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All Journal Jurnal Sains dan Teknologi Bulletin of Electrical Engineering and Informatics International Journal of Engineering, Science and Information Technology
I Ketut Gede Darma Putra
Universitas Udayana
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EEG-Based Focus Analysis to Evaluate the Effectiveness of Active Learning Approaches Udayana, I Putu Agus Eka Darma; Sudarma, Made; Putra, I Ketut Gede Darma; Sukarsa, I Made; Jo, Minho
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1068

Abstract

Electroencephalography (EEG) has emerged as a non-invasive and objective technique for monitoring brain activity in real time, widely applied to measure cognitive states such as concentration and alertness. Its ability to capture brain responses during learning processes makes EEG a promising tool to evaluate student engagement more accurately than conventional methods. This study investigates the effectiveness of two active learning methods, Project-Based Learning (PjBL) and Problem-Based Learning (PBL), in the context of English tutoring for elementary students using EEG signals as a cognitive indicator. A total of 20 students aged 8–12 years from ThinkerBee Learning Centre Bali participated in the study. EEG data were recorded using the Muse 2 Headband while students completed test-based tasks designed for each learning method. The EEG signals were preprocessed using bandpass filtering, Continuous Wavelet Transform (CWT), and frequency band decomposition. Concentration scores were then calculated using two approaches: a heuristic method based on the Beta/(Theta + Alpha) ratio and a Long Short-Term Memory (LSTM) model. The heuristic method produced average scores of 0.3991 (PjBL) and 0.3822 (PBL), with a 4.42% difference, while the LSTM model showed a more substantial difference, with scores of 0.5454 (PjBL) and 0.4265 (PBL). A Spearman correlation test between EEG-derived scores and students’ academic results yielded a perfect correlation value of 1.0000, indicating a strong relationship between cognitive engagement and learning outcomes. These results demonstrate the potential of EEG as a reliable tool for objectively assessing learning effectiveness in primary education contexts.
Smart Stego: A Web Application for Hiding Secret Data in Images with LSB and CNN Suryawan, I Gede Totok; Sudarma, Made; Putra, I Ketut Gede Darma; Sudana, Anak Agung Kompiang Oka
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1008

Abstract

This study develops a web-based steganography model to insert the identity of artisans in the form of palmprint images into the image of gringsing ikat woven cloth as a medium for ownership authentication. The method used in the insertion process combines a Convolutional Neural Network and the Least Significant Bit. In contrast, extracting or re-introducing palmprint images from stego images is carried out using a CNN-based classification model. This system was tested with two scenarios; in the first scenario, one palmprint image was inserted into 26 different cloth motifs, while in the second scenario, one cloth motif was inserted into 99 different palmprint images. The test results showed that the system produced consistent confidence values for all cloth motifs in the first scenario. In contrast, in the second scenario, the system achieved an average confidence of 93.5% and a recognition accuracy of 87%. The developed application has proven to be efficient with a reduction in stego image size of up to 66% while maintaining the quality of the stego image, as well as a speedy average execution time of 0.15 seconds for insertion and 0.09 seconds for extraction. These findings prove that the developed steganography model can effectively insert and re-recognize identity images (palmprints) in woven cloth images and has the potential to be applied as an image-based craft product ownership verification system.
Sistem Informasi Manajemen Kependudukan Desa Adat di Bali Sudana, Anak Agung Kompiang Oka; Purnawan, Abdi; Putra, I Ketut Gede Darma; Wirdiani, Ni Kadek Ayu
JST (Jurnal Sains dan Teknologi) Vol. 12 No. 2 (2023): July
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jstundiksha.v12i2.52227

Abstract

Proses pendataan kependudukan di Desa Adat masih dilakukan secara manual sehingga rentan terjadi kesalahan dalam pencatatan data. Permasalahan ini mendorong untuk mengembangkan sistem informasi yang dapat membantu pihak Desa Adat sehingga mempermudah pihak Desa Adat dalam melakukan pendataan kependudukan di lingkungannya serta terintegrasi antara satu Desa Adat dengan Desa Adat lain. Tujuan dari penelitian ini adalah untuk menciptakan sistem informasi manajemen kependudukan desa adat terintegrasi berbasis web. Pengumpulan data pada penelitian ini dilakukan dengan studi literatur beserta wawancara langsung dengan beberapa Prajuru Banjar  Adat dan/atau Prajuru Desa Adat di Bali serta Dinas Pemajuan Masyarakat Adat. Hasil dari proses studi literatur beserta wawancara tersebut diterjemahkan kedalam desain sistem, yaitu gambaran umum sistem, diagram konteks, data flow diagram, dan desain basis data. Penelitian ini dilakukan dengan menggunakan Metode SDLC (Software Development Life Cycle) Model Waterfall dan dikembangkan menggunakan Bahasa pemrograman PHP, dengan Kerangka Kerja Laravel, dan Basis Data MySQL. Hasil dari penelitian ini yaitu sebuah sistem informasi yang membantu manajemen kependudukan Desa Adat yang telah diuji dengan menggunakan Metode Black Box dan Post-Study System Usability Questionnaire (PSSUQ) dan mendapatkan nilai yang baik dibandingkan dengan norma penilaian pada Metode PSSUQ. Sehingga sistem dikategorikan mampu membantu proses pengelolaan data penduduk pada Desa Adat.
Recency, frequency, quality: novel feature from sentiment analysis for clustering and ranking in tourism big data analytics Saraswati, Ni Wayan Sumartini; Putra, I Ketut Gede Darma; Sudarma, Made; Sukarsa, I Made; Aristamy, I Gusti Ayu Agung Mas
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.10709

Abstract

Understanding tourist perceptions has been a key benefit of sentiment analysis in tourism data. However, its outcomes can be further utilized to gain insights into the characteristics of tourist attractions and hotels. This study aims to develop a new feature, called recency, frequency, quality (RFQ), derived from sentiment analysis results to cluster and rank tourist attractions and hotels in Bali. RFQ consists of three components: review recency, review frequency, and review quality. These dimensions reflect the recentness of reviews, the popularity based on the number of reviews, and the review quality measured by the ratio of positive to negative sentiment polarity. Using big data analytics through clustering and ranking, the study finds that the quality of tourist attractions and hotels is primarily concentrated in Badung and Gianyar regencies. More tourist attractions are found in the silver cluster than in the gold, indicating the need to enhance quality. In the hotel sector, the diamond cluster dominates among star-rated hotels, suggesting overall high quality. Budget hotels show fairly good quality, with most falling under the gold cluster.
Co-Authors Anak Agung Kompiang Oka Sudana Aristamy, I Gusti Ayu Agung Mas Ayu Wirdiani Bintari, Ni Putu Erika Sari Dharmadi, I Putu Arya I Gede Totok Suryawan I Made Sukarsa I Made Sunia Raharja, I Made Sunia I Putu Agus Eka Darma Udayana, I Putu Agus Eka I Putu Arya Dharmaadi Jo, Minho Khasanah, Siti Rohmatul Kumalasari, Ulfadiyah Nir Made Sudarma Purnawan, Abdi Rusjayanthi, Ni Kadek Dwi Saraswati, Ni Wayan Sumartini Wardy, Dwiki Krisnanda