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All Journal Dinamika Informatika Journal of Telematics and Informatics Scientific Journal of Informatics JITEK (Jurnal Ilmiah Teknosains) Panrita Abdi - Jurnal Pengabdian pada Masyarakat Sistemasi: Jurnal Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Komputer Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Sisfokom (Sistem Informasi dan Komputer) JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) E-Link: Jurnal Teknik Elektro dan Informatika Jurnal Berdaya Mandiri Journal of Computer Networks, Architecture and High Performance Computing Prosiding Seminar Nasional Sains Teknologi dan Inovasi Indonesia (Senastindo) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Dinamika Informatika (JDI) Jurnal Pelayanan dan Pengabdian Masyarakat Indonesia Applied Science and Technology Research Journal The Indonesian Journal of Computer Science
Banu Santoso
Universitas Amikom Yogyakarta
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Journal : Applied Science and Technology Research Journal

 1 
IoT implementation for Adjustment Automatic pH and TDS/EC Parameters on the System Hydroponics Lettuce Setiawan, Fanes; Santoso, Banu
APPLIED SCIENCE AND TECHNOLOGY REASERCH JOURNAL Vol. 4 No. 1 (2025): Applied Science and Technology Research Journal
Publisher : Lembaga Penelitian dan Pengabdian Mayarakat (LPPM) Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/astro.v4i1.7878

Abstract

Cultivation hydroponics becomes a solution for efficient modern agriculture, especially in the use of land and water. However, maintaining stability of pH and TDS/EC parameters remains become main challenge. Research: This developed system is based on the Internet of Things (IoT) using an ESP32 microcontroller for monitoring and adjusting automatic pH and TDS in cultivating lettuce. Integrated pH and TDS sensors with an actuator automatically in the form of a pump, micro and DC motors, which are controlled in real-time via the Flutter app and Firebase cloud storage. Test results show that the system succeeds in maintaining the pH in the range 6.0–7.0 for 96.44% of the time operations and TDS in the range 560–840 ppm for 96.79% of the time testing. The Paired Samples t-Test produced a p-value of 0.289 for pH and 0.595 for TDS. This value is more than 0.05, so there is no significant relationship in statistical relationship between the condition before and after automation. That is, the system automatically has no significant influence on parameter values, but is capable of guarding its stability consistently. Thus, the system is effective in managing hydroponic water quality in an automatic way.
Technology Trends, Innovations, and Future Research Directions in 3D Printing (Additive Manufacturing): A Systematic Literature Review Santoso, Banu; Dhananjaya Yama Hudha Kumarajati; Herianto; Alva Edy Tontowi; Muhammad Kusumawan Herliansyah
APPLIED SCIENCE AND TECHNOLOGY REASERCH JOURNAL Vol. 4 No. 2 (2025): Applied Science and Technology Research Journal
Publisher : Lembaga Penelitian dan Pengabdian Mayarakat (LPPM) Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/astro.v4i2.8232

Abstract

3D printing or Additive Manufacturing (AM) technology has experienced rapid growth in the past five years, driven by the integration of new technologies such as artificial intelligence (AI), bio- and nano-composite materials, and blockchain-based security systems. This study aims to analyze technology trends, key innovations, and predict future research directions in AM using a Systematic Literature Review (SLR) approach to 80 Scopus/WoS indexed articles. The results show that AI plays a central role in improving production efficiency and accuracy, while material innovations expand AM applications to the medical and aerospace sectors. In addition, the application of 4D printing and blockchain is beginning to form a new paradigm in intelligent and decentralized manufacturing. The 2025–2030 research roadmap compiled from these findings shows a strategic focus on adaptive AI, multifunctional bioinks, modular manufacturing systems, and full integration between AM, blockchain, and smart materials. This study not only identifies research trends and gaps but also offers strategic contributions to the development of future AM technologies in a more adaptive, sustainable, and secure manner.
A Comprehensive Review of AI, Machine Learning, Deep Learning, and GANs Integration in Additive Manufacturing: Trends, Applications, and Challenges Santoso, Banu; Herianto; Wangi Pandan Sari; Alva Edy Tontowi
APPLIED SCIENCE AND TECHNOLOGY REASERCH JOURNAL Vol. 4 No. 2 (2025): Applied Science and Technology Research Journal
Publisher : Lembaga Penelitian dan Pengabdian Mayarakat (LPPM) Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/astro.v4i2.8233

Abstract

The integration of Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Generative Adversarial Networks (GANs) into Additive Manufacturing (AM) has opened new horizons for intelligent, efficient, and adaptive production processes. This paper provides a comprehensive review of current trends, diverse applications, and emerging challenges in the convergence of these technologies within AM systems. We explore how AI-driven techniques contribute to real-time monitoring, defect detection, process optimization, and design generation, enhancing the overall quality, precision, and scalability of 3D printing. ML and DL approaches enable predictive modeling and adaptive control, while GANs offer promising capabilities in generative design and synthetic data augmentation. The review highlights key research contributions, technological advancements, and industrial implementations, mapping the landscape of intelligent AM. Moreover, it discusses the limitations of data availability, model interpretability, computational requirements, and integration complexities. Finally, the study identifies future directions for research, including hybrid AI models, physics-informed learning, and sustainable AM development. By synthesizing multidisciplinary insights, this paper aims to guide researchers and practitioners toward more intelligent, automated, and sustainable additive manufacturing frameworks through the strategic adoption of AI and its subfields. Keywords: Additive Manufacturing, Machine Learning, Artificial Intelligence, 3D Printing, Deep Learning
A Comparative Study Of HC-SR04 and HY-SRF05 Ultrasonic Sensors For Automated Height Measurement Based On IoT Kusuma, Mohan Henry; Banu Santoso
APPLIED SCIENCE AND TECHNOLOGY REASERCH JOURNAL Vol. 4 No. 2 (2025): Applied Science and Technology Research Journal
Publisher : Lembaga Penelitian dan Pengabdian Mayarakat (LPPM) Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/astro.v4i2.8247

Abstract

The inefficiency and potential for operator error in manual height measurements limit data reliability in health and fitness monitoring. To address this, we developed an automated IoT-based system to compare the performance of HC-SR04 and HY-SRF05 ultrasonic sensors. The system architecture is built on a NodeMCU ESP8266 microcontroller, which sends measurement data to a cloud-based Firebase platform for real-time storage and historical analysis, all visualized on a dynamic ReactJS dashboard. The evaluation involved 30 human subjects with heights ranging from 100 to 200 cm. The analysis revealed a mean absolute error of 0.20 cm (0.131%) for HY-SRF05 and 0.233 cm (0.16%) for HC-SR04. Crucially, statistical testing found no significant difference in accuracy between the two sensors (T-test, p > 0.05). The study concludes that both low-cost sensors are highly capable and statistically equivalent for this application. The complete IoT system demonstrates a robust solution for deploying affordable, scalable, and accurate automated height measurement tools, offering a significant improvement over traditional methods.
Co-Authors 'Alaika 'izza alfa azkiya' Ach Izalul Haq Achmad, Lukman Adhi Wibowo Afin Nur Ikhsan Agung Pambudi Alaydrus, Syarif Ahmad Hasny Al Mutsanna Alva Edy Tontowi Angga Arindra Shonta Arief, Muhammad Rudyanto Azman, Mohamed Nor Azhari Baeturohman, Rama Bayu Faris Arkan Bayu Setiaji Dhananjaya Yama Hudha Kumarajati Dony Ariyus Eko Pramono Elik Hari Muktafin Erni Seniwati Feriman Haryoko Haryoko Hastari Utama Herianto Ichsan Wasiso Irma Rofni Wulandari Jeki Kuswanto Jeki Kuswanto K Rasyid, Rum Mohamad Andri Kusrini Kusrini Kusuma, Mohan Henry Lukman Lukman Marti Widya Sari, Marti Melinne Maldini Rosady Moch. Akbar Maulana Muhammad Abdul Ghofur Muhammad Koprawi Muhammad Kusumawan Herliansyah Muhammad Saifulloh Mulyatun, Sri Nila Feby Puspitasari NINIK TRI HARTANTI Nugroho, Rangga Wahyu Nur Rahman, Nur Nuraini Nuraini Pradipta Mahardika Sulaksono Prasetya, Dian R. Hafid Hardyanto Rasyid, Rum Mohamad Andri K Rofinus Benson Date Bay Rosyidah Jayanti Vijaya Ryan Putranda Kristianto Setiawan, Fanes Tegris, Efrat Toriq, Farhan Tri Hartanti, Ninik Wahyudi, Vivin Wangi Pandan Sari Wijayanto, Febri Windyarto Aziz Assidiqie Zaim Irfansyah Arbi