement learning and deep learning—dominates adaptation techniques and consistently yields superior task performance (6.67–27.3% improvement over static interfaces). Mobile applications and web interfaces are the most prevalent deployment platforms. Key challenges include predictability, privacy, cognitive load management, and user autonomy. Future research should prioritize explainable AI integration, standardized evaluation frameworks, and longitudinal studies.
Student Perceptions of the Use of Technology in Mathematics Learning Ni Wayan Suardiati Putri; Kadek Suryati; Evi Dwi Krisna; Ni Kadek Ulan Cahyani
Jurnal Krisnadana Vol 5 No 3 (2026): Jurnal Krisnadana May - July 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/p1srk603

Abstract

The use of technology in mathematics learning is crucial for supporting digital learning in higher education, particularly in helping students understand abstract mathematical concepts. This study aims to determine students' perceptions of the use of technology in mathematics learning. The study used a quantitative descriptive approach with a survey method. The subjects were 130 students who had participated in technology-based mathematics learning. The instrument was a five-level Likert-scale questionnaire with six indicators: ease of use, benefits of technology, interest and motivation, interaction and engagement, obstacles to use, and support for understanding mathematical concepts. Data were analyzed using percentages. The results showed that students had positive perceptions. The dominant response was agreement for the ease of use indicator (53.54%), benefits of technology (51.69%), interest and motivation (44.15%), interaction and engagement (51.23%), and support for understanding concepts (46.00%). For the obstacles indicator, the highest response was neutral at 39.54%. Thus, technology is perceived as capable of supporting mathematics learning, although its optimization still requires the readiness of facilities, networks, and user skills.
The Use of Artificial Intelligence-Based Learning Tools to Enhance Students’ Employment Readiness in the Digital Age Ayu Gede Willdahlia; Desak Made Dwi Utami Putra; Aniek Suryanti Kusuma; Ni Kadek Nita Noviani Pande
Jurnal Krisnadana Vol 5 No 3 (2026): Jurnal Krisnadana May - July 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/ttjd4r39

Abstract

This study examines the utilization of Artificial Intelligence (AI)-based learning tools, such as ChatGPT, Grammarly, and Quillbot, in improving student employability in the digital era. The rapid development of technology has brought significant transformation to the education sector, where graduates are now required to possess a broader range of skills beyond academic knowledge, including critical thinking, communication, collaboration, and digital literacy. This research addresses the existing gap between the use of AI as a technical aid and its potential to systematically develop these essential competencies. A quantitative research approach was employed with a purposive sample of 150 active students from the Indonesian Business and Technology Institute (INSTIKI) who actively use AI tools in their academic activities. Data was collected via a Likert-scale online questionnaire and analyzed using descriptive and inferential statistics, including correlation and simple linear regression. The findings indicate that students frequently use AI tools and perceive them as beneficial to their learning process. Overall, the analysis reveals that the use of these AI tools has a positive correlation with students’ employability. The strategic integration of AI serves as a catalyst for fostering skills highly relevant to the demands of the modern job market, particularly in digital literacy, critical thinking, and collaboration. The study concludes that AI is not merely a technical tool, but a strategic partner in holistically preparing students for future professional challenges.

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