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All Journal Techno.Com: Jurnal Teknologi Informasi Journal JCONES TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Teknologi Informasi dan Ilmu Komputer JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Abadimas Adi Buana Share : Journal of Service Learning Jurnal Informatika dan Sistem Informasi (JUISI) Journal of Advanced in Information and Industrial Technology (JAIIT) Infotech: Jurnal Informatika & Teknologi Journal of Computer, Electronic, and Telecommunication (COMPLETE) Journal of Technology and Informatics (JoTI) Jurnal Abdi Masyarakat Indonesia Journal of Applied Business, Taxation and Economics Reseach Jurnal Nasional Teknik Elektro dan Teknologi Informasi Journal of Innovation Research and Knowledge Journal of Business Management and Economic Development Jurnal Pengabdian Masyarakat EKOBIS ABDIMAS : Jurnal Pengabdian Masyarakat Green Inflation: International Journal of Management And Strategic Business Leadership Aksi Kita: Jurnal Pengabdian Kepada Masyarakat TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Heri Pratikno
Universitas Dinamika
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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Menentukan Ukuran Sepatu Secara Realtime Melalui Segmentasi Citra Telapak Kaki Heri Pratikno; Kusumawati, Weny Indah
Journal of Computer, Electronic, and Telecommunication (COMPLETE) Vol. 3 No. 2 (2022): December
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/complete.v3i2.255

Abstract

Abstract: Sepatu selain sebagai fashion juga sebagai pelindung utama kulit permukaan kaki pada aktifitas kehidupan sehari-hari. Pada toko sepatu belum mempunyai sistem dan alat untuk mendeteksi ukuran sepatu orang secara realtime dan otomatis, sehingga calon pembeli sepatu tidak perlu lagi mencoba berulangkali untuk mendapatkan ukuran sepatu yang sesuai dan nyaman dipakai. Pada penelitian ini membuat sebuah sistem dan alat yang mampu mendeteksi ukuran sepatu secara realtime dan otomatis melalui segmentasi citra dari telapak kaki menggunakan webcam. Untuk mendapatkan ukuran sepatu yang pas pada penelitian ini maka dilakukan komparasi tiga metode deteksi tepi, yaitu: Sobel, Prewitt dan Canny. Hasil eksperimen secara empiris, metode Canny mempunyai akurasi tertinggi dalam mendeteksi ukuran panjang telapak kaki sebesar 97% dan lebarnya 98,8%. Metode Sobel mempunyai waktu komputasi tercepat, yaitu: 23,26 detik. Presisi terbaik dalam mendapatkan ukuran telapak kaki pada penelitian ini pada skala 4,48 piksel sebanding dengan 1 mm.
Kontrol Level Kecepatan Kipas Melalui Deteksi Gestur Jari Tangan Menggunakan MediaPipe dan Faster-RCNN Fakhruddin, Muhammad Aldi; Pratikno, Heri; Musayyanah; Kusumawati, Weny Indah
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 6: Desember 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023107345

Abstract

Interaksi antara manusia dan komputer saat ini lebih interaktif, responsif dan intuitif, di masa lalu proses interaksi tersebut diperlukan kontak secara fisik atau menggunakan sensor-sensor elektronik. Pada penelitian ini interaksi antara manusia dan komputer atau peralatan elektronik tidak diperlukan kontak fisik maupun melalui sensor karena dilakukan secara computer vision hanya menggunakan webcam sehingga proses interaksinya lebih natural. Penerapan mikrokontroler sebagai backbone utama teknologi berbasis Internet of Things di era Industry 4.0, bertujuan untuk mempermudah pekerjaan manusia terutama dukungan layanan di dunia industri. Pada era Society 5.0 semua penerapan teknologi yang ada tujuan utamanya tidak hanya mempermudah pekerjaan manusia tetapi bagaimana teknologi tersebut bisa lebih mengerti dan memahami manusianya maka disitulah diterapkan Artificial Itelligence. Dalam penelitian ini diterapkan sistem kontrol interaksi antara pengguna dan komputer untuk pengaturan level kecepatan putaran kipas angin secara otomatis dan realtime berbasis teknologi computer vision for deep learning melalui deteksi bentuk gestur jari tangan kanan dan gestur jari tangan kiri menggunakan webcam. Mikrokontroler yang digunakan pada penelitian ini adalah Arduino Uno, sedangkan penerapan computer vision for deep learning menggunakan framework MediaPipe dan Faster-RCNN. MediaPipe berfungsi untuk mendeteksi bentuk gestur fitur jari kedua tangan dan Faster-RCNN digunakan untuk proses klasifikasi empat bentuk gestur jari tangan untuk mematikan kipas angin atau menghidupkan kipas angin dengan kecepatan putarannya pada level 1, level 2 atau level 3. Hasil pengujian akurasi rata-rata deteksi gestur jari tangan menggunakan MediaPipe pada jarak 10 cm (41,6%), jarak 50 cm (85,35%), jarak 100 cm (71,68%), dan jarak 175 cm (69,33%). Sedangkan hasil pengujian Faster-RCNN mempunyai akurasi klasifikasi rata-rata pada jarak 10 cm (36%), jarak 50 cm (30,75%), jarak 100 cm (18,68 %), dan jarak 175 cm (14.83%).   Abstract Interaction between humans and computers is now more interactive, responsive and intuitive, in the past the interaction process required physical contact or using electronic sensors. In this study, the interaction between humans and computers or electronic equipment does not require physical contact or through sensors because it is done in computer vision using only a webcam so that the interaction process is more natural. The application of microcontrollers as the main backbone of Internet of Things-based technology in the Industry 4.0 era, aims to facilitate human work, especially service support in the industrial world. In the era of Society 5.0, all applications of technology that have the main goal are not only to facilitate human work but how technology can better understand and understand humans, so that's where Artificial Intelligence is applied. In this study, an interaction control system was applied between the user and the computer to adjust the fan speed level automatically and in real time based on computer vision technology for deep learning through the detection of the shape of the right hand finger gesture and the left hand finger gesture using a webcam. The microcontroller used in this study is Arduino Uno, while the application of computer vision for deep learning uses the MediaPipe and Faster-RCNN frameworks. MediaPipe serves to detect the shape of the finger feature gestures of both hands and Faster-RCNN is used to process the classification of four finger gestures to turn off the fan or turn on the fan with its rotational speed at level 1, level 2 or level 3. The results of the average accuracy test detection of finger gestures using the MediaPipe at a distance of 10 cm (37%), a distance of 50 cm (70%), a distance of 100 cm (54.7%), and a distance of 175 cm (63.3%). While the Faster-RCNN test results have an average classification accuracy at a distance of 10 cm (34%), a distance of 50 cm (24%), a distance of 100 cm (8.7%), and a distance of 175 cm (4.7%).
PENINGKATAN KOMPETENSI GURU MELALUI PELATIHAN KECERDASAN ARTIFISIAL GENERATIF DI SDK VINCENTIUS SURABAYA Pratikno, Heri; Kisworo, Angen Yudho
BESIRU : Jurnal Pengabdian Masyarakat Vol. 1 No. 7 (2024): BESIRU : Jurnal Pengabdian Masyarakat, Juli 2024
Publisher : Lembaga Pendidikan dan Penelitian Manggala Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62335/fhfwvf18

Abstract

Dalam menghadapi tantangan pendidikan di abad 21, peningkatan kompetensi guru menjadi sangat penting. Salah satu aspek penting dalam kompetensi ini adalah kemampuan memanfaatkan teknologi, termasuk kecerdasan artifisial generative. Tujuan dari pengabdian masyarakat ini adalah untuk meningkatkan kompetensi guru di SD Vincentius Surabaya dalam menggunakan kecerdasan artifisial generatif. Pelatihan ini dirancang untuk membekali para guru dengan pengetahuan dan keterampilan dasar dalam mengimplementasikan kecerdasan artifisial generatif dalam proses pembelajaran. Melalui pendekatan praktis dan interaktif, diharapkan para guru dapat lebih efektif dalam mengintegrasikan teknologi ini ke dalam kurikulum mereka, sehingga dapat meningkatkan kualitas pendidikan di sekolah. Ke depan, dukungan berkelanjutan dan peningkatan program pelatihan akan menjadi kunci untuk memastikan penerapan teknologi AI yang optimal dalam pendidikan dasar.
Strategy for Penetrating Global Regulatory Barriers: A Case Study of Non-Tariff Measures for Biopharmaceutical plant MSMEs in Lumajang Kukuh Judy Handojo; Sudarmiatin Sudarmiatin; Heri Pratikno
Green Inflation: International Journal of Management and Strategic Business Leadership Vol. 3 No. 2 (2026): May: Green Inflation: International Journal of Management and Strategic Busines
Publisher : Asosiasi Riset Ilmu Manajemen Kewirausahaan dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/greeninflation.v3i2.709

Abstract

A MSMEs in Indonesia has recently contributed to national exports by 15,7%  compared with Thailand that has reached 29 %, so substantial revision are required to make sure that increasing contribution which ultimately will give positive impact toward the economy overall, because almost 90 % of human resource work in MSMEs sector with nature resource and other plentiful resources. The main problem that is commonly found by MSMEs is to optimize the available resources as well as fulfill the required standards that have established and required regulation in order to ensure the resulting product is accepted by the market and to comply with the regulation that has been established by the regulator. Indonesia as the second biggest country in the world has biodiversity certainly offers benefits that hard to imitate by other country in producing biopharmaceutical plants product, therefore it offers competitive potential in the global market, however market penetration by MSMEs biopharmaceutical plants sector commonly discontinued regarding with technical barriers to trade (TBT). This study is based on a case study that aims to analyze main challenges in fulfillment of international certification and to formulate adaptation strategy for MSMEs. By conducting through a descriptive qualitative method with case study approaches, the result of study indicates that high compliance costs,  registration procedural complexity from the source and destination country, as well as the inconsistency of raw material quality became the main barriers. The proposed strategy including group certification model, CPOTB standard harmonization, and the utilization of integrated government assistance schemes will provide real contribution in assisting MSMEs fulfilling global market requirements.
Pelatihan IoT Berbasis ESP32 untuk Mendukung P5 Siswa Kelas 8 SMPN 2 Taman Sidoarjo Heri Pratikno; Pauladie Susanto; Harianto Harianto; Weny Indah Kusumawati
Aksi Kita: Jurnal Pengabdian kepada Masyarakat Vol. 2 No. 3 (2026): MEI-JUNI
Publisher : Indo Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/rmxrma72

Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kompetensi siswa kelas 8 SMPN 2 Taman Sidoarjo dalam bidang teknologi Internet of Things (IoT) melalui pelatihan pembuatan sistem monitoring suhu dan kelembaban berbasis ESP32 yang dilengkapi dengan fitur alarm otomatis. Permasalahan mitra berupa keterbatasan pengetahuan teknis siswa dalam mengimplementasikan perangkat sensor digital DHT22, pemrograman mikrokontroler, serta pengiriman data real-time ke smartphone melalui protokol MQTT. Metode pelaksanaan kegiatan meliputi empat tahap: diskusi kebutuhan mitra, pembuatan perangkat sistem monitoring, pelaksanaan pelatihan, serta serah terima perangkat kepada pihak sekolah. Pelatihan diintegrasikan ke dalam Proyek Penguatan Profil Pelajar Pancasila (P5) dengan tema TEBAS (Teknologi Berbasis Aplikasi untuk Sekolah Adiwiyata). Hasil kegiatan menunjukkan bahwa peserta mampu memahami dan mengoperasikan sistem monitoring suhu dan kelembaban secara mandiri melalui aplikasi IoT MQTT Panel di smartphone, serta sistem alarm buzzer aktif ketika suhu melampaui ambang batas yang ditentukan. Hasil angket menunjukkan tingkat kepuasan peserta yang tinggi, dengan mayoritas responden memberikan penilaian Sangat Setuju pada seluruh indikator evaluasi. Keberhasilan program ini diperkuat oleh tersedianya modul panduan pelatihan dan keberlanjutan kerja sama antara SMPN 2 Taman Sidoarjo dengan Universitas Dinamika.  
Implementasi teknologi drone dan internet of things sebagai sarana untuk memantau polusi udara SO2 dan NO2 di area industri Ilham Ainul Bashir; Weny; Harianto; Heri Pratikno
INFOTECH : Jurnal Informatika & Teknologi Vol 6 No 1 (2025): INFOTECH: Jurnal Informatika & Teknologi
Publisher : LPPMPK - Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/infotech.v6i1.1634

Abstract

Kegiatan industri menghasilkan pencemaran udara yang menjadi masalah untuk kesehatan manusia dan keberlangsungan lingkungan. Gas berbahaya seperti Sulfur Dioksida (SO₂) dan Nitrogen Dioksida (NO₂) memicu masalah pernapasan, menyebabkan iritasi, dan menurunkan kualitas udara. Masalah utama yang dihadapi dalam pengawasan kualitas udara adalah keterbatasan dari sistem tradisional dan memiliki jangkauan yang terbatas. Penelitian ini bertujuan untuk mengimplementasikan sistem pemantauan kualitas udara yang dapat berubah sesuai kebutuhan dan memberikan informasi dengan menggabungkan teknologi drone dan Internet of Things (IoT). Data sensor dikirim langsung melalui jaringan MQTT dan terlihat di aplikasi ponsel. Metode yang diterapkan adalah rekayasa sistem yang berfokus pada eksperimen. Uji sensor memperlihatkan rata-rata kesalahan relatif sebesar 10,7% untuk MQ-135 dan 10,2% untuk MQ-136, dengan tingkat ketepatan yang cukup untuk pemantauan awal. Sistem IoT telah diuji sebanyak 30 kali dan menunjukkan persentase keberhasilan pengiriman data mencapai 100%. Dalam pengujian drone, alat ini dapat membawa beban seberat 400 gram sejauh 50 meter secara horizontal, tetapi tidak dapat terbang lebih jauh hingga 60 meter. Ketinggian tertinggi yang dapat dicapai drone tidak diuji secara vertikal terhadap mdpl, tetapi pengujian berlangsung di wilayah dataran rendah Kabupaten Sidoarjo yang memiliki ketinggian sekitar 3 hingga 5 mdpl, sehingga tinggi ini tidak menjadi kendala utama dalam penelitian ini. Waktu penerbangan drone hanya mencapai 5 menit, sehingga perlu ada perkembangan lebih lanjut untuk memperpanjang daya tahan energi dan memperluas jarak jangkauannya. Penelitian menunjukkan bahwa menggabungkan drone dengan IoT dapat menjadi pilihan lain untuk pemantauan udara di lokasi industri karena memiliki keunggulan dalam hal mobilitas, kecepatan, dan efisiensi biaya.
System design for turbidity control in aquaponic ponds Aditya Aprilianto; Weny Indah Kusumawati; Harianto; Heri Pratikno
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 12 No 2 (2025): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v12i2.1547

Abstract

Aquaculture is fish farming, and hydroponics is the cultivation of plants/vegetables without soil, which means utilizing water and growing media. Aquaponic systems are a combination of fish farming (aquaculture) and soil-less plant/vegetable farming (hydroponics), creating a mutually beneficial relationship. This research aims to design and implement an automated system capable of monitoring and controlling the water turbidity level in aquaponic ponds using the SEN0189 sensor integrated with the Internet of Things (IoT) platform. The developed system utilizes a turbidity sensor, float switch, NodeMCU ESP8266 microcontroller, and connection to the Firebase cloud to enable real-time remote monitoring. The control logic in the system is designed to be able to take automatic water draining and filling actions based on the detected turbidity level parameters. Tests were conducted 98 times, showing a sensor success rate of 92% with 8% non-conforming readings due to program logic mismatches. The tests also revealed the significant influence of environmental lighting, where sensor results at night showed higher values despite clear water conditions. In addition, the system successfully avoided overlapping processes between draining and filling, with an operational success rate of 100% in the overall device test. The results show that the system is effective and reliable for maintaining water quality in aquaponic systems, as well as providing users with the convenience of remotely monitoring and managing water conditions through an IoT connection. This system can be an efficient alternative solution to support the success of fish and plant farming in household and commercial scale aquaponics.
A novel fern-like lines detection using a hybrid of pre-trained convolutional neural network model and Frangi filter Heri Pratikno; Mohd Zamri Ibrahim; Jusak Jusak
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 3: June 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i3.23319

Abstract

Full ferning is the peak of the formation of a salt crystallization line pattern shaped like a fern tree in a woman’s saliva at the time of ovulation. The main problem in this study is how to detect the shape of the salivary ferning line patterns that are transparent, irregular and the surface lighting is uneven. This study aims to detect transparent and irregular lines on the salivary ferning surface using a comparison of 15 pre-trained convolutional neural network models. To detect fern-like lines on transparent and irregular layers, a pre-processing stage using the Frangi filter is required. The pre-trained convolutional neural network model is a promising framework with high precision and accuracy for detecting fern-like lines in salivary ferning. The results of this study using the fixed learning rate model ResNet50 showed the best performance with an error rate of 4.37% and an accuracy of 95.63%. Meanwhile, in implementing the automatic learning rate, ResNet18 achieved the best results with an error rate of 1.99% and an accuracy of 98.01%. The results of visual detection of fern-like lines in salivary ferning using a patch size of 34×34 pixels indicate that the ResNet34 model gave the best appearance
Blocking Delay Effects on Microcontroller Speed and Responsiveness in Industrial IoT Devices: A Systematic Review Pauladie Susanto; Weny Indah Kusumawati; Harianto Harianto; Heri Pratikno; Herru Prastyo
Journal of Technology and Informatics (JoTI) Vol. 8 No. 1 (2026): Vol. 8 N. 1 (2026)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/joti.v8i1.1347

Abstract

This review synthesizes research on the impact of blocking delay on microcontroller speed and responsiveness in IoT devices for industrial automation. It evaluates blocking delay effects on microcontroller performance. The review benchmarks scheduling and edge computing techniques, identifies mitigation strategies, compares case study outcomes, and analyzes architectural and software factors influencing blocking delay. A systematic analysis of experimental, simulation, and co-design studies was conducted. The analysis focused on real-time scheduling, interrupt handling, network-induced latency, and edge computing integration. Key findings reveal that advanced scheduling algorithms and interrupt nesting significantly reduce blocking delays and improve task responsiveness. Edge computing and hardware optimizations also minimize network-induced latency and enhance local processing capabilities. Multiple sources of blocking delay, including resource contention and network overload, are mitigated through adaptive scheduling and hardware-assisted mechanisms. Real-world case studies confirm substantial latency reductions and improved control performance in industrial IoT contexts. These findings underscore the interplay of software and hardware factors in shaping microcontroller responsiveness. The review highlights the necessity for scalable, integrated solutions that address dynamic industrial environments. It informs the design of more responsive and efficient microcontroller-based IoT systems for industrial automation.
Co-Authors Adani, Muhammad Faizin Aditya Aprilianto Andre Hartoko Aji Putra Perdana Bayunugraha, Erdasetya Chalim, Muchammad Daniel Tanugraha, Filbert Dewanto, Arief Rizki Eka Sari Oktarina Fakhruddin, Muhammad Aldi Fitri, Febriana Fredi Wakerkwa Harianto Harianto Harianto Harianto Harianto Harianto Herru Prastyo Ilham Ainul Bashir Jusak Jusak Jusak Jusak Kisworo, Angen Yudho Kukuh Judy Handojo Kusuma, Mochamad Fajar Mohd Zamri Ibrahim Muhammad Rifki Pratama Musayyanah Musayyanah Musayyanah Noorizki, Adisaputra Zidha Pauladie Susanto Pauladie Susanto Philbert, Nicholas Pradinasari, Ryanda Khansa Putro, Abid Eka Sukatno Ramadhan, Rifandy Syahril Setiawan Jaya, Toni Slamet Sopiah, Sopiah Sudarmiatin Sukma, Mochamad Rizal Permata Sulistyo, Bagus Cahyo Susijanto Tri Rasmana Toni Setiawan Jaya Utomo, Niko Priyo Wardhana, Ludi Wishnu Weny Weny Indah Kusumawati Yoppy Mirza Maulana Yosefine Triwidyastuti Yosefine Triwidyastuti Yosefine Triwidyastuti Yosia Pradeska Admaja Zamri Ibrahim, Mohd