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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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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.
Automatic Catfish Sorter and Counter Based on Weight Classification Alif Naufal Allaudin; Aris Nasuha
Journal of Robotics, Automation, and Electronics Engineering Vol. 1 No. 1 (2023): March 2023
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jraee.v1i1.64

Abstract

Catfish is one of the main raw materials in the fisheries sector which also supports the Indonesian economy. However, manual sorting of catfish makes the weight of catfish not uniform when marketed. Therefore, tools and machines are needed that automatically sort catfish in large quantities, making it more effective and easier for catfish breeders to use. In this study the process of making the system was realized in 3 stages, namely needs analysis, implementation, and testing of tools. The purpose of this system is to be able to classify the weight of catfish in the large category with fish weighing > 140 grams, medium with fish weighing 80-140 grams and small with fish weighing 20-80 grams. From the system test results, the average accuracy is 99.56. % and a precision of 98.75% for load cell sensor readings, while for E18 infrared sensor readings the results are always known, but data is not always sent and displayed on the LCD screen. Classification of fish categories carried out by the system has worked well, where the system is able to sort and count correctly 14 times out of 15 tests with an accuracy of 93%. The average computing time required for this tool is 3.67 seconds for 15 tests.
Smart Aquaculture in Internet of Things-based Catfish Farming Kurniawan Budi Kusnanto; Aris Nasuha
Journal of Robotics, Automation, and Electronics Engineering Vol. 1 No. 1 (2023): March 2023
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jraee.v1i1.65

Abstract

The primary objective of developing the project titled "Smart Aquaculture in Internet of Things-based Catfish Farming" is to create a specialized tool for catfish farming that facilitates automated monitoring and control of water quality, eliminating the need for manual intervention at the aquaculture pond. The collected data is made accessible through a web monitoring system. The tool aims to mitigate catfish mortality risks, enhance yield, and streamline the cultivation process. The development process of this tool encompasses several stages, which are as follows: (1) Requirements Analysis, involving the identification of necessary tools and materials for the project; (2) Implementation, encompassing the design and fabrication of the tool, outlining the circuit scheme, and detailing the step-by-step manufacturing process; (3) Testing, describing the procedures and results of evaluating the tool's performance. The monitoring system employs PH- 4502C sensors, DS18B20 temperature sensor, and HC-SR04 level sensor, all controlled by ESP32 DevKit. Comparative analysis against standard measuring instruments demonstrates an average error percentage of 1.64% for pH, 0.88% for temperature, and 0.70% for water level measurements. Additionally, the data transmission test reveals a delay of 19.16 seconds, while the actuator response test, based on sensor readings, successfully operates within the system's intended parameters.
Monitoring Smart Applications for Monitoring and Controlling of IoT-Based Strawberry Hydroponic Plants Willi Bianyosa Arif Wibiya; Aris Nasuha
Journal of Robotics, Automation, and Electronics Engineering Vol. 1 No. 2 (2023): September 2023
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jraee.v1i2.166

Abstract

Hydroponic farming has become an attractive option in strawberry cultivation as it provides better control over the growing environment of the plants. However, proper management and continuous monitoring are challenges often faced by farmers in hydroponic farming practices. Therefore, in this study, we designed an IoT-based application that aims to monitor and control strawberry hydroponic farming through smartphone devices. The method used in this research involves developing an application that connects with various sensors installed in the hydroponic farm environment. The data obtained from the sensors is transmitted in realtime through the IoT network. In addition to the monitoring function, the application is also equipped with a control system that can be customized according to the needs of farmers. The result of this research is an application that can work from a short distance (local) or a long distance (cloud). The application is equipped with a hazard alarm notification system. The feature allows farmers to take action to maintain the health and quality of strawberry plants. The use of this application is expected to help make it easier for farmers to monitor and control hydroponic farming to be more efficient and optimize crop yields.
Prototyping of an Automation System for Hydroponic Strawberry Nutrient Dosing Fiosa Putra; Aris Nasuha
Journal of Robotics, Automation, and Electronics Engineering Vol. 1 No. 2 (2023): September 2023
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jraee.v1i2.168

Abstract

Strawberries are a fruit that is a superior commodity in growing the economy in Indonesia. However, there was a decline in strawberry production from 2017 to 2021. This was due to constraints in the conventional cultivation process and environmental controls that were not yet optimal. This research focuses on designing an automated system for cultivating strawberries in containers using several sensors. The sensors used are the EC sensor to measure hydroponic nutrient levels, the pH sensor to measure water acidity, and the DHT22 sensor to measure temperature and humidity. Sensor data is sent to the server using IoT technology. Data is also visualized through an Android application that can be monitored from anywhere and at any time. The design of the automation system, named Amanda Mini, delivers the right amount of nutrients so that the health and nutrition of strawberry plants are sufficient. Water flow is carried out automatically using water supply pumps, sample pumps, stirrer pumps, and plant pumps. In this way, the Amanda Mini automation system facilitates hydroponic strawberry cultivation activities, which can increase strawberry production.
Prototype Design of Toxic Gas (CO) Monitoring Equipment in Motorcycle Workshop Al Hasan, Muhammad Hanif; Nasuha, Aris
Journal of Robotics, Automation, and Electronics Engineering Vol. 2 No. 2 (2024): September 2024
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jraee.v2i2.611

Abstract

Workshop is one of the places that contributes a significant amount of carbon monoxide gas, originating from motor vehicle exhaust. A workshop is also a place at high risk of fire. Due to the lack of awareness among visi- tors and workshop workers about the dangers of carbon monoxide gas and the potential for fires in motorcycle workshops, a tool is needed to monitor carbon monoxide levels and detect fire in the workshop. The aim of this final project is to design and develop a device, software, and demonstrate the per- formance of a system for monitoring carbon monoxide levels and detecting fire in a motorcycle workshop. This research uses the Research and Develop- ment (R&D) method. The results of the monitoring system created showed good outcomes. The sensor used was able to read carbon monoxide levels with an error rate of 5.56%, while the Flame sensor was able to detect fire at a maximum distance of up to 70 cm. The monitoring system functioned well, with carbon monoxide levels visualized using ThingSpeak. The DC fan also worked effectively, when carbon monoxide levels in the room reached 25 ppm or higher, the DC fan would turn on and help with air circulation.
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