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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 Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat 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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Troop camouflage detection based on deep action learning Muslikhin Muslikhin; Aris Nasuha; Fatchul Arifin; Suprapto Suprapto; Anggun Winursito
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i3.pp859-871

Abstract

Detecting troop camouflage on the battlefield is crucial to beat or decide in critical situations to survive. This paper proposed a hybrid model based on deep action learning for camouflage recognition and detection. To involve deep action learning in this proposed system, deep learning based on you only look once (YOLOv3) with SquezeeNet and the fourth steps on action learning were engaged. Following the successful formulation of the learning cycle, an instrument examines the environment and performance in action learning with qualitative weightings; specific target detection experiments with view angle, target localization, and the firing point procedure were performed. For each deep action learning cycle, the complete process is divided into planning, acting, observing, and reflecting. If the results do not meet the minimal passing grade after the first cycle, the cycle will be repeated until the system succeeds in the firing point. Furthermore, this study found that deep action learning could enhance intelligence over earlier camouflage detection methods, while maintaining acceptable error rates. As a result, deep action learning could be used in armament systems if the environment is properly identified.
Pengenalan Viseme Dinamis Bahasa Indonesia Menggunakan Convolutional Neural Network Aris Nasuha; Tri Arief Sardjono; Mauridhi Hery Purnomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 3: Agustus 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1057.97 KB)

Abstract

There has been very little researches on automatic lip reading in Indonesian language, especially the ones based on dynamic visemes. To improve the accuracy of a recognition process, for certain problems, choosing suitable classifiers or combining of some methods may be required. This study aims to classify five dynamic visemes of Indonesian language using a CNN (Convolutional Neural Network) and to compare the results with an MLP (Multi Layer Perceptron). Varying some parameters theoretically improving the recognition accuracy was attempted to obtain the best result. The data includes videos on pronunciation of daily words in Indonesian language by 28 subjects recorded in frontal view. The best recognition result gives 96.44% of validation accuracy using the CNN classifier with three convolution layers.
Development of Javanese Speech Emotion Database (Java-SED) Fatchul Arifin; Ardy Seto Priambodo; Aris Nasuha; Anggun Winursito; Teddy Surya Gunawan
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 3: September 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i3.3888

Abstract

Javanese is one of the most widely spoken regional languages in Indonesia, alongside other regional languages. Emotions can be recognized in a variety of ways, including facial expression, behavior, and speech. The recognition of emotions through speech is a straightforward process, but the outcomes are quite significant. Currently, there is no database for identifying emotions in Javanese speech. This paper aims to describe the creation of a Javanese emotional speech database. Actors from the Kamasetra UNY community who are accustomed to performing in dramatic roles participated in the recording. The location where recordings are made is free of interference and noise. The actors of Kamasetra have simulated six types of emotions, including happy, sad, fear, angry, neutral, and surprised. The cast consists of ten people between the ages of 20 and 30, including five men and five women. Both humans (30 Javanese-speaking verifiers ranging in age from 17 to 50) and a machine learning system (30 Javanese-speaking verifiers with ages between 17 and 50) verify the database that has been created. The verification results indicate that the database can be used for Javanese emotion recognition. The developed database is offered as open-source and is freely available to the research community at this link https://beais-uny.id/dataset/
Pembuatan Media Pembelajaran Online dengan OBS Studio dan Youtube di SMKN 1 Pundong Septian Rahman Hakim; Aris Nasuha; Moh Alif Hidayat Sofyan; Purno Tri Aji; Cipto Sabdo Prabowo
Indonesia Berdaya Vol 5, No 1 (2024)
Publisher : UKInstitute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47679/ib.2024695

Abstract

Pembuatan media pembelajaran berbasis teknologi informasi dan komunikasi merupakan salah satu solusi bagi Sekolah Menengan Kejuruan (SMK) Pundong Kabupaten Bantul DI Yogyakarta dalam menyajikan materi pembelajaran dalam menghadapi era revolusi industri 4.0. Namun, saat ini hanya sedikit yang mengetahui tentang penggunaan media pembelajaran online dalam konteks pembelajaran dalam berbagai bidang. Penelitian ini merupakan hasil dari pengabdian kepada masyrakat yang dilakukan dengan menggunakan metode pelatihan/workshop. Berdasarkan temuan, sebanyak dua puluh lima (25) guru di SMKN 1 Punding memiliki tingkat keberhasilan pemahaman materi di atas 60%. Metode yang di gunakan dalam penelitian ini adalah dengan berpatokan nilai pretest dan posttest serta melihat dari hasil implementasi dari video yang telah di upload oleh peserta pelatihan sesuai dengan bidang studi yang di ajarkan.
Implementasi Integrasi Computer Vision dan Kendali PID untuk Robot Line Follower dengan Kendali Kecepatan Dinamis Priambodo, Ardy Seto; Nasuha, Aris; Dhewa, Oktaf Agni
Telekontran : Jurnal Ilmiah Telekomunikasi, Kendali dan Elektronika Terapan Vol. 12 No. 1 (2024): TELEKONTRAN vol 12 no 1 April 2024
Publisher : Program Studi Teknik Elektro, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/telekontran.v12i1.13323

Abstract

This research aims to develop a dynamic speed control system for line follower robots by integrating computer vision technology and PID control. The main challenge in controlling line follower robots is maintaining stability and speed while navigating various types of turns and complex paths. This study proposes the use of computer vision to detect paths more accurately and responsively, and PID control to dynamically adjust the robot's speed based on detected errors. The research methods involve simulating the e-puck robot in a Webots environment, developing algorithms for black line detection and error calculation, and designing the PID control system. The test results show that in Arena 1, the completion time with fixed base speed is 58.08 seconds, while with dynamic base speed it is 50.386 seconds, indicating a 13.3% reduction in completion time. In Arena 2, the completion time with fixed base speed is 71.584 seconds, while with dynamic base speed it is 66.624 seconds, indicating a 6.9% reduction in completion time. Thus, this control system is more effective in keeping the robot on the desired path, reducing deviations and improving path tracking accuracy.
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.
Penguatan Produksi Batik Tulis bagi Pengrajin Lokal melalui Pelatihan Inovasi Teknologi ASP2 Bersama PT. PMCT di Sanggar Batik Astoetik, Bantul, Daerah Istimewa Yogyakarta Hadi Karyono, Tri; Dhewa, Oktaf Gani; Nasuha, Aris; Komarudin, Komarudin; Sutopo, Sutopo; Pustikaningsih, Adeng; Hidayatulloh, Indra
Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat Vol 5 No 2 (2025): JIPPM - Desember 2025
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jippm.959

Abstract

Pengrajin batik tulis menghadapi lamanya tahap sketsa (hingga ±3 hari) dan menurunnya minat generasi muda, yang menekan produktivitas. Kegiatan ini bertujuan memperkenalkan dan menguji Automatic Smart Pen Plotter (ASP2) sebagai solusi percepatan sketsa sekaligus penguatan literasi digital. Pelatihan praktik penggunaan ASP2 dilaksanakan pada 23 Agustus 2025 di Sanggar Batik Astoetik dengan 20 peserta, melalui tahapan hands-on, observasi, dan evaluasi kepuasan. Peserta berhasil mengoperasikan ASP2 untuk membuat pola di kain mori dan melanjutkan ke proses membatik tradisional (pencantingan, pewarnaan, nglorod), dengan percepatan nyata pada tahap sketsa dibanding cara manual. Survei menunjukkan kepuasan 100% pada aspek fasilitator, waktu, dan kemudahan penggunaan; 80% menyatakan peningkatan keterampilan dan pengetahuan yang sangat besar; dan 100% berminat mengikuti pelatihan lanjutan. Penerapan ASP2 pada mitra berdampak pada peningkatan produktivitas, penguatan kompetensi digital, serta terbentuknya persepsi positif bahwa teknologi dapat menjadi mitra dalam pelestarian batik.
Co-Authors Adeng Pustikaningsih Ahmad Taufiq Musaddid Alam, Rahib Lentera Alif Naufal Allaudin Anggun Winursito Ardy Seto Priambodo Cipto Sabdo Prabowo Darmawan, Robby Dessy Irmawati Dhewa, Oktaf Gani Fatchul Arifin Fiosa Putra Gunawan, Teddy Surya Hendrawan Armanto Indra Hidayatulloh Komarudin Komarudin Kurniawan Budi Kusnanto Lukman Zaman Mauridhi Hery Purnomo Moh Alif Hidayat Sofyan Muhammad Hanif Al Hasan Muslikhin Oktaf Agni Dhewa Purno Tri Aji Septian Rahman Hakim Suprapto Suprapto Sutopo Sutopo Teddy Surya Gunawan Tri Arief Sardjono Tri Hadi Karyono Willi Bianyosa Arif Wibiya