Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Al-MIKRAJ: Jurnal studi Islam dan Humaniora Software Engineering in Computing Systems
Sri Erina Damayanti
Universitas Komputer Indonesia
Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
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.
Global Trends and Framework Development of AI and IoT Integrated Waste Automation for Emerging Economies Sri Erina Damayanti; Brian Damastu Ridho Hutama; Popon Dauni; Jack Febrian Rusli
Software Engineering in Computing Systems Vol. 1 No. 2 (2026): May: Software Engineering in Computing Systems
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/secons.v1i2.444

Abstract

Waste management in Indonesia faces extreme regional disparities, ranging from critical waste accumulation zones and circular economy transition zones to specific material deficit zones. The primary problem lies in the inability of conventional systems to process heterogeneous waste efficiently, which leads to the failure of sustainable environmental conservation. An intelligent solution is required to integrate physical technology with an adaptive policy evaluation system. This research develops a systematic framework for the development and evaluation of waste processing automation technology. The research stages begin with a Bibliometric Analysis and Systematic Literature Review (SLR) using metadata from Scopus and Web of Science to identify global trends via VOSviewer. Furthermore, this study integrates AI and IoT as primary instruments for nature conservation. Through the processing of large data volumes (Big Data) from IoT sensors, AI (such as Multi-Criteria Decision Making) performs predictive analysis to automatically evaluate three regional conditions. AI plays a crucial role in determining corrective actions, including optimizing the use of oxy-hydrogen (HHO) fuel in incinerators to suppress emissions and managing cross-regional waste logistics, thereby ensuring natural resources are preserved through precise and low-pollution waste elimination processes. This research generates intelligent governance patterns and actionable insights to guide system users, particularly local governments and industrial managers, in implementing appropriate waste processing technologies. This solution provides automated operational guidance that ensures energy efficiency and economic sustainability while maintaining ecosystem preservation through standardized waste processing based on the specific regional characteristics in Indonesia.
Co-Authors Agus Nursikuwagus Andrias Darmayadi Brian Damastu Ridho Hutama Jack Febrian Rusli Popon Dauni Popon Dauni Rizal Rachman Usep Mohamad Ishaq