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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurnal Inotera Balanca : Jurnal Ekonomi dan Bisnis Islam Applied Science and Technology Research Journal
Herianto
Universitas Gadjah Mada
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

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Analysis and Comparison of 3D Printed Soft Pneumatic Actuator Configurations for Swaying Lateral Motion of Planar Objects Syahirul Alim Ritonga; Ifran N. Sah Putra Sidauruk; Herianto; Adriyan Christofer Sitanggang
Jurnal Inotera Vol. 9 No. 1 (2024): January-June 2024
Publisher : LPPM Politeknik Aceh Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31572/inotera.Vol9.Iss1.2024.ID297

Abstract

Soft pneumatic actuators (SPAs) offer unique possibilities in robotics and automation due to their compliance and versatility. Unlike conventional actuators that can move either revolute or prismatic, SPAs can produce complex motions, especially when configured in combinations. This paper systematically investigated the performance of four distinct SPA configurations (Types 1-4) concerning the task of moving a planar square object and swaying it laterally to the right and left. These configurations are analyzed for their ability to achieve desired movements and orientations. Type 4, involving two SPAs, emerges as the most effective configuration, successfully navigating the challenges posed by the desired task. In contrast, Type 2, consisting of four SPAs, encounters difficulties in executing the task attributed to increased inertia, which was similar as type 3. Types 1, while not precisely meeting the primary task, reveal distinctive movements - left-right motion without orientation change. This study contributes valuable insights into the complex dynamics of SPAs, offering considerations for optimal design and performance. The outcomes could be developed in the future in soft actuator applications, especially those involving configurations based on specific needs.
COMPARATIVE PERFORMANCE OF SEQUENTIAL CNN AND PRE-TRAINED LEARNING FOR 3D PRINTING DEFECT CLASSIFICATION Dwi Riyono; Cholid Mawardi; Herianto
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 3 (2026): JITK Issue February 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i3.7337

Abstract

3D Printing is currently needed in various industries, including education in terms of research development. In this study, researchers classify 3D printing defect images to recognize images that are difficult to see with the naked eye. With limited observation, an image classification method is needed to help users detect defects in the printing process with a Deep Learning model. The printing process uses PLA and ABS-based filament materials, which are mostly used in 3D Printing objects with fused deposition modeling (FDM)-based 3D Printer machines. In this study, there are several stages, including data augmentation, model development using sequential CNN, pre-trained CNN based with pre-trained models, namely VGG-16 and VGG-19, training, validation, and model evaluation. The dataset taken for training is 1557, with a ratio of 80 percent training and 20 percent validation between defective and non-defective objects. The results of this study have a good accuracy value on Sequential CNN with an accuracy of 99.68% compared to pre-trained CNN models, namely VGG-16 and VGG-19. The classification results are also compared with other additive manufacturing classification methods with different machines and materials such as metal and 3D Food Printing which are measured based on classification model optimization analysis
Comparison of 3D Printing Technologies for Polymer-HA Bone Scaffolds: A Systematic Review Toward Hybrid Fabrication Strategies Dhananjaya Yama Hudha Kumarajati; Herianto; Muhammad Kusumawan Herliansyah; Kusmono; 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.v4i2.8230

Abstract

Bone scaffold fabrication using 3D printing faces a fundamental dilemma: the trade-off between mechanical strength and biological functionality. To address this challenge, a systematic literature review (SLR) of 28 primary research articles was conducted to compare various hydroxyapatite-based scaffold fabrication technologies. The analysis confirms a clear trade-off: Fused Filament Fabrication (FFF) excels in mechanical strength, Digital Light Processing (DLP) in architectural precision (<100 µm), and Direct Ink Writing (DIW) in flexibility for bio-functionality, proving no single method is ideal. The main conclusion is that hybrid fabrication strategies—intelligently integrating the strengths of multiple technologies—offer the most promising approach to creating functional scaffolds with an optimal balance of strength and bioactivity for future clinical applications.
Technology Trends, Innovations, and Future Research Directions in 3D Printing (Additive Manufacturing): A Systematic Literature Review Banu Santoso; 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 Banu Santoso; 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
Pengaruh Green Fiance, Pertumbuhan Ekonomi dan Keterbukaan Perdagangan Terhadap Emisi CO2 Bukti dari Negara Anggota OKI: The Effect of Green Fiance, Economic Growth and Trade Openness on CO2 Emissions Evidence from OIC Member Countries Herianto; Andi Ajeng Tenri Lala Tenri Lala; Nurpasila
Balanca : Jurnal Ekonomi dan Bisnis Islam Vol. 6 No. 2 (2024): Balanca: Jurnal Ekonomi dan Bisnis Islam
Publisher : Institut Agama Islam Negeri Parepare

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35905/balanca.v6i2.7895

Abstract

Sustainable development is currently not only measured by the economic growth of a country or region but goes further than that. One of them, through the stability and maintenance of the environment. This study aims to look at the relationship between green financing, economic growth, trade barriers and CO2 emissions specifically in countries that are members of the OIC cooperation. This study uses a quantitative approach with a panel data estimation model with the help of testing using the eviews 9 statistical application. Samples were used in 8 countries namely Bahrain, Bangladesh, Brunei Darussalam, Indonesia, Malaysia, Jordan, Kazakhstan, Sudan and Saudi Arabia, with sample fees using purposive example. Furthermore, data was obtained from the official website of the world bank and the Islamic Financial Service Board (IFSB). The peculiarity of this research is that it shows that environmentally friendly financing, economic growth and the rise of trading have a positive effect on CO2 emissions. The results of this study confirm that development policies in several OIC member countries have had a significant impact on pollution in these countries and the presence of Islamic banks through financing in the green economy sector has not shown an impact that can reduce CO2 emissions.
Co-Authors Adriyan Christofer Sitanggang Alva Edy Tontowi Andi Ajeng Tenri Lala Tenri Lala Banu Santoso Dhananjaya Yama Hudha Kumarajati Ifran N. Sah Putra Sidauruk Kusmono M. Cholid Mawardi Muhammad Kusumawan Herliansyah Nurpasila Riyono, Dwi Syahirul Alim Ritonga Wangi Pandan Sari