Clustering is a process of sorting out a data set to become separate cluster groups and each has similarities, and aims to group the data into one cluster. This research aims to group the book information which is contained in Universitas Prima Indonesia, by using K-means clustering method. On this K-means clustering algorithm, the variables used as input are : NIM, Name, Book Title and Author. The output produced consists of 3 clusters, those are (C1) the most frequently borrowed book, (C2) book that is often borrowed, and (C3) book that is rarely borrowed. With the use of this K-means Clustering method, the final result obtained consists of member of cluster 1 as many as 19 members, member of cluster 2 as many as 22 members, and member of cluster 3 as many as 19 members. The information of grouping this book data can be used by the library. In the case of the selection of books that must be added to the library and to minimize the books that are rarely borrowed so as not to cause a buildup of books that are rarely borrowed, so there is a space for books to be added into the library.
Employees are one of the resources used as a means of movement in promoting a company. Employee performance is highly influential on the profits obtained by the company. Therefore, to stimulate employee performance in selecting outstanding employees each period by providing additional bonuses or salaries for selected employees. However, because the process of evaluating and selecting outstanding employees carried out by managers of Human Resource Development (HRD) still uses a conventional system and takes a lot of time, so a decision support system is needed to evaluate the performance of HRD managers to be more effective and efficient while saving time and energy compared to the current system. For this reason, the author proposes a decision support system and was used to determine outstanding employee by using the simple multi-attribute rating technique (SMART) method. The Decision Support System Application applies the SMART method to help decision maker to determinate the outstanding employee and based on the table above, it was concluded that the employee recommended as an outstanding employee is employee C with the highest final score of 66.20.
Ilmu tajwid merupakan ilmu yang digunakan untuk mengetahui cara mengucapkan kalimat-kalimat Al-Qur’an agar tidak salah dalam membacanya. Melalui penerapan ilmu tajwid tentang hukum bacaan nun mati/tanwin dan mim mati dalam ayat-ayat pilihan dapat menanamkan kesadaran berperilaku sesuai dengan aturan dalam kehidupan. Penelitian ini bertujuan untuk mengkaji sejauh mana sistem pendekatan tutorial sebaya dapat meningkatkan motivasi, aktivitas, serta hasil belajar siswa pada materi pembelajaran ilmu tajwid pada siswa kelas X-MIPA 9 SMAN 1 Matauli Pandan sebanyak 28 orang. Proses pengkajian Penelitian Tindakan Kelas (PTK) dilakukan melalui 4 tahapan yaitu: planning/perencanaaan, action/pelaksanaaan, observasi/ pengamatan dan refleksi. Hasil analisis data menunjukkan persentase peningkatan nilai rata-rata hasil tes formatif yang dilakukan melalui 3 siklus, yaitu pada siklus I sebesar 56,56%, pada siklus II sebesar 75,08% dan pada siklus III mencapai 85,16%. Tingkat ketuntasan belajar secara klasikal juga mengalami peningkatan yang signifikan, yaitu pada siklus I sebesar 28%, pada siklus II sebesar 56% dan pada siklus III mencapai 88%. Hai ini menunjukkan bahwa metode tutor sebaya mampu meningkatkan motivasi dan hasil belajar siswa pada materi pembelajaran ilmu tajwid.
The times change a lot of things, one of them human needs such as shoes. Along with the development of modern life, shoes are an irreplaceable part to maintain one's appearance. So it is very important for companies to provide various types of shoes with certain advantages needed by the community so they can compete with other shoe products. For that reason, the writer tries to make it easier for the seller to make the best shoe recommendations more effectively and efficiently so that they can better utilize the available data to be processed into the recommendations. And the usual manual method is done by looking at the previous shoe data and less considering other criteria with the existence of this support system the results of the recommendations are more accurate and precise. Therefore the researchers made a decision support application using the Simple Additive Weighting (SAW) method, based on web with Dreamweaver Editor application and MySQL database. With the hope that this application will make it easier for the seller to determine the best shoes.
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