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All Journal Jurnal Pendidikan Vokasi International Journal of Advances in Intelligent Informatics jurnal Teknologi Informasi Magister International Journal of Artificial Intelligence Research KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Teknologi Informatika dan Komputer Jurnal Pengabdian Dharma Wacana Journal of Research in Social Science and Humanities International Journal of Advanced Science and Computer Applications Jurnal Masyarakat Madani Indonesia Jurnal Alih Teknologi Sistem Informasi (JATSI)

Nurdiyanto, Heri

Pendidikan Teknologi Dan Kejuruan Universitas Negeri Yogyakarta

Author-ID : 545024

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

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Student Opinions on the Use of High-Tech Mobile Devices in the Design of Digital Games for Learning Jeanette, Eva; Ovchinnikova, Brooks; Nurdiyanto, Heri
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : Universitas Dharma Wacana

Schools have adopted digital technologies as a strategy for learning and teaching activities because it offers opportunities for scaffolding. This strategy has been implemented in conjunction with creative activities. In addition, activities based on digital games, known as digital game-based learning (DGBL), and various mobile technologies, have been piloted in schools over the past few years to develop innovative learning. The purpose of this research is to investigate how children's collaborative interactions develop while participating in activities requiring them to solve problems utilizing intelligent and mobile technology. Our research combines theoretical viewpoints on joint participation, affordances, and a sense of community in the context of collaborative interactions. This is done with a contextual perspective on learning as its starting point. The following are some of the questions posed in this research: (1) How do children's digital game design activities drive and support collaborative interactions while they are engaged in problem-solving activities? Furthermore, (2) How do children's ideas for designing digital games manifest themselves during activities involving the design of games that involve innovative mobile technology? The study is based on a case where a creative workshop was held with 22 Swedish third-grade children aged 9 to 10 years old who participated in game design activities in a pedagogical lab. When the children worked together to solve the problem of designing and producing a joint digital game idea using mobile technology, a sense of community emerged due to their efforts. The study's results were analyzed using a thematic approach, which revealed that the children used different orientations in their collaborative interactions. Based on this, we argue that it is crucial to be aware of the pedagogical context when preparing for educational activities that involve innovative mobile technology. This is because the pedagogical context is the aspect of the design that creates meaningful collaborative interactions, and it is only then that innovative mobile technology becomes smart. These findings have significant ramifications for the methodological field of incorporating cutting-edge mobile technology into various types of educational settings

Analysis of Expert System for Early Diagnosis of Disorders During Pregnancy Using the Forward Chaining Method Basiroh, Basiroh; Priyatno, Priyatno; Kareem, Shahab Wahhab; Nurdiyanto, Heri
International Journal of Artificial Intelligence Research Vol 5, No 1 (2021): June 2021
Publisher : Universitas Dharma Wacana

Nowadays technological developments are increasingly having a positive influence on the development of human life, including in the health sector. One of them is an expert system that can transfer an expert's knowledge into a computer application to simplify and speed up the diagnosis of a disorder or disease in humans. The purpose of this final project is to design an application to diagnose diseases that occur during pregnancy which is caused by the existence of these pregnancies to simplify and speed up the diagnosis of diseases experienced by pregnant women. This study uses the forward chaining method. By involving experts in this expert system analysis according to current needs. Users are given easy access to information on several types of pregnancy disorders and their symptoms, as well as consultation through several questions that the user must answer to find out the results of the diagnosis. While experts are facilitated in system management, both the process of adding, updating and, deleting data.

A contribution spanning three time periods offered by artificial intelligence and synthetic biology Sven, Diaconescu Ada; Bellman, Francesco; Nurdiyanto, Heri
International Journal of Artificial Intelligence Research Vol 7, No 1 (2023): June 2023
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.348

The field of synthetic biology benefits significantly from the application of artificial intelligence. I'd want to make three suggestions, which all have something to do with the past, the present, and the future of artificial intelligence. The works of Turing and von Neumann in biology and artificial systems from the past are exciting to investigate within the new framework of synthetic biology, particularly regarding the concepts of self-modification and self-replication as well as their links to the emergence and the bottom-up approach. The ongoing epistemological investigation into the emergence and the research being conducted on swarm intelligence, superorganisms, and biologically inspired cognitive architecture may result in discoveries on the potential uses of synthetic biology to explain mental processes. Finally, the current discussion on the future of artificial intelligence and the rise of superintelligence may point to some research trends for the future of synthetic biology and help to better define the boundary of concepts such as "life," "cognition," "artificial," and "natural," as well as their interconnections in theoretical synthetic biology. In addition, the rise of superintelligence may point to some research trends for the future of synthetic biology

Fuzzy Preference Relations-Based AHP for Multi-Criteria Supplier Segmentation Nurdiyanto, Heri; Fauzi, Chairani; Lestari, Sri
International Journal of Artificial Intelligence Research Vol 8, No 1 (2024): June 2024
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.1.1103

Supplier segmentation is a strategic activity for businesses. It involves dividing suppliers into distinct categories and managing them differently. Various supplier typologies based on different dimensions and factors are available in the existing literature. By highlighting two main characteristics the skills and the desire of suppliers to work with a specific company this article integrates many typologies. Almost all of the supplier segmentation criteria stated in the literature are covered by these dimensions. These dimensions can be defined utilizing a multi-criteria decision-making process for each specific case. To account for the inherent ambiguities and uncertainties in human judgment, a fuzzy Analytic Hierarchy Process (AHP) is suggested as part of the technique. This approach makes use of fuzzy preference relations. A broiler firm uses the suggested process to divide up its suppliers. A categorization of vendors according to two aggregated criteria is the end outcome. Lastly, we offer some suggestions for future research, draw some conclusions, and talk about some techniques to address distinct sectors

Application of Computer Vision and Pattern Recognition in Automated Quality Inspection of Industrial Products Nurdiyanto, Heri; Kindiasari, Aktansi; Sulistiyanto, Sulistiyanto
International Journal of Artificial Intelligence Research Vol 9, No 2 (2025): December
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v9i2.1507

Quality inspection is a critical process in industrial production to ensure that products meet predefined standards and specifications. Traditionally, quality inspection has relied heavily on manual visual checks, which are time-consuming, subjective, and prone to human error. This study explores the application of computer vision and pattern recognition techniques to develop an automated quality inspection system for industrial products. The proposed system employs high-resolution cameras and image processing algorithms to capture and analyze visual features of products in real-time on the production line. Key techniques utilized include feature extraction, edge detection, and texture analysis to identify defects such as scratches, dents, and dimensional inaccuracies. Pattern recognition algorithms, such as support vector machines (SVM) and convolutional neural networks (CNN), are trained on large datasets of product images to classify items as acceptable or defective with high accuracy. The system was tested on a dataset collected from a manufacturing facility producing metal components. Experimental results demonstrate that the automated system achieved an inspection accuracy of 98%, significantly outperforming manual inspection methods in terms of speed and consistency. Furthermore, the integration of this system into the production line reduced inspection time by approximately 70% and minimized production downtime. This research highlights the potential of intelligent informatics, particularly computer vision and pattern recognition, in enhancing the efficiency, reliability, and scalability of industrial quality control processes. The findings suggest that such automated systems can contribute significantly to the advancement of Industry 4.0 by enabling smart manufacturing practices and reducing dependence on manual labor. Future work will focus on extending the system to handle more complex products and dynamic production environments

An AI-driven framework for learning analytics and operational optimization in technology and vocational education: Bridging industrial engineering and informatics Nurdiyanto, Heri; Hernandes , Leonel; Hammad, Jehad A.H; Kindiasari, Aktansi
Jurnal Pendidikan Vokasi Vol. 15 No. 3 (2025): November
Publisher : ADGVI & Graduate School of Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jpv.v15i3.95617

This study aims to present an artificial intelligence-based framework that combines learning analytics with operational optimization, which can address the ever-present problems concerning technology and vocational education. In the case of vocational institutions, it has been noticed that while learning environments are increasingly embracing the incorporation of digital technologies, the connection between the use of data for educational outcomes and operational decision-making remains disconnected. In many instances, learning-related data is analyzed separately from production-oriented activities, which include scheduling, resource allocation, and process efficiency, despite the fact that these activities are part of the learning process in the factory and learning environments. This study aims to address the disconnect between the use of learning-related data and production-oriented activities through the incorporation of perspectives from industrial engineering and informatics, which are integrated into a single framework that is oriented towards artificial intelligence. Machine learning is utilized for the representation of learning processes, while optimization techniques are used for decision-making regarding task allocation, scheduling, and resource allocation. Instead of being restricted to a particular application domain, the framework is developed with the idea of adaptability so that it can be used across different contexts of vocational education. An empirical study was conducted within a particular context of a technology-oriented vocational education domain to assess the viability of the proposed framework. It was found that the integration of learning analytics with operational optimization provides a more consistent outcome compared to the individual analysis of these factors. It was also found that the proposed AI-based framework provides a better outcome for the assessment of competency as well as the prediction of performance, which leads to the efficiency of managing a production-oriented learning process. Such findings indicate the ability of the application of AI to support the field of vocational education more comprehensively. This study contributes to the field of research by proposing an interdisciplinary framework that goes beyond the idea of individual technological tools to offer a more comprehensive perspective on the adoption of AI within the context of vocational education.

Inovasi Galeri Virtual Seni Budaya Nusantara sebagai Media Edukasi dan Pelestarian Budaya di Era Digital Permana, Angga Sukma; Suparmanto, Nova; Nurdiyanto, Heri; Sulistyo, Bambang
Jurnal Masyarakat Madani Indonesia Vol. 5 No. 1 (2026): Februari
Publisher : Alesha Media Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59025/b7v84883

Perkembangan teknologi digital membuka peluang baru dalam upaya pelestarian dan penyebarluasan seni budaya Nusantara. Namun, di sisi lain, minat generasi muda terhadap warisan budaya lokal cenderung menurun karena terbatasnya akses terhadap informasi dan media pembelajaran yang menarik. Kegiatan Pengabdian kepada Masyarakat (PKM) ini bertujuan untuk menghadirkan sebuah inovasi berupa Galeri Virtual Seni Budaya Nusantara yang dapat dimanfaatkan sebagai media edukasi sekaligus sarana pelestarian budaya di era digital. Program ini dilaksanakan melalui beberapa tahapan, mulai dari identifikasi kebutuhan masyarakat, perancangan konsep galeri virtual, pengembangan platform berbasis web, hingga pelatihan pemanfaatan galeri kepada masyarakat dan komunitas seni. Galeri virtual yang dikembangkan menampilkan berbagai koleksi seni budaya Nusantara seperti karya seni rupa, artefak budaya, serta dokumentasi pertunjukan tradisional dalam format digital yang mudah diakses. Hasil kegiatan menunjukkan bahwa keberadaan galeri virtual mampu meningkatkan pemahaman dan ketertarikan masyarakat terhadap kekayaan budaya Indonesia. Selain itu, platform ini juga memberikan ruang baru bagi pelaku seni dan komunitas budaya untuk mempromosikan karya mereka kepada publik yang lebih luas. Dengan demikian, inovasi galeri virtual ini tidak hanya berfungsi sebagai media edukasi, tetapi juga menjadi salah satu strategi adaptif dalam menjaga keberlanjutan seni budaya Nusantara di tengah perkembangan teknologi digital.

Co-Authors A.A. Ketut Agung Cahyawan W Agus, Isnandar Aldi Muharsyah Angga Sukma Permana Apriyanto, Krisnanda Dwi Apsiswanto, Untoro Bambang Sulistyo Bellman, Francesco Budi Sutomo Darmono Dikki Handoko Edi Istiyono Efori Buulolo Ella Wulandari Envermy Vem, Envermy Fachrurrazi Fachrurrazi Fauzi, Chairani Febri Sugandi Galih Pranowo Hammad, Jehad A.H Hermanto Hermanto Hernandes , Leonel Hotmelinsa Situmorang Ibrahim Khalid Ilma, Awla Akbar Inas Ajeng Nur Afifah Iqbal Saeed Umar Irfan Setiawan Jeanette, Eva Kareem, Shahab Wahhab Kharismawati, Anisa Khasanah Khasanah Kindiasari, Aktansi M Ikhsan Setiawan M Said Hasibuan Maharani Maharani, Maharani Mesran Mesran Mesran, Mesran Natalia Silalahi, Natalia Nelly Astuti Hasibuan Nidia Sutrikanti Noor Fitrihana Nova Suparmanto Nur Endah Januarti Ovchinnikova, Brooks Praptiwi, Wahyu Kharina Priyatno, Priyatno Ridwan Yusuf Sadiq Ullah Saputri, Tri Aristy Singagerda, Faurani Santi Soraya Rahma Hayati Sri Lestari Sudaryono Sudaryono Suginam Sulistiyanto Sulistiyanto Sulistiyanto Sulistiyanto, Sulistiyanto Surya Darma Nasution Susanto, Tofan Susetyaningsih, Ririn Sutiksno, Dian Utami Sven, Diaconescu Ada Syaputra, Muhammad Adie Taronisokhi Zebua Usep Saprudin Widowati Pusporini, Widowati Yuhandri Yuhandri, Yuhandri

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