<mets:mets OBJID="eprint_77881" LABEL="Eprints Item" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/mets.xsd http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mets="http://www.loc.gov/METS/" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mets:metsHdr CREATEDATE="2026-08-11T10:23:33Z"><mets:agent ROLE="CUSTODIAN" TYPE="ORGANIZATION"><mets:name>Institutional Repository UIN Sunan Kalijaga Yogyakarta</mets:name></mets:agent></mets:metsHdr><mets:dmdSec ID="DMD_eprint_77881_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:titleInfo><mods:title>EVALUASI KESIAPAN PERUSAHAAN PENYEDIA JASA JARINGAN DI INDONESIA UNTUK TRANSFORMASI DIGITAL BERBASIS KECERDASAN BUATAN</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">NIM.: 23206051001</mods:namePart><mods:namePart type="family">Mochamad Ali Fais</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>Artificial intelligence (AI)-driven digital transformation has become a strategic necessity for network service providers or Internet Service Providers (ISPs), particularly because this industry faces increasing demands for service reliability, operational efficiency, security, and improved customer experience. This study aims to evaluate the readiness of medium-sized ISPs in Indonesia to implement AI-driven digital transformation by extending the Technology-Organization-Environment (TOE) framework into TOE-H-R through the addition of Human and Resilience dimensions. This model extension is intended to capture organizational readiness more comprehensively, not only from technological and environmental perspectives but also from human and operational resilience perspectives. The research model examines the effects of Technology, Organization, Environment, Human, and Resilience on AI readiness. In addition to direct relationships, the model also tests Human as a mediator in the relationship between Organization and AI readiness, and Resilience as a moderator in the relationship between Technology and AI readiness. This study applies a quantitative approach involving 150 managerial respondents and uses Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The model evaluation includes outer loading, construct reliability, Average Variance Extracted (AVE), Heterotrait-Monotrait Ratio (HTMT), Variance Inflation Factor (VIF), R-square, f-square, path coefficients, specific indirect effects, and total effects. The results show that Environment has a positive and significant effect on AI readiness with a coefficient of 0.297 and a p-value of 0.001. Organization also has a positive and significant effect on AI readiness with a coefficient of 0.209 and a p-value of 0.009, and a positive and significant effect on Human with a coefficient of 0.568 and a p-value of 0.000. Technology shows a positive direction of influence but is not significant at the 5% level. Human, Resilience, the Resilience x Technology interaction, and the mediation path of Organization -&gt; Human -&gt; AI readiness are not statistically significant. The R-square value of AI readiness is 0.536, indicating that the model explains 53.6% of the variance in AI readiness. These findings indicate that AI readiness among medium-sized ISPs is more strongly influenced by external environmental and organizational factors than by technology, human readiness, and resilience as direct predictors.</mods:abstract><mods:classification authority="lcc">004 Pemrosesan Data, Ilmu Komputer, Teknik Informatika</mods:classification><mods:originInfo><mods:dateIssued encoding="iso8061">2026-06-03</mods:dateIssued></mods:originInfo><mods:originInfo><mods:publisher>UIN SUNAN KALIJAGA YOGYAKARTA;FAKULTAS SAINS DAN TEKNOLOGI</mods:publisher></mods:originInfo><mods:genre>Thesis</mods:genre></mets:xmlData></mets:mdWrap></mets:dmdSec><mets:amdSec ID="TMD_eprint_77881"><mets:rightsMD ID="rights_eprint_77881_mods"><mets:mdWrap MDTYPE="MODS"><mets:xmlData><mods:useAndReproduction>
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