دورية أكاديمية

FAKTOR-FAKTOR YANG MEMENGARUHI INDEKS ARTIFICIAL INTELLIGENCE GLOBAL

التفاصيل البيبلوغرافية
العنوان: FAKTOR-FAKTOR YANG MEMENGARUHI INDEKS ARTIFICIAL INTELLIGENCE GLOBAL
المؤلفون: Yanuar Ichwan Satria Nugroho, Triyani Hendrawati, Kennedy Marthendra, Brian Riski Jayama Simanjuntak
المصدر: Jurnal Lebesgue, Vol 4, Iss 3, Pp 1425-1438 (2023)
بيانات النشر: Universitas Bina Bangsa, 2023.
سنة النشر: 2023
المجموعة: LCC:Mathematics
مصطلحات موضوعية: regresi linear model, teknologi, kemajuan, kecerdasan buatan, indeks ai global, linear regression model, technology, progress, artificial intelligence, global ai index, Mathematics, QA1-939
الوصف: The Global AI (Artificial Intelligence) Index is a value that aims to measure the progress of artificial intelligence (AI) around the world. Currently, technology is increasingly sophisticated and of course makes humans compete to create technology to make life easier. The purpose of this study is to analyse the effect of human resources, infrastructure, and government policies on the global AI index. The method used to determine the relationship between human resources, infrastructure, and government policies with the global AI index is the multiple linear regression method. From the results of data processing, a linear regression = - 7,54675 + 0,65972 + 0,25096 + 0,07672 . Based on this model, the influence of human resources, infrastructure, and government policies has a significant positive effect on the Global AI Index. The coefficient of determination of the model is 0.8833, in other words, human resources (), infrastructure (), and government policy () are able to explain the value of the global AI index (Y) by 88.33% and the remaining 11.67% is explained by other variables
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
Indonesian
تدمد: 2721-8929
2721-8937
العلاقة: https://lebesgue.lppmbinabangsa.id/index.php/home/article/view/406Test; https://doaj.org/toc/2721-8929Test; https://doaj.org/toc/2721-8937Test
DOI: 10.46306/lb.v4i3.406
الوصول الحر: https://doaj.org/article/ad07c16f803c4aaf83334835240590c4Test
رقم الانضمام: edsdoj.07c16f803c4aaf83334835240590c4
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:27218929
27218937
DOI:10.46306/lb.v4i3.406