Article Per Year (5 Year)
p-Index From 2021 - 2026
0.778
P-Index
This Author published in this journals
All Journal Sistemasi: Jurnal Sistem Informasi JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Al-MIKRAJ: Jurnal studi Islam dan Humaniora
Andrias Darmayadi
Universitas Komputer Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
PENERAPAN CONVOLUTIONAL NEURAL NETWORK UNTUK PENGENALAN BAHASA ISYARAT INDONESIA: STUDI KASUS DAN TINJAUAN FILSAFAT SAINS Hernalom Sitorus; Ucu Nugraha; Sri Titi Handayani; Agus Nursikuwagus; Usep Mohamad Ishaq; Andrias Darmayadi
Jurnal Ilmiah Teknologi Infomasi Terapan Vol. 12 No. 2 (2026)
Publisher : Universitas Widyatama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33197/jitter.vol12.iss2.2026.3448

Abstract

The low literacy of Indonesian Sign Language (BISINDO) in the general public remains a barrier to communication with the Deaf community, while research on AI-based sign language recognition generally focuses solely on technical achievements. This study aims to develop a BISINDO alphabet recognition system based on Convolutional Neural Network (CNN) and evaluate it through a philosophy of science perspective. The methods used include collecting a BISINDO alphabet hand image dataset, data augmentation, and transfer learning-based CNN training with the MobileNetV2 architecture and a stepwise training scheme, then deployed to Android using TensorFlow Lite. Test results show the system is able to achieve an accuracy of around 93% on controlled test data with stable real-time inference performance. The scientific contribution of this research is not only in the development of applied AI systems, but also in providing a reflective ontological, epistemological, and axiological framework to assess the validity and social implications of BISINDO recognition technology.
Open Government Data Analytics of Tourist Visits In West Java 2014–2024: A Data Science and Philosophy of Science Perspective Ucu Nugraha; Hernalom Sitorus; Sri Titi Handayani; Agus Nursikuwagus; Usep Mohamad Ishaq; Andrias Darmayadi
Sistemasi: Jurnal Sistem Informasi Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.6175

Abstract

Open Government Data (OGD) in tourism provides opportunities for data-driven analytics to support destination management policies. In policy practice, tourism OGD is often accepted at face value as a direct representation of real-world conditions, even though such data are constructed through definitions, recording procedures, and measurement choices. Therefore, a philosophy of science perspective is essential in data governance. This article analyzes an Open Data Jabar dataset on the number of tourist visits by visitor type and district/city in West Java Province for the period 2014–2024 (n = 565; 27 districts/cities; two visitor categories: domestic and international). The data science approach includes data quality auditing (completeness and consistency), time-series aggregation, spatial concentration measurement using the Gini coefficient, and a comparison of shock–recovery patterns in tourist visits before and after the pandemic. The results indicate a decline in total visits of -50.6% in 2020 compared to 2019, with international visits experiencing the sharpest drop (-82.8%). By 2024, total visits reached 64,517,298, dominated by domestic tourists (63,963,443; international share 0.9%). Spatial concentration in 2024 is reflected by a Gini coefficient of 0.429, with the top five regions accounting for 44.2% of total visits. The discussion emphasizes that visitor counts are epistemic representations shaped by definitions, reporting practices, and data cleaning processes. Therefore, policy recommendations should be accompanied by data provenance, metadata, and explicit uncertainty annotations to avoid the reification of indicators.
Epistemologi Artificial Intelligence: Kebenaran, Validitas, dan Otoritas Algoritmik Sri Nurhayati; Diana Effendi; Agus Nursikuwagus; Usep Mohamad Ishaq; Andrias Darmayadi
AL-MIKRAJ Jurnal Studi Islam dan Humaniora (E-ISSN 2745-4584) Vol. 6 No. 1: Al-Mikraj, Jurnal Studi Islam dan Humaniora
Publisher : Pascasarjana Institut Agama Islam Sunan Giri Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/almikraj.v6i1.8530

Abstract

The development of artificial intelligence (AI) has brought fundamental changes in the way knowledge is produced, validated, and accepted in various sectors of life. Algorithmic models, especially deep learning, generate predictions and recommendations that are often treated as operational truths even though the inference process is not fully explainable. This study analyzes how AI changes the understanding of truth, validity, and epistemic authority from the perspective of the philosophy of science, and links it to the ontological and axiological dimensions in modern knowledge production. A qualitative approach based on philosophical analysis is used to integrate the thoughts of Popper, Kuhn, Lakatos, Van Fraassen, and Floridi. The results show that AI shifts knowledge from rational justification to performative and statistical validity, and challenges the position of humans as the primary epistemic agents. This study asserts that the epistemic transformation triggered by AI requires ontological and axiological reflection so that the development of knowledge remains in line with humanitarian principles and ethical responsibility
Epistomologi Sains di Era Kecerdasan Buatan: Menimbang Kebenaran Prediktif Popon Dauni; Rizal Rachman; Sri Erina Damayanti; Agus Nursikuwagus; Usep Mohamad Ishaq; Andrias Darmayadi
AL-MIKRAJ Jurnal Studi Islam dan Humaniora (E-ISSN 2745-4584) Vol. 6 No. 1: Al-Mikraj, Jurnal Studi Islam dan Humaniora
Publisher : Pascasarjana Institut Agama Islam Sunan Giri Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/almikraj.v6i1.8879

Abstract

The development of artificial intelligence (AI), particularly machine learning and deep learning, has brought significant changes to contemporary scientific practices. AI no longer functions solely as a computational tool, but plays an active role in the production, validation, and evaluation of scientific knowledge through data modelling and probabilistic inference. This development raises fundamental questions in the philosophy of science, particularly regarding the shift in the concept of scientific truth from the paradigm of empirical verification and causal explanation towards an approach based on prediction, mathematical approximation, and the management of uncertainty. This research aims to re-evaluate the status of scientific truth in the age of AI by philosophically analysing the relationship between uncertainty, computational knowledge, and scientific truth claims generated by AI models. The research method used is a qualitative study based on literature review and conceptual analysis of contemporary science and technology philosophy literature. The study results indicate that the integration of AI into scientific practice is driving a shift in the epistemology of science from a verifiative orientation towards a predictive epistemology that emphasises model reliability and instrumental validity. This research concludes that scientific truth in the AI era is more contextual and pragmatic, thus demanding an adaptive, reflective, and interdisciplinary framework for the epistemology of science. Theoretically, scientific truth in the age of artificial intelligence is more contextual, thus requiring an adaptive, reflective, and interdisciplinary framework for the epistemology of science as its main theoretical contribution.
Co-Authors Agus Nursikuwagus Diana Effendi Hernalom Sitorus Popon Dauni Rizal Rachman Sri Erina Damayanti Sri Nurhayati Sri Titi Handayani Ucu Nugraha Usep Mohamad Ishaq