Abstract

Since the increase in Covid-19 in Indonesia, many new policies have been made by the government in prevention efforts. One of them is in the field of education through the Circular of the Ministry of Education and Culture No. 3692/MPK.A/HK/2020 concerning "Online Learning from home in the context of preventing the spread of coronavirus disease (Covid -19)", YASPIM Vocational School as one of the institutions at the lowest level, must respond and obey the circular letter from the Ministry of Education and Culture. According to the principal, namely Mr. Rosad Furqon, S.Ag., M.Pd, the process of online learning activities has not been maximized, especially in supporting learning facilities because the parents of students who attend school in this area are mostly middle-income, so not all students have sufficient supporting equipment. for online learning, in certain areas there are still signal problems, and teachers also complain about the declining achievement of student learning outcomes. To make it easier for schools and the government to take action in an effort to support the process of online teaching and learning activities, it is necessary for researchers to contribute ideas to determine the level of barriers to online learning, which are made into 2 clusters, namely a low cluster and a high cluster. In this study, researchers analyzed the level of barriers to online learning at YASPIM Vocational School by using the k-means clustering algorithm, which is a research field in analysis and data mining. In this algorithm, the grouping technique is based on the similarity of data that does not have any reference (unsupervised). However, it will divide the entire data into groups or have the same resemblance. Basically, this algorithm calculates the distance between each data center and the data center (centroid) to measure the similarity of the data. The results of this study obtained 10 low cluster classes, and 5 high cluster classes on online learning barriers at YASPIM Gegerbitung Vocational School.

Highlights

  • Sejak virus covid -19 masuk ke Indonesia pada bulan maret 2020 pemerintah membuat berbagai kebijakan dalam setiap bidang agar menekan angka penyebaran virus tersebut karena dinilai sangat berbahaya dan berdampak pada banyaknya angka kematian

  • many new policies have been made by the government in prevention efforts

  • of them is in the field of education

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Summary

PENDAHULUAN

Sejak virus covid -19 masuk ke Indonesia pada bulan maret 2020 pemerintah membuat berbagai kebijakan dalam setiap bidang agar menekan angka penyebaran virus tersebut karena dinilai sangat berbahaya dan berdampak pada banyaknya angka kematian. 2020 Tentang pedoman pembelajaran tatap muka di masa adaptasi kebiasaan baru pandemi coronavirus disease [1], Sekolah melakukan pembelajaran tatap muka terbatas 30 % dari jumlah kelas keseluruhan setiap harinya sehingga melakukan pembelajaran daring dengan metode campuran daring dan tatap muka, namun tidak sepenuhnya berjalan dengan efektif karena pada sebagian wali kelas dan guru mata pelajaran mengeluhkan tentang siswa hanya belajar saat tatap muka saja sedangkan pada saat pembelajaran daring siswa tidak hadir dan tidak mengerjakan tugas. Untuk memecahkan masalah tersebut perlunya pengklasteran terhadap kelas-kelas yang dinilai rentan terhadap keberlangsungan proses kegiatan belajar, hal ini agar memberikan manfaat berupa pilihan alternatif kepada sekolah untuk memaksimalkan proses pembelajaran pada siswa. Hasil dari penelitian ini adalah sebuah sistem yang mampu melakukan pengelompokan dataset tsunami dengan menggunakan metode K-Medoids. Pada penelitian mempunyai manfaat untuk membantu pihak sekolah dan pemerintah sebagai data penunjang agar proses kegiatan belajar mengajar menjadi lebih maksimal meskipun dalam keadaan pandemi seperti ini

Menentukan banyaknya cluster
Algoritma K-Means Clustering
Tahap Pengolahan Data
Menentukan Data Objek
Data Objek
Clustering Berikut ini penempatan data objek ke cluster

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