Penerapan Algoritma K-Means Pada Pemetaan Kemampuan Penggunaan Teknologi Informasi Remaja dan Dewasa di Indonesia
-
Ronal Watrianthos
*
Universitas Al Washliyah, Rantauprapat,
Indonesia
- Reti Handayani Universitas Mahaputra Muhammad Yamin, Solok, Indonesia
- Ade Fitrah Putra Akhir Universitas Prof. Dr. Hazairin SH, Bengkulu, Indonesia
- Ambiyar Ambiyar Universitas Negeri Padang, Padang, Indonesia
- Unung Verawardina Universitas Negeri Padang, Padang, Indonesia (*) Corresponding Author
Abstract
In modern-day Indonesia, having access to various forms of technology is regarded as crucial. This is because the IT skills gap will only grow worse if the government does not act swiftly to make technology more accessible to the general public. PISA suggests that schools may gain much more from incorporating IT into their curriculum if they did so. The goal of this research is to establish whether or not there are notable variations in the level of knowledge in information technology across the different provinces in Indonesia. Official data from the Central Statistics Agency for 2019-2021, including information on the number of adolescents and adults aged 15-59 with abilities in the field of ICT at the provincial level, is used in the clustering calculation. The K-means algorithm is one unsupervised learning technique for clustering data into collections with other instances that share similar properties. The results showed that the seventh cluster had the lowest DBI value of the three examined, coming in at -0.357. Cluster 0 has the lowest average percentage of the population with IT skills, at 29.32%. Only in Papua Province will you find this particular zero cluster.
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