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All Journal JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknologi J-Innovation Jurnal Teknologi Jurnal Elektro Kontrol (ELKON) Recent in Engineering Science and Technology
Agus Siswoyo
Universitas Sanata Dharma
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences

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Analisis Tingkat Penyebaran Suhu Inkubator Bayi Dengan Sensor DS18B20 Eko Arianto; Agus Siswoyo
J-Innovation Vol. 11 No. 2 (2022): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v11i2.144

Abstract

A baby incubator is a special device used by newborns that is used to keep the baby's temperature warm. The temperature in the baby incubator can be adjusted according to the baby's needs. Babies who need the most incubators are babies born prematurely and babies born with low weight. A good baby incubator is one that can maintain the required temperature stably and evenly throughout the room. In this study, we will focus on observing the temperature distribution in the baby incubator. Tests in this study will use a lab-scale baby incubator. The baby incubator will be set at 32℃ then the DS18B20 temperature sensors will be placed on four sides in the baby incubator room. Then measurements will be made for 30 minutes and timed data is taken every 2 minutes. The baby incubator temperature analyzer prototype was successfully made and tested in comparison with several other temperature sensors, the result is that the DS18B20 is stable and can indeed be a good choice of temperature sensor. The results of testing the level of heat distribution in the baby incubator, there is an uneven temperature at each sensor point with a difference of 0.15 ~ 0.29℃. When compared to the Krisbow Environment meter, the Environment measurement results tend to be lower. The results of this analysis indicate that there is an uneven distribution of heat in the incubator <0.30℃. It is necessary to do a more detailed analysis on each incubator temperature setting, namely at a temperature of 32~37℃ in another study.
Implementasi gerakan omnidirectional pada robot rugby Agus Siswoyo; Eko Arianto
J-Innovation Vol. 11 No. 2 (2022): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v11i2.143

Abstract

Robots in the KRAI competition (Indonesian ABU Robot Contest) are required to be able to maneuver and move well, efficiently and quickly in order to be able to carry out the task of picking up and kicking rugby balls. In order for the robot to move quickly and precisely, a wheel that can move dynamically is needed. The wheel used is the Omniwheel. This wheel has a small wheel located on the outer side of the main wheel, so that the movement of the rugby robot can run smoother when changing positions. With dynamic and efficient maneuvers and displacement of the rugby robot, the robot can move more agile and can stop in the desired position.
Design and Control Development of an Autonomous Visitor Guiding Robot in a Hospital Environment Agus Siswoyo; Pippie Arbiyanti; Rodik Wahyu Indrawan
Jurnal Teknologi Vol. 13 No. 1 (2023): Jurnal Teknologi
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jitekin.v13i1.81

Abstract

Mobile robot technology, coupled with artificial intelligence, has reached a point where robots can now autonomously navigate and store area data, while the integration of smart sensor and controller technology enables them to detect and adapt to dynamic environments by making predictions under diverse conditions. In general, hospital visitors do not have sufficient preparation and knowledge accompanied by sudden situations, this often makes visitors, namely patients and patient companions confused and panicked. The reality is that until now, many visitors are still pacing in the wrong room, asking the officers many times, which eventually leads to misunderstandings by visitors to the hospital system, facilities, and services which are considered complicated and make visitors dissatisfied. Applied technology innovation Design and control of autonomous visitor guide robots in hospital environments (Viguro Robot) offers solutions using interactive robots that can provide location information and deliver visitors to their intended location. Artificial intelligence is employed through the utilization of sensors, digital data, or remote input, allowing the amalgamation of hospital patient data, instant material analysis, and the utilization of insights derived from Viguro Robots' sensors. This robot is designed by utilizing the development of autonomous mobile robot technology, interactive human machine interface, localization and mapping, and obstacle avoidance. The stages in making the robot begin with design planning, initial testing, stage I validation, stage II validation, and implementation testing. This applied innovation of technology is expected to offer solutions in order to improve facilities and quality of service to patients and patient companions in hospitals.
Desain dan kontrol robot pemandu pengunjung otonom di lingkungan rumah sakit (Robot Viguro): Desain dan kontrol robot pemandu pengunjung otonom di lingkungan rumah sakit (Robot Viguro) Agus Siswoyo; Rodik Wajyu Indrawan
J-Innovation Vol. 12 No. 1 (2023): Jurnal J-Innovation
Publisher : Politeknik Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55600/jipa.v12i1.147

Abstract

In recent years, the development of autonomous robots for healthcare applications has gained significant interest. This paper presents the design and development of an autonomous robot tailored for guiding visitors in healthcare facilities, aiming to enhance their experience and provide efficient navigation. Equipped with huskylens cameras, proximity sensors, and other sensors, the robot perceives its environment and detects obstacles. A robust navigation system incorporates mapping and localization algorithms, enabling real-time mapping and accurate positioning. Through a user-friendly interface, visitors input their destination, and the robot plans an optimal path considering distance, obstacles, and congestion. It adapts to dynamic changes like moving objects or crowded areas for safe and efficient navigation. The development process involved iterative design, prototyping, and testing, incorporating feedback from staff and visitors for improved functionality and user experience. Preliminary pilot test results demonstrate the effectiveness of the autonomous guiding robot, providing accurate navigation and enhancing visitor satisfaction. This research contributes to advancing autonomous robotics in healthcare by addressing the need for visitor guidance, improving efficiency, potentially reducing staff workload, and enhancing overall experiences for patients and visitors.  
SISTEM AKUISISI DAN KLASIFIKASI MOTIF BATIK MENGGUNAKAN ESP32-CAM DAN CNN EKSTERNAL TERINTEGRASI IOT agus siswoyo; Subagyo
Jurnal Elektro Kontrol (ELKON) Vol. 6 No. 1 (2026): Jurnal ELKON
Publisher : Teknik Elektro Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/elkon.v6i1.17330

Abstract

Batik memiliki beragam motif dengan karakteristik visual kompleks sehingga identifikasi manual sering sulit dilakukan. Penelitian ini mengembangkan sistem akuisisi dan klasifikasi motif batik menggunakan ESP32-CAM sebagai perangkat pengambil citra, MobileNetV2 sebagai model Convolutional Neural Network (CNN) pada komputer eksternal, serta Blynk sebagai platform Internet of Things (IoT) untuk pemantauan jarak jauh. Sistem dirancang untuk mengenali 10 motif batik, yaitu Parang, Truntum, Ceplok, Sidomukti, Betawi, Garut, Lamongan, Madura, Cirebon, dan Kawung. Dataset terdiri atas 1.200 citra dan ditingkatkan melalui augmentasi berupa rotasi, flip horizontal, penyesuaian kecerahan, dan zoom 20%. Citra yang diperoleh dari ESP32-CAM dikirim ke komputer melalui serial/WiFi, kemudian diproses melalui resize 160×160 piksel, normalisasi, dan klasifikasi menggunakan model CNN berbasis transfer learning. Hasil prediksi berupa nama motif dan tingkat kepercayaan ditampilkan pada antarmuka komputer serta dikirim ke dashboard Blynk. Pengujian menunjukkan akurasi rata-rata 85% pada data uji dengan waktu respons 1–2 detik. Sistem bekerja optimal pada pencahayaan 200–500 lux, jarak 15–20 cm, dan sudut pengambilan kurang dari 30°. Keterbatasan utama sistem adalah ketergantungan pada komputer eksternal. Pengembangan selanjutnya diarahkan pada perluasan dataset dan implementasi model ringan pada perangkat edge. Kata kunci: Batik, deteksi motif, CNN, ESP32-CAM, IoT.
BERSAUDARA Robot (Room And Air Cleaner) As a Preven-tion of the Spread of Viruses in Work Areas in Buildings and Isolation Rooms Agus Siswoyo; Eko Aris Cahyono; Rodik Wahyu Indrawan
Recent in Engineering Science and Technology Vol. 1 No. 1 (2023): RiESTech Vol. 1 No. 1 Years 2023
Publisher : MBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59511/riestech.v1i01.5

Abstract

BERSAUDARA Robot innovation emerged based on health protocols in the new normal era and workers' anxiety about the spread of viruses in buildings. This robot is designed by utilizing the development of robotics technology, Remote Operated Vehicle (ROV), vacuum floor cleaner, and air purifier equipped with UV Sterilizer and HEPA Filter. BERSAUDARA Robot innovation is expected to fulfill the protocol for preventing the spread of the Covid-19 virus, especially work areas in buildings or isolation rooms, by cleaning floors and air regularly so as to minimize human contact and support the continuity of the activities of workers during the "New Normal".
Application of AGV in the Production System at the PT. Adhikara Wiyasa Gani Agus Siswoyo; Rodik Wahyu Indrawan; Abdul Azis Abdillah
Recent in Engineering Science and Technology Vol. 1 No. 2 (2023): RiESTech Vol. 1 No. 2 Years 2023
Publisher : MBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59511/riestech.v1i02.16

Abstract

This study aims to analyze the effectiveness and efficiency of applying AGV in the production system at the PT. Adhikara Wiyasa Gani. AGV is implemented as a means of transporting materials from the warehouse to the production line, as well as returning finished goods to the warehouse. The research method used was data collection through field observations, interviews with workers, and analysis of production data before and after using AGV. The research results show that the use of AGV can increase the effectiveness and efficiency of the production system. The time required for material delivery from the warehouse to the production line and the return of finished goods to the warehouse can be minimized, thereby speeding up production time. In addition, AGV can also reduce production costs by reducing labor costs and minimizing the risk of human error in shipping goods. In conclusion, the application of AGV can have a positive impact on the production system at the PT. Adhikara Wiyasa Gani. However, further research can be conducted to deepen the effectiveness and efficiency of AGV implementation in production systems in general.
Algoritma Anti-Bias Pasca-Prediksi pada Sistem Pengenalan Makanan Khas Yogyakarta Berbasis ESP32-CAM Agus Siswoyo; Johannes Leon
Jurnal Teknologi Vol 26, No 2 (2026): Agustus 2026
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/teknologi.v26i2.9191

Abstract

Automatic recognition of regional food specialties using embedded devices still faces challenges, particularly prediction imbalance (bias) due to the very small dataset size. This study developed a recognition system for eight types of Yogyakarta specialties (gudeg, sate klatak, bakpia, jogja tahu, pecel gudeg, ayam geprek, es dawet, and klepon) based on ESP32‑CAM integrated with a Flask server and a TensorFlow model (MobileNetV2). The training dataset consisted of only 51 images (average 6–7 images per class). The main problem encountered was extreme bias: the initial model predicted the "klepon" class in 85% of the tests. To address this, a post-prediction anti-bias algorithm was proposed that combined multiple randomization techniques, HSV-based color feature analysis, and weighted probability distributions. Tests were conducted on 15 scenarios with varying lighting and shooting angles. The results show that the anti-bias algorithm successfully reduced the dominance of klepon predictions from 85% to 15%, and achieved a more balanced distribution of predictions between classes. The system's average response time was 1.2 seconds with a 94% success rate for ESP32-server communication. The recognition accuracy under optimal conditions reached 78% (72% average). This system demonstrates that a hybrid edge-cloud approach with a post-prediction anti-bias algorithm can be an effective solution for object recognition on very small datasets, especially for IoT-based culinary applications.
Real-Time Food Ingredient Detection and Rule-Based Recipe Recommendation Using CPU-Deployable YOLOv8n agus siswoyo
JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) Vol. 9 No. 2 (2026): August 2026
Publisher : University of Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jeemecs.v9i2.17284

Abstract

This paper presents a real-time food ingredient detection and rule-based recipe recommendation system using YOLOv8n for CPU-only deployment. The system detects five common household ingredients tempeh, egg, spring onion, soy sauce, and noodle—from a live webcam stream and maps the detected ingredient set to predefined recipe rules. A custom dataset of 1,250 images was collected under variations in lighting, distance, and camera angle, annotated in YOLO format, and divided into training, validation, and test subsets using stratified sampling. Experimental results on the held-out test set showed an overall precision of 0.88, recall of 0.84, F1-score of 0.86, mAP@0.5 of 0.89, and mAP@0.5:0.95 of 0.59. On a CPU-only Intel Core i5-1135G7 laptop, the system achieved approximately 28 FPS, indicating its feasibility for real-time kitchen-assistance applications. The rule-based recommendation module achieved 90.0% strict accuracy and 96.7% lenient accuracy across valid, partial, and invalid ingredient combinations. These results suggest that YOLOv8n can be integrated with an interpretable rule-based recommendation engine for lightweight food-related applications. However, the current system remains limited by the small number of ingredient classes, sensitivity to lighting and occlusion, and the static recipe database.
Pengenalan Teknologi Kesehatan Bagi Siswa SMK Pangudi Luhur Muntilan Sebagai Upaya Peningkatan Literasi Kesehatan Antonius Hendro Noviyanto Noviyanto; Agatha Mahardika Anugrayuning Jiwatami; Eko Arianto; Agus Siswoyo
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 7 No. 2 (2026): Edisi Mei - Agustus
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v7i2.9321

Abstract

Perkembangan teknologi kesehatan digital menuntut masyarakat memiliki literasi kesehatan yang memadai agar mampu memanfaatkan perangkat kesehatan secara tepat, aman, dan bertanggung jawab. Namun demikian, siswa SMK masih memiliki keterbatasan dalam memahami fungsi, cara penggunaan, interpretasi hasil pengukuran, serta prinsip kerja alat kesehatan dasar seperti tensimeter digital dan pulse oximeter. Program pengabdian kepada masyarakat ini bertujuan meningkatkan literasi teknologi kesehatan siswa SMK Pangudi Luhur Muntilan melalui pendekatan edukatif dan praktis yang mengintegrasikan bidang pendidikan kesehatan dan teknologi elektromedis. Kegiatan dilaksanakan menggunakan metode blended learning dengan pendekatan experiential learning yang meliputi tahap persiapan, asesmen kebutuhan, penyusunan modul, workshop interaktif, praktik penggunaan alat kesehatan, perancangan alat kesehatan sederhana berbasis Arduino, pendampingan, serta evaluasi hasil pembelajaran. Sebanyak 48 siswa mengikuti kegiatan dalam kelompok-kelompok kecil untuk mendorong kolaborasi, diskusi, dan pembelajaran berbasis proyek. Hasil kegiatan menunjukkan peningkatan pemahaman siswa tentang teknologi kesehatan dasar, keterampilan dalam mengoperasikan alat kesehatan, dan kemampuan merancang prototipe sederhana. Luaran yang dihasilkan berupa modul pelatihan, publikasi ilmiah, publikasi media sosial dan website, serta Hak Kekayaan Intelektual (HKI). Program ini diharapkan menjadi model penguatan literasi kesehatan digital di lingkungan sekolah kejuruan sekaligus mendukung implementasi pengembangan teknologi tepat guna untuk meningkatkan kualitas hidup masyarakat.
Co-Authors Abdul Azis Abdillah Agatha Mahardika Anugrayuning Jiwatami Antonius Hendro Noviyanto Eko Arianto Eko Arianto Eko Aris Cahyono Johannes Leon Pippie Arbiyanti Rodik Wahyu Indrawan Rodik Wajyu Indrawan Subagyo