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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Eduvest - Journal of Universal Studies J-Icon : Jurnal Komputer dan Informatika
Dewi, Ni Made Rai Masita
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Aerospace Engineering Computer Science & IT Health Professions Neuroscience Social Sciences

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Performance Comparison of KNN and CNN in Classifying Balinese Gangsa Instrument Tones Yusadara, I Gede Putra Mas; Dewi, Ni Made Rai Masita; Budaya, I Gede Bintang Arya
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.14019

Abstract

Balinese traditional music, particularly the Gamelan Gangsa, represents a unique aspect of Indonesia’s cultural heritage. Despite its cultural significance, the study and teaching of this instrument face challenges, particularly in tone standardization and the availability of effective learning tools. This research addresses these challenges by exploring the application of Artificial Intelligence (AI) technologies specifically K-Nearest Neighbors (KNN) and Convolutional Neural Networks (CNN) in the identification and classification of Gamelan Gangsa tones. The study involved the creation of a dataset comprising audio recordings of the instrument, followed by the development and evaluation of KNN and CNN models. The results indicate that KNN, with an accuracy of 90%, outperformed CNN, which achieved an accuracy of 85%. The findings suggest that KNN is particularly effective in distinguishing subtle tonal differences, making it a valuable tool for supporting traditional music education. This research not only contributes to the technical understanding of Gamelan Gangsa’s acoustic characteristics but also underscores the potential of AI in cultural preservation. The development of AI-based tone identification systems can facilitate the teaching and learning of traditional music, ensuring its transmission to future generations. The study serves as a foundation for further exploration into the integration of AI technologies with cultural heritage, demonstrating how modern innovations can enhance the appreciation and understanding of traditional arts.
TATA KELOLA TI PADA SISTEM INFORMASI DOSEN ITB STIKOM BALI MENGGUNAKAN FRAMEWORK COBIT 5 Dewi, Ni Made Rai Masita
JATISI Vol 11 No 2 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i2.7941

Abstract

ITB STIKOM Bali, as an institution of information technology education, must ensure that the implemented faculty information system is not only efficient in data management but also meets security and data integrity standards. The COBIT 5 framework, a global standard for IT governance, is used to evaluate and improve IT governance processes in the Faculty Information System at ITB STIKOM Bali. COBIT 5 provides a structured framework for managing risks, ensuring compliance, and enhancing IT performance. Understanding the importance of IT governance in the implementation of faculty information systems, institutions can ensure that information technology is optimally used to support academic and administrative activities safely, efficiently, and effectively. This research aims to identify potential improvements in the governance of the Faculty Information System. Through this research, it is hoped to provide a clear understanding of the extent to which IT governance at ITB STIKOM Bali aligns with the best practices set by COBIT 5. The results of this research are expected to serve as a basis for institutions to enhance the operational sustainability of the Faculty Information System, reduce security risks, and increase user satisfaction through the implementation of good and efficient IT governance. Therefore, good IT governance is highly necessary in managing the implementation of faculty information systems.
MAPPING TATA KELOLA DOMAIN COBIT 5 PADA PENERAPAN LMS E-LEARNING ITB STIKOM BALI Dewi, Ni Made Rai Masita; Pramana, Dian; Yusadara, I Gede Putra Mas
J-Icon : Jurnal Komputer dan Informatika Vol 12 No 2 (2024): Oktober 2024
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v12i2.15174

Abstract

The implementation of e-Learning at ITB STIKOM Bali represents a significant support for online learning. The Learning Management System (LMS) called e-Learning ITB STIKOM Bali, based on Moodle LMS, is used to conduct lectures online. e-Learning is integrated with SINAK (Academic Information System), SID (Lecturer Information System), and SION (Online Information System) for both students and lecturers, including course registration and enrollment of students and lecturers. This system is used for both fully online lectures (Asynchronous Learning) and blended learning lectures in all study programs. However, proper maintenance and management of this system are necessary. Therefore, evaluation and analysis in IT governance related to the used LMS are required. In order to measure the maturity level of the e-Learning LMS implementation, measurement based on mapping and measuring the level of capability or gaps is needed. This measurement is conducted using the Process Assessment Model (PAM) within the COBIT 5 framework. Measurement activities will be based on several domains within COBIT 5, with process mapping based on business goals and institutional objectives. Based on the process mapping using PAM, domains strongly related to institutional IT goals focusing on customers and internal aspects are identified: MEA01 (Monitor and Evaluate Performance and Conformance), DSS 03 (Manage Security Services), APO13 (Manage Security), EDM 03 (Ensure Risk Optimization), BAI 07 (Manage Change Acceptance and Transitioning).
Effectiveness of AdaBoost and XGBoost Algorithms in Sentiment Analysis of Movie Reviews Lestari, I Gusti Ayu Nandia; Dewi, Ni Made Rai Masita; Meiliana, Komang Gita; Aryanto, I Komang Agus Ady
Journal of Applied Informatics and Computing Vol. 9 No. 2 (2025): April 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i2.9077

Abstract

Currently there are many entertainment platforms that provide various movies, TV shows, games, and other content. These platforms usually offer a variety of features, one of which is reviews. Review data written by viewers plays an important role in influencing public interest in the film. However, the increasing number of reviews makes it difficult to assess the sentiment of the film quickly and accurately. This highlights the need for a system that can analyze reviews based on sentiment, making it easier for viewers to evaluate the film and supporting the entertainment industry in understanding the needs of the audience. Therefore, this study develops a sentiment analysis model to identify whether a review contains positive or negative sentiment using machine learning algorithms. The data used to build the model is obtained from user reviews of a film on the IMDb platform. This dataset is available on Kaggle with 50,000 movie reviews in text format. The characteristics of the data include two columns: review_text and sentiment. The methods used to create the classification model are AdaBoost and XGBoost. The data preprocessing process includes several stages such as text cleaning, tokenization, stopword removal, lemmatization, and vectorization using TF-IDF to convert the review text into numeric form, as well as converting the positive and negative labels into 1 and 0. Based on the results of model training with cross-validation, the accuracy of the XGBoost model is 85% and AdaBoost is 77%. Feature selection showed an improvement in the XGBoost model's accuracy from 85% to 86%, while the AdaBoost model's performance remained stable at 77%. Thus, it can be concluded that the XGBoost model demonstrates better performance than the AdaBoost model in sentiment classification.
Dashboard Application For Monitoring Patient Data In Hospitals Sekarini, I Gusti Agung Ayu; Widhiyanti, Anak Agung Sandatya; Dewi, Ni Made Rai Masita
Eduvest - Journal of Universal Studies Vol. 5 No. 8 (2025): Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v5i8.51010

Abstract

In the increasingly advanced digital era, the healthcare sector faces significant challenges in effectively managing patient visit data. Monitoring patient visits, both inpatient and outpatient, is a crucial aspect of hospital management. This study aims to develop a dashboard application that can monitor inpatient and outpatient visit data in real-time and in an integrated manner at hospitals in Gianyar City. The problems faced include data inaccuracies, delays in decision-making, and lack of data integration from various sources. The research methods used include needs analysis through interviews and surveys, system design with architecture and prototype design, application development using the waterfall method, as well as testing using blackbox testing and application performance evaluation using usability testing. This application is designed to collect data from various sources, integrate it, and present it in an easily understandable visual form. The results of the study show that this dashboard application can improve the efficiency and accuracy of managing patient visit data, as well as support faster and more accurate decision-making. The conclusion of this study is that the developed dashboard application can help hospitals manage patient visit data more effectively, thereby improving the quality of healthcare services.
Co-Authors Aryanto, I Komang Agus Ady Budaya, I Gede Bintang Arya Dian Pramana Lestari, I Gusti Ayu Nandia Meiliana, Komang Gita Sekarini, I Gusti Agung Ayu Widhiyanti, Anak Agung Sandatya Yusadara, I Gede Putra Mas