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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
Department Of Computer Engineering, Faculty Of Computer Science, Universitas Amikom Yogyakarta, Indonesia
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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.
IoT-Based Smart Farming System Design for Greenhouse Monitoring in Urban Areas Marti Widya Sari; Erika Amalia; Prahenusa Wahyu Ciptadi; R. Hafid Hardyanto; Banu Santoso
APPLIED SCIENCE AND TECHNOLOGY REASERCH JOURNAL Vol. 5 No. 1 (2026): 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.v4i2.9323

Abstract

The rapid development of urban areas has led to a significant reduction in agricultural land, creating the need for innovative solutions to meet food demands, especially for fresh vegetables. One promising alternative is urban farming supported by the Internet of Things (IoT). This research aims to design and develop an IoT-based smart farming system for monitoring vegetable crops in urban areas with limited land availability. The system uses a NodeMCU ESP32 as the main controller, an SHT20 sensor to measure temperature and humidity, and a pH sensor to monitor the acidity of the nutrient solution. Sensor data are displayed in real time through an LCD and an Android-based application, and are also used to control an automatic fan to maintain optimal environmental conditions. The research method applied is an experimental approach comprising a literature review, system design, hardware and software implementation, and system testing. Based on the research results, the IoT-based smart farming system was successfully developed and can monitor plant environmental conditions and nutrient solutions in real time via an Android application, with data stored in a database and displayed appropriately. The test results indicate that the system helps users manage vegetable cultivation more efficiently. This system is expected to provide an effective, efficient, and sustainable smart farming solution for urban areas with limited land availability.
Applying an IoT Technology in Hydroponic Smart Farming Systems on a Limited Area Dwi Endah Wahyuni; Marti Widya Sari; Prahenusa Wahyu Ciptadi; R. Hafid Hardyanto; Banu Santoso
APPLIED SCIENCE AND TECHNOLOGY REASERCH JOURNAL Vol. 5 No. 1 (2026): 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.v4i2.9324

Abstract

Population growth continues to drive food demand, while agricultural land becomes increasingly scarce due to urbanization and land conversion. This condition demands agricultural innovations that can increase productivity sustainably in limited land. One emerging solution is the hydroponic system, but managing key parameters such as water temperature, water level, and nutrient content (TDS) is often still done manually, which risks reducing crop quality. This study aims to design and implement an Internet of Things (IoT)-based hydroponic system capable of real-time and remote monitoring. The research method used is an experimental method, including literature review, needs analysis, system design, hardware and software installation, and system testing. The system was developed using an ESP32 microcontroller with a DS18B20 temperature sensor, a JSN SR04T ultrasonic sensor, and a TDS sensor, along with an Android application as the monitoring interface. The design results show that the system can monitor hydroponic conditions in real time, powered by solar panels. This system is expected to improve the efficiency of nutrient management and support the implementation of smart agriculture in limited land.
Developing an IoT-Based Smart Mini Hydroponic Greenhouse Prototype Arya Nanda Eka Putra; Marti Widya Sari; Prahenusa Wahyu Ciptadi; R. Hafid Hardyanto; Banu Santoso
APPLIED SCIENCE AND TECHNOLOGY REASERCH JOURNAL Vol. 5 No. 1 (2026): 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.v4i2.9325

Abstract

The development of urban agriculture faces challenges related to limited land availability, water scarcity, and inefficient plant management. These conditions encourage the adoption of smart agricultural technologies that operate automatically and efficiently. This study aims to develop an IoT-based smart mini greenhouse prototype suitable for urban environments with limited space. The research method used is an experimental approach focusing on system design and implementation. The system employs an ESP32 microcontroller as the main control unit and is equipped with pH, Electrical Conductivity, and water temperature sensors to monitor the quality of hydroponic nutrient solutions. Sensor data are automatically processed to control circulation pumps and nutrient correction pumps via relay modules, and the data are transmitted to a web-based monitoring system in real time. The test results show that the system can monitor water quality parameters stably and automatically perform irrigation and nutrient correction according to predefined threshold values. The implementation of this system improves the efficiency of water and nutrient management and reduces reliance on manual monitoring. These results indicate that the IoT-based smart mini greenhouse has the potential to serve as a practical and sustainable solution for supporting urban farming in areas with limited land.
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 Arya Nanda Eka Putra Azman, Mohamed Nor Azhari Baeturohman, Rama Bayu Faris Arkan Bayu Setiaji Dhananjaya Yama Hudha Kumarajati Dony Ariyus Dwi Endah Wahyuni Eko Pramono Elik Hari Muktafin Erika Amalia Erni Seniwati Feriman Haryoko Haryoko Herianto Ichsan Wasiso Irma Rofni Wulandari Jeki Kuswanto Jeki Kuswanto K Rasyid, Rum Mohamad Andri Kusrini Kusuma, Mohan Henry Lukman Lukman Marti Widya Sari Marti Widya Sari, Marti Melinne Maldini Rosady Moch. Akbar Maulana Muhammad Abdul Ghofur Muhammad Koprawi Muhammad Kusumawan Herliansyah Muhammad Rudyanto Arief Muhammad Saifulloh Mulyatun, Sri Nila Feby Puspitasari NINIK TRI HARTANTI Nur Rahman, Nur Nuraini Nuraini Pradipta Mahardika Sulaksono Prahenusa Wahyu Ciptadi Prasetya, Dian R. Hafid Hardyanto R. Hafid Hardyanto Rangga Wahyu Nugroho Rasyid, Rum Mohamad Andri K Rofinus Benson Date Bay Rosyidah Jayanti Vijaya Ryan Putranda Kristianto Setiawan, Fanes Tegris, Efrat Toriq, Farhan Tri Hartanti, Ninik Utama, Hastari Vivin Wahyudi Wangi Pandan Sari Wijayanto, Febri Windyarto Aziz Assidiqie Zaim Irfansyah Arbi