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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

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.

PENINGKATAN KAPASITAS PRODUKSI DAN BRANDING CAMILAN COKLAT CHIPS PADA BEEMA BROWNIES Wijaya ADH, IGKG Puritan; Yusadara, I Gede Putra Mas; Wirawan, I Wayan Arik; Wikranta Arsa, I Gusti Ngurah; Saputra, I Made Arya Budhi; Gautama, I Made Bhaskara; Sari, Ni Made Wirastika; Rini, Erma Sulistyo; Parwita, I Made Mika; Damayanthi, Ni Putu Desy
Jurnal Berdaya Mandiri Vol. 6 No. 1 (2024): JURNAL BERDAYA MANDIRI (JBM)
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jbm.v6i1.6104

BEEMA Brownies, a snack manufacturer, has started producing snacks in the form of Brownies-flavored Choco Chips and several other flavors made from good quality ingredients without artificial sweeteners and preservatives. Even though in the middle of a pandemic, we are still optimistic that we can capture a sufficient consumer market because the market need for healthy snacks is still very much needed. With the implementation of Phase 1 activities, namely the provision of production equipment, namely ovens, product packaging tools and 2 sets of baking sheet equipment, the current production capacity of Beema Brownies has increased from a maximum of 150/package per day with an average product requirement of around 100-200 packs/sold. day to 300/pack per day using the 2 ovens that you already have. Training on the use of the equipment provided has also been carried out so that BEEMA production employees are able to use the newly provided oven equipment and packaging equipment. The amount of production has been able to meet the average demand every day. BEEMA Chocochips has also increased the HR capabilities of 2 employees who help produce in an effort to increase the amount of Chocochips production. By having a website for UKM BEEMA Chocchips, they already have the means for digital identity and digital promotional content for their products so that they are known to the wider community. Keywords: Brownies, Production, Website

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

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).

Classification of User Expressions on Social Media Using LSTM and GRU Models Yusadara, I Gede Putra Mas; Saryanti, I Gusti Ayu Desi
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 1 (2025): JANUARY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i1.2318

Social media serves as a platform for sharing information. Through social media, users can interact with others and express their feelings and emotions. Therefore, emotion analysis plays a crucial role in understanding users' conditions regarding various issues and social events. This study aims to compare the performance of emotion classification models in analyzing and identifying users' emotions on social media. The research process includes data preprocessing, training, and model performance evaluation. The dataset used is derived from Twitter social media and is available on Kaggle. It consists of two main columns: text and label, with the latter categorized into six groups. The dataset undergoes several preprocessing techniques to ensure it is ready for model training. The model training process implements the architectures of LSTM and GRU to analyze the emotions contained within the text. The evaluation results show that the model achieves an accuracy of 93% for LSTM and 94% for GRU, indicating that the GRU model slightly outperforms the LSTM in classifying emotions in textual data. This research is expected to contribute to emotion analysis systems based on deep learning.

Pengadaan Branding dan Marketing Digital Produk Makanan Industri Rumah Tangga Pawon Noya Healthy Foods Putri, Dian Rahmani; Deniari, Ni Ketut; Yusadara, I Gede Putra Mas; Cahyani, Ni Made Junia; Santika, Kadek Dwi; Wicaksana, Gede Hendri Mahardika
Bhakti Persada Jurnal Aplikasi IPTEKS Vol. 8 No. 1 (2022): Bhakti Persada Jurnal Aplikasi IPTEKS
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/bp.v8i1.9-17

Mitra Usaha Mikro Kecil dan Menengah (UMKM) dalam pengabdian ini adalah industri rumah tangga Pawon Noya Healthy Foods. Fungsi manajemen bisnis yang diimplementasikan ke dalam branding dan metode pemasaran yang baik dapat membantu UMKM dalam mengelola dan menjalankan usahanya. Permasalahan yang dihadapi mitra adalah belum adanya branding dan label produk serta belum memahami tentang teknologi digital marketing. Permasalahan kedua berkaitan dengan Ilmu Bahasa dan Komunikasi, yaitu yang berkaitan dengan komunikasi pemasaran produk (marketing communication). Tim Pengabdian Masyarakat STIKOM Bali telah melaksanakan kegiatan PKM ke lokasi Mitra UMKM PAWON NOYA Healthy Foods yang berlokasi di Batubulan, Gianyar, Bali. Tujuan dari PKM ini adalah pertama, untuk membantu Mitra dalam membuat branding dan label kemasan untuk produknya serta membantu Mitra dalam melakukan pemasaran dengan teknologi digital marketing dan kedua, komunikasi pemasaran produk. Tim Pengabdian Masyarakat STIKOM Bali mendampingi UMKM selama masa pengabdian untuk mencari solusi yang efektif, efisien dan memiliki nilai tambah dalam mengelola usahanya, selain itu juga membantu UMKM menemukan solusi yang efektif dan efisien serta memiliki nilai tambah dalam mengelola usaha.

PENINGKATAN KAPASITAS PRODUKSI DAN BRANDING CAMILAN COKLAT CHIPS PADA BEEMA BROWNIES Wijaya ADH, IGKG Puritan; Yusadara, I Gede Putra Mas; Wirawan, I Wayan Arik; Wikranta Arsa, I Gusti Ngurah; Saputra, I Made Arya Budhi; Gautama, I Made Bhaskara; Sari, Ni Made Wirastika; Rini, Erma Sulistyo; Parwita, I Made Mika; Damayanthi, Ni Putu Desy
Jurnal Berdaya Mandiri Vol. 6 No. 1 (2024): JURNAL BERDAYA MANDIRI (JBM)
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jbm.v6i1.6104

BEEMA Brownies, a snack manufacturer, has started producing snacks in the form of Brownies-flavored Choco Chips and several other flavors made from good quality ingredients without artificial sweeteners and preservatives. Even though in the middle of a pandemic, we are still optimistic that we can capture a sufficient consumer market because the market need for healthy snacks is still very much needed. With the implementation of Phase 1 activities, namely the provision of production equipment, namely ovens, product packaging tools and 2 sets of baking sheet equipment, the current production capacity of Beema Brownies has increased from a maximum of 150/package per day with an average product requirement of around 100-200 packs/sold. day to 300/pack per day using the 2 ovens that you already have. Training on the use of the equipment provided has also been carried out so that BEEMA production employees are able to use the newly provided oven equipment and packaging equipment. The amount of production has been able to meet the average demand every day. BEEMA Chocochips has also increased the HR capabilities of 2 employees who help produce in an effort to increase the amount of Chocochips production. By having a website for UKM BEEMA Chocchips, they already have the means for digital identity and digital promotional content for their products so that they are known to the wider community. Keywords: Brownies, Production, Website

A Comparative Analysis of Character and Word-Based Tokenization for Kawi-Indonesian Neural Machine Translation Budaya, I Gede Bintang Arya; Yusadara, I Gede Putra Mas
Journal of Applied Informatics and Computing Vol. 9 No. 6 (2025): December 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i6.11283

Preserving regional languages is a strategic step in preserving cultural heritage while expanding access to knowledge across generations. One approach that can support this effort is the application of automatic translation technology to digitize and learn local language texts. This study compares two tokenization strategies, word-based and character-based on a Kawi–Indonesian translation model using the FLAN-T5-Small Transformer architecture. The dataset used consists of 4,987 preprocessed sentence pairs, trained for 10 epochs with a batch size of 8. Statistical analysis shows that Kawi texts have an average length of 39.6 characters (5.4 words) per sentence, while Indonesian texts have an average length of 54.9 characters (7.5 words). These findings suggest that Kawi sentences tend to be lexically dense, with low word repetition and high morphological variation, which can increase the learning complexity of the model. Evaluation using BLEU and METEOR metrics shows that the model with word-based tokenization achieved a BLEU score of 0.45 and a METEOR score of 0.05, while the character-based model achieved a BLEU score of 0.24 and a METEOR score of 0.04. Although the dataset size has increased compared to previous studies, these results indicate that the additional data is not sufficient to overcome the limitations of the semantic representation of the Kawi language. Therefore, this study serves as an initial baseline that can be further developed through subword tokenization approaches, dataset expansion, and training strategy optimization to improve the quality of local language translations in the future.

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