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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) ELINVO (Electronics, Informatics, and Vocational Education) International Journal of Community Service Learning TELEKONTRAN: Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan Indonesia Berdaya Insyst : Journal of Intelligent System and Computation Jurnal Nasional Teknik Elektro dan Teknologi Informasi Journal of Robotics, Automation, and Electronics Engineering
Aris Nasuha
Universitas Negeri Yogyakarta
Arts Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Advanced Multimodal Emotion Recognition for Javanese Language Using Deep Learning Arifin, Fatchul; Nasuha, Aris; Priambodo, Ardy Seto; Winursito, Anggun; Gunawan, Teddy Surya
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 12, No 3: September 2024
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v12i3.5662

Abstract

This research develops a robust emotion recognition system for the Javanese language using multimodal audio and video datasets, addressing the limited advancements in emotion recognition specific to this language. Three models were explored to enhance emotional feature extraction: the SpectrogramImage Model (Model 1), which converts audio inputs into spectrogram images and integrates them with facial images for emotion labeling; the Convolutional-MFCC Model (Model 2), which leverages convolutional techniques for image processing and Mel-frequency cepstral coefficients for audio; and the Multimodal Feature-Extraction Model (Model 3), which independently processes video and audio features before integrating them for emotion recognition. Comparative analysis shows that the Multimodal Feature-Extraction Model achieves the highest accuracy of 93%, surpassing the Convolutional-MFCC Model at 85% and the Spectrogram-Image Model at 71%. These findings demonstrate that effective multimodal integration, mainly through separate feature extraction, significantly enhances emotion recognition accuracy. This research improves communication systems and offers deeper insights into Javanese emotional expressions, with potential applications in human-computer interaction, healthcare, and cultural studies. Additionally, it contributes to the advancement of sophisticated emotion recognition technologies.
Teacher Competence in the Use of ChatGPT for Developing Learning Media in Vocational High Schools Tri Aji, Purno; Aris Nasuha; Dessy Irmawati; Moh Alif Hidayat Sofyan; Ahmad Taufiq Musaddid
International Journal of Community Service Learning Vol. 8 No. 4 (2024): November
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/ijcsl.v8i4.85397

Abstract

ChatGPT technology opens up great education opportunities, especially in supporting the development of educator competencies needed in the 21st century. However, teacher competency in utilizing Artificial Intelligence (AI) technology is still low. As a result, existing learning media are not optimal in presenting engaging and interactive digital teaching materials according to the needs of students in the era of education 4.0. This community service aims to improve the competence of vocational high school teachers in using ChatGPT and AI applications for the development of learning media. This study involved 60 teachers from various fields. The methods used were lectures, discussions, and direct practice with online assistance. Teachers were trained to create interactive teaching materials using ChatGPT and other AI applications. The data analysis technique used qualitative descriptive analysis. The post-test results showed a significant increase in teacher competency in using AI applications, with an average score above 4 out of 5 in key aspects such as material usefulness and skill development. The activity results showed increased teachers' ability to utilize AI technology to create digital-based learning media, such as learning videos and interactive teaching materials. This activity significantly improves the quality of the learning process in vocational high schools. This training is expected to optimize teachers' digital skills to face challenges in the era of education 4.0.
Sistem Manajemen Kartu Nama dengan OCR dan Ekstraksi Informasi Otomatis Darmawan, Robby; Nasuha, Aris; Zaman, Lukman; Armanto, Hendrawan
Intelligent System and Computation Vol 3 No 2 (2021): INSYST: Journal of Intelligent System and Computation
Publisher : Institut Sains dan Teknologi Terpadu Surabaya (d/h Sekolah Tinggi Teknik Surabaya)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52985/insyst.v3i2.194

Abstract

Sebagai pelaku bisnis, kartu nama adalah salah satu hal yang penting untuk bertukar informasi. Namun kartu nama biasanya mudah hilang atau rusak, sehingga beberapa orang biasanya menyimpan informasi dari kartu nama itu pada telepon genggam atau komputer mereka. Penelitian ini akan membuat sistem manajemen kartu nama baik individu dan juga perusahaan dengan ekstraksi informasi kartu nama otomatis untuk mempermudah pengguna perorangan ataupun perusahaan dalam melakukan penyimpanan kartu nama para kolega. Untuk mewujudkan aplikasi yang dilengkapi dengan fitur tersebut dilakukan proses pengenalan karakter pada gambar kartu nama menggunakan Tesseract OCR dan information extraction memanfaatkan klasifikasi entity dengan membangun classifier menggunakan Naive Bayes dan mengkombinasikannya dengan rule based. Hasil uji coba yang telah dilakukan mendapatkan performa 85.1% untuk pengenalan karakter dan 86% untuk pengklasifikasian entity. Dilakukan juga uji coba fungsionalitas terhadap setiap fitur pada sistem ini dengan menggunakan metode blackbox testing yang memastikan setiap aksi yang dilakukan pengguna akan menghasilkan output sesuai target yang diharapkan. Selain itu, dari hasil kuisioner yang berisikan tentang usability dari sistem ini, sebagian besar responden merasa terbantu dalam memanajemen kartu nama dengan menggunakan sistem aplikasi ini.
Sistem Pengendali pH Air dan Pemantauan Lingkungan Tanaman Hidroponik menggunakan Fuzzy Logic berbasis IoT Alam, Rahib Lentera; Nasuha, Aris
Elinvo (Electronics, Informatics, and Vocational Education) Vol. 5 No. 1 (2020): Mei 2020
Publisher : Department of Electronic and Informatic Engineering Education, Faculty of Engineering, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (460.266 KB) | DOI: 10.21831/elinvo.v5i1.34587

Abstract

Hidroponik merupakan solusi bercocok tanam untuk lahan pertanian yang semakin menyempit. Namun, pengendalian pH serta monitoring lingkungan yang masih manual membuat hasil tanam menjadi kurang optimal. Proyek akhir ini bertujuan untuk menciptakan perangkat keras dan perangkat lunak untuk mengontrol pH air dan memonitor lingkungan tanaman hidroponik berbasis Internet of things (IoT). Sistem tersebut menggunakan sistem kontrol logika fuzzy untuk mengendalikan pH media tanam hidroponik dan terdapat pengembangan cloud server guna mempermudah petani dalam mengontrol media tanam serta lingkungan tanaman hidroponik. Pembuatan alat ini mengacu pada metode kuantitatif yang terdiri dari tahap analisis, desain/perancangan, perakitan serta pengujian. Hasil dari pengujian yang telah dilakukan adalah ketelitian sensor pH meter sebesar 98,38%, ketelitian sensor DHT22 untuk mengukur suhu sebesar 97,91% dan kelembaban sebesar 95,89%, ketelitian sensor DS18B20 sebesar 96,16%, ketelitian sensor HCSR-04 sebesar 97,65%, Rata-rata waktu penstabilan pH 64s dengan error 2.05%. Semua fitur dalam aplikasi Blynk bekerja dengan baik, waktu ping server rata-rata 18ms dan waktu respons alat rata-rata 83s. Penggunaan sistem ini diharapkan bermanfaat bagi masyarakat awam untuk berkebun tanpa mencemaskan kebutuhan lahan luas dan kerumitan perawatan. Hal tersebut berdampak pada kemandirian pangan pada level rumah tangga dapat diwujudkan melalui penyediaan tanaman panggan untuk konsumsi keluarga.
Co-Authors Ahmad Taufiq Musaddid Al Hasan, Muhammad Hanif Alam, Rahib Lentera Alif Naufal Allaudin Anggun Winursito Ardy Seto Priambodo Cipto Sabdo Prabowo Darmawan, Robby Dessy Irmawati Fatchul Arifin Fiosa Putra Gunawan, Teddy Surya Hendrawan Armanto Kurniawan Budi Kusnanto Lukman Zaman Mauridhi Hery Purnomo Moh Alif Hidayat Sofyan Muslikhin Oktaf Agni Dhewa Purno Tri Aji Septian Rahman Hakim Suprapto Suprapto Teddy Surya Gunawan Tri Arief Sardjono Willi Bianyosa Arif Wibiya Winursito, Anggun