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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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Web Based Marketing Prospect Data Management Information System at Politeknik Ganesha Guru Luh Putu Cintya Prabandari; Desak Nyoman Dewanggi Triananda Budidana
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: 10.58982/522f7105

Abstract

Higher education in the modern era faces challenges along with the rapid development of technology. Educational institutions such as Politeknikik Ganesha Guru need to manage prospect data efficiently to remain relevant and competitive. Unstructured prospect data management is a major obstacle, with data scattered across multiple formats such as physical documents and spreadsheets, leading to duplication, inconsistency, as well as inaccurate data analysis. In addition, tracking the history of lead interactions, such as interest and required follow-ups, was difficult without a structured system, affecting personalization and follow-up effectiveness. Manual management also makes it difficult to access and update data in real-time, hampering the marketing team especially when off-campus. On the other hand, limitations in data analysis slow down the evaluation of marketing performance. The utilization of a web-based information system is expected to be an effective solution, as it can integrate data centrally, improve accessibility, and allow for more accurate analysis. With this solution, Politeknik Ganesha Guru can be more competitive in attracting potential students and improving educational services.
Machine Learning-Based Sentiment Analysis of User-Generated Content: Insights from Google Maps Reviews Ayu Gde Chrisna Udayanie; I Wayan Adi Sparta; Putu Eka Parianthana; Ni Putu Dea Sillviari
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/cp9nwn24

Abstract

The rapid growth of user-generated content on digital platforms has provided valuable opportunities for understanding customer perceptions through sentiment analysis. Google Maps, as one of the most widely used location-based services, allows visitors to share their experiences and opinions regarding public facilities and commercial destinations. This study aims to analyze visitor sentiment toward Living World Bali using machine learning techniques. A total of 4,060 Google Maps reviews were collected and processed through several text preprocessing stages, including cleaning, case folding, normalization, tokenization, stopword removal, and stemming. The Term Frequency–Inverse Document Frequency (TF-IDF) method was employed for feature extraction, while the Random Forest algorithm was utilized for sentiment classification. Experimental results indicate that the proposed model achieved an accuracy of 91.75%, precision of 92.39%, recall of 98.84%, and an F1-score of 95.55%. The sentiment distribution analysis revealed that positive sentiment dominated the dataset, accounting for 84.70% of all reviews, suggesting a high level of customer satisfaction with Living World Bali. Furthermore, the findings demonstrate that the integration of TF-IDF and Random Forest provides an effective approach for classifying textual reviews in the tourism and retail domains. The proposed framework offers valuable insights for shopping center management in evaluating customer experiences and supporting data-driven decision-making processes to improve service quality and visitor satisfaction.
Development of 2D Animation Learning Mediafor Animal Life Cycle Material Rizkita Ayu Mutiarani; I Ketut Wiguna; I Putu Susila Handika
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/e2vc5q81

Abstract

Learning media plays a strategic role in supporting the success of the teaching and learning process. In education, animation is widely used as a modern instructional medium, particularly to represent learning materials that are difficult to explain verbally. This output was developed as an alternative instructional medium for science learning, especially to explain process-oriented concepts that may be difficult for students to understand when delivered only through verbal explanation or static images. The product was created in the form of a 2D animated video in MP4 format, integrating illustrations, frame-by-frame animation, text, voice-over, sound effects, and background music. The production process employed Adobe Photoshop 2021 for visual asset creation and animation, and Adobe Premiere Pro 2020 for post-production. The material presented in the media covers animal life cycles without metamorphosis, represented by chickens and fish, as well as animal life cycles with metamorphosis, represented by frogs, butterflies, and cockroaches. The media consists of 20 scenes arranged narratively through two characters, Kirana and Leoni, who serve as learning guides. The evaluation results showed that the media received highly positive responses from 33 fifth-grade students, with an average score of 88.2%. The measurement of students’ conceptual understanding through pre-test and post-test results produced an average N-Gain score of 0.89, which falls into the high category. Therefore, this 2D animation learning media output is considered feasible to be used as a supporting instructional medium for teachers in delivering animal life cycle material in elementary schools.
Digital Game-Based Learning Effectiveness in Formal Education: A Review I Kadek Budi Sandika; I Nyoman Yoga Trisemarawima; Anggie Birda Ardelia Ghani
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/f2zsaa84

Abstract

The 21st-century technological landscape has significantly transformed conventional education through the adoption of Digital Game-Based Learning (DGBL) and gamification. This study aims to conduct a systematic literature review using the PRISMA protocol to map publication trends, pedagogical effectiveness, ideal game mechanics, and research disparities across one hundred peer-reviewed journal articles published between 2014 and 2026. The findings reveal an exponential growth in publication volume, heavily dominated by contributions from Asia, Europe, and North America. Integrating core game elements such as points, leaderboards, badges, challenges, and narrative framing empirically enhances intrinsic motivation, long-term memory retention, and cognitive learning outcomes. Furthermore, this review identifies a noticeable research divide: computer science journals prioritize technical architectures and adaptive algorithms, whereas educational journals focus on psychopedagogical validation. Practical implications highlight the urgent need for interdisciplinary collaboration, teacher digital literacy programs, and equitable ICT infrastructure to support inclusive digital curricula.
Optimization of Data Mining Models in Identifying Consumer Shopping Patterns in the Retail Sector Using the FP-Growth Method I Made Suryana Dwipa; I Made Nada; Anak Agung Gde Sutrisna WP; I Putu Gede Jody Priandika; Yohana Rista Dama
Jurnal Krisnadana Vol 5 No 1 (2025): Jurnal Krisnadana- in Progress September-October 2025
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/vj1pe417

Abstract

Intense competition in the trading industry makes business actors to carry out more effective sales strategies to face market competition. One strategy that can be used to face market competition is to utilize data mining information technology with the association rules method. Data mining is the process of collecting, using historical data, and modeling large data sets to obtain new patterns or knowledge that can be utilized later. UD.  Kori conducts dozens more sales transactions every day. Sales transactions that occur every day produce increasing data in the database and the availability of goods often does not meet consumer needs, making consumers switch to other stores. This study aims to apply the Fp-Growth Algorithm to determine consumer buying patterns based on sales transaction data. Sales transaction data used as many as 34,085 transactions. Through the mining process with the Fp-Growth algorithm, it will be obtained what products are often purchased simultaneously by consumers and the tool used in this study is Google Colaboratory using the python programming language. The results of the study found that products that are often purchased simultaneously are Mie Sedap Kuah Rasa Soto and Indomie Goreng have support of 0.29% and confidence of 97% with the highest lift ratio reaching 159.73.

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