Saragih, “The effect of mining data k-means clustering toward students profile model drop out potential,” J. Kitagawa, “A Study of LoRa Performance in Monitoring of Patient’s SPO2 and Heart Rate based IoT,” Int. Niswar et al., “Performance evaluation of ZigBee-based wireless sensor network for monitoring patients’ pulse status,” in Proceedings - 2013 International Conference on Information Technology and Electrical Engineering: “Intelligent and Green Technologies for Sustainable Development”, ICITEE 2013, 2013. Kitagawa, “ZigBee Radio Frequency (RF) performance on Raspberry Pi 3 for Internet of Things (IoT) based blood pressure sensors monitoring,” Int. Siregar, “Perancangan Sistem Informasi Berbasis E-Commerce Untuk Peningkatan Penjualan Produk Jersey Olah Raga,” J.
Siregar, “Sistem Informasi Pembelian Dan Penjualan Pakaian Pada Galoenk Distro Pematangsiantar,” JurTI (Jurnal Teknol. Purba, “Aplikasi Pencatatan Laporan Penjualan Kita-Kita.Net Berbasis Web,” TEKINKOM, vol. Siregar, “Perancangan Website Sebagai Media Promosi Dan Penjualan Produk,” TAM (Technology Accept. Kitagawa, “Quality of Service and power consumption optimization on the IEEE 802.15.4 pulse sensor node based on Internet of Things,” Int. Siregar, “PERANCANGAN SISTEM INFORMASI PENDATAAN BARANG PADA PT. Sihombing, “PERANCANGAN APLIKASI PENGOLAH DATA SISWA BERBASIS ANDROID (STUDI KASUS: MIS NURUL HUDA LABUHAN BATU SELATAN),” J. From the results of this data analysis, it can be seen that the book titles contained in cluster 3 are the most recommended books to be added to the Business Indonesia Polytechnic library In addition, books contained in cluster 3 have the fewest copies. From the lending data, the data contained in cluster 3 is the book group with the highest loan amount among the other 2 clusters. The final results obtained consisted of: members of cluster 1 consisting of 119 book titles, cluster2 of 8 books, and cluster3 of 21 books.
With the use of the K-means clustering method, the final results of the grouping are obtained up to the 6th iteration, where the center point no longer changes and no data moves between clusters.
The resulting output consists of 3 clusters, namely books that are borrowed most frequently, books that are borrowed frequently, and books that are rarely borrowed. In this K-means clustering algorithm, the variables used as input are: book id, book title, total loan and copies. Book grouping is done using the K-Means Clustering method. This study aims to classify the book information contained in the Business Indonesia Polytechnic library.
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