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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
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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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
PENGEMBANGAN SISTEM DETEKSI KECELAKAAN DI JALAN RAYA MENGGUNAKAN ALGORITMA YOLOv8 DAN NOTIFIKASI OTOMATIS MELALUI TELEGRAM Alaydrus, Syarif Ahmad Hasny Al Mutsanna; Banu Santoso
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4218

Abstract

This research develops an accident detection system using supervised machine learning with YOLOv8 for object detection. The stages include data collection, labeling, model training, and system implementation with Telegram notifications. Data is taken from sample videos, converted into frame-by-frame images, and labeled with LabelImg. YOLOv8 is trained to recognize five object classes: car, accident, truck, person, and motorcycle. Implementation is done in Python with OpenCV, ultralytics, and cvzone. The system sends real-time notifications to Telegram upon an accident, achieving an average accuracy of 0.914 with notification times of 287.2ms – 334.1ms. This system aids traffic monitoring and quick response to accidents, reducing the negative impact of traffic accidents.
Implementation of WSN and IoT to Monitor and Control Villa Electronic Equipment in Blankspot Areas Saifulloh, Muhammad; Santoso, Banu; Ariyus, Dony
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.5165

Abstract

Maintaining a remote villa in a blank spot area presents challenges in ensuring optimal environmental conditions without the direct presence of the owner. This study aims to develop an Internet of Things (IoT)-based Wireless Sensor Network (WSN) system using the XBee S2C module with the Zigbee remote monitoring and control protocol. This system utilizes temperature, humidity, lighting, and water level sensors connected to electronic device controls such as lights, fans, and water pumps. Sensor Nodes are placed in the villa to collect data, while Coordinator Nodes are located in areas with internet access to upload data to the Thingspeak platform. Data is visualized through an interactive web interface that allows for remote control up to 1.03 km. The test results show a data transmission success rate of 100% with an average control response time of 6.5 and 9 seconds. This system offers the best solution for managing a villa in a blank spot area, making it easy for owners to monitor and control electronic equipment in real-time. This research contributes to developing WSN and IoT technologies, especially for applications in remote areas with website platform.
ANALISIS PERANCANGAN METODE VLSM DAN FLSM PADA MANAJEMEN IP ADDRESS LAN Rahman, Nur; Santoso, Banu; Pambudi, Agung; K Rasyid, Rum Mohamad Andri; Mulyatun, Sri; Tegris, Efrat; Widya Sari, Marti
(JITEK)Jurnal Ilmiah Teknosains Vol 10, No 1/Mei (2024): Jitek
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jitek.v10i1/Mei.18988

Abstract

Computer networks are very important for people in the current era of modern globalization to access their daily needs. A good computer network is certainly needed to speed up community activities. Sub-netting is one of the things that can be done to optimize IP management on a computer network. This research on the application of the subnetting method on a computer network can be a reference in determining a better subnetting method for building a network. This research aims to analyze the influence of the two subnetting methods on a computer network, compare the network speeds obtained, and the application of the two subnetting methods on a computer network based on QoS parameters. The research results show that the analysis of both subnetting methods displays a very good QoS Index with the following details: FLSM: average throughput 50.792kbps, packet loss 0%, average delay 5.25ms, average jitter 5.37ms. VLSM: average throughput 77.843kbps, packet loss 0%, average delay 3.52ms, average jitter 3.58ms. In the FLSM method, all applied subnets have 101 remaining unused IPs and in VLSM, all applied subnets have 19 unused IPs remaining. This proves that networks designed using the VLSM subnetting method have more optimal network quality and more effective IP management.
PROGRAM KEMITRAAN MASYARAKAT PADA PENGELOLAAN GREEN HOUSE SMART FARMING DI DUKUH TAMBAK, NGESTIHARJO, BANTUL Santoso, Banu; Sari, Marti Widya; Prasetya, Dian; Tri Hartanti, Ninik
Jurnal Berdaya Mandiri Vol. 5 No. 3 (2023): JURNAL BERDAYA MANDIRI (JBM)
Publisher : Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jbm.v5i3.5616

Abstract

This community service was carried out in the Tambak Hamlet, Ngestiharjo Village, Kasihan, Bantul, Yogyakarta. Tambak Hamlet is a hamlet located in the Ngestiharjo Village, Bantul, which is on the outskirts of Yogyakarta. Therefore, the population in this area is quite dense, so that agricultural land becomes increasingly limited. Narrow land still exists in this area, which can be used for farming or planting horticultural crops. However, nowadays the weather is getting more and more erratic, so the time for planting is becoming more difficult. In Tambak Hamlet there is already an IoT-based green house for smart farming for horticultural crops, but it has not been managed, because it is still in the development stage. Based on this, the service team is trying to make a suggestion regarding the management of the green house, so that the results can be maximized and able to increase the economic value for the community. This service aims to develop agricultural digitalization through the Smart Farming Model, using Internet of Things (IoT) technology, to assist in crop monitoring, so that the growth and yield of horticultural crops is optimal. The purpose of this service is in line with the 3rd and 5th Main Performance Indicators (IKU) of Higher Education. The 3rd IKU, namely lecturers who carry out activities outside the campus, in this case the lecturer performs community service which is carried out in the Tambak Hamlet. The 5th IKU is the work of lecturers used by the community, namely in the form of ideas and thoughts in the development of smart farming. The expected outputs from this community service activity are services in the form of training and assistance for the management of green house smart farming, and publication in the form of scientific articles that will be published in national journals. Keywords: smart farming, green house, community service, digitalization, agriculture
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.
EVALUASI DASAR PENETRATION TESTING MENGGUNAKAN FRAMEWORK MITRE ATT&CK Vivin Wahyudi; Muhammad Rudyanto Arief; Banu Santoso; Rangga Wahyu Nugroho
E-Link: Jurnal Teknik Elektro dan Informatika Vol. 20 No. 1: Mei 2025
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/e-link.v20i1.9399

Abstract

Penetration testing is a method used to identify security vulnerabilities in networks or computer systems. In this process, pentesters attempt to exploit security gaps by simulating potential attacks that could be carried out by an actual attacker. The goal of penetration testing is to evaluate the security of computer systems or networks. This multi-stage approach, which includes information gathering, exploitation, and post-exploitation, utilizes the MITRE ATT&CK framework. Tools are used to help identify and exploit security weaknesses, such as nmap, netdiscover, metasploit, SSH, and MySQL. This research can reduce the risk of data loss and operational disruptions, enhance pentesters' skills and awareness, and strengthen the security of computer systems and networks.
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 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 Rudyanto Arief Muhammad Saifulloh Mulyatun, Sri Nila Feby Puspitasari NINIK TRI HARTANTI Nur Rahman, Nur Nuraini Nuraini Pradipta Mahardika Sulaksono Prasetya, Dian 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 Vivin Wahyudi Wangi Pandan Sari Wijayanto, Febri Windyarto Aziz Assidiqie Zaim Irfansyah Arbi