The distribution of scholarships is carried out to assist in the determination of recommending someone who deserves to receive a scholarship, a Decision Support System is needed because the system for selecting scholarship candidates is still manual, and has many weaknesses. The large number of scholarship participant applicants makes schools having difficulty handling manual data processing so that software is needed to simplify the data processing. There for not all students who apply to receive scholarships can be granted, because the number of students who apply is very large, it is very necessary to build an SPK with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method which can help provide recommendation for scholarship recipients. Based on the analysis of the DSS with the TOPSIS method, it was carried out by means of a questionnaire, interview observation and system implementation. In the assessment of scholarship acceptance, it can be used as a basis for facilitating decisions on scholarship recipients because the system will process data and provide information quickly, precisely and consistently to the principal of students to receive the best scholarships to be awarded. Can form a decision that is right, effective and efficient in managing data on student recipients who are truly entitled to receive the scholarship. The TOPSIS method can be used to determine scholarship recipients, SPK in the assessment of scholarship acceptance can facilitate decisions in grade 7 students of SMP Negeri 17 Padang proportionally based on the results of student data processing including family cards, parents 'jobs, parents' income, number of dependents of parents and age parents accurately and accurately because the system can minimize errors in the process of calculating data normalization
Obat merupakan salah satu komponen tak tergantikan dalam pelayanan Kesehatan yang dapat membantu dalam mengobati masyarakat yang sakit. Perencanaan kebutuhan obat merupakan salah satu aspek penting dalam pengelolaan obat, karena berpengaruh pada pengadaan, peredaran dan penggunaan obat di unit pelayanan kesehatan. Perencanaan kebutuhan obat yang tepat akan menjadikan pengadaan efektif dan efisien sehingga sesuai dengan kebutuhan pelayanan kesehatan dengan kualitas yang terjamin dan dapat diperoleh pada saat dibutuhkan. Puskesmas merupakan salah satu pelayanan kesehatan yang dikelola di bawah Dinas Kesehatan Kabupaten dan Kota. Namun pada kenyataannya masih terdapat kendala dalam proses pengadaan obat di Puskesmas sehingga belum mencapai pelayanan prima terkait ketersediaan pelayanan obat. Clustering dalam Data Mining dapat digunakan untuk menganalisa pemakaian obat-obatan, perencanaan dan pengendalian obat-obatan di Puskesmas. Metode yang akan digunakan dalam penelitian ini adalah algoritma Fuzzy C-Means yang merupakan metode pembelajaran mesin tanpa pengawasan yang paling banyak digunakan dan relatif berhasil di antara banyak algoritma pengelompokan fuzzy. Tujuan dari penelitian ini adalah untuk mengelompokkan data obat-obatan yang dapat digunakan sebagai referensi dalam pengambilan keputusan dalam perencanaan dan pengendalian pasokan medis di puskesmas tersebut. Berdasarkan 501 record data LPLPO Bulanan Farmasi pada bulan Oktober 2020-Februari 2021, didapatkan hasil cluster satu sebanyak 179 jenis obat yang termasuk ke dalam tingkat pemakaian rendah, cluster 2 terdapat 18 jenis obat yang termasuk ke dalam tingkat pemakaian sedang dan cluster 3 sebanyak 4 jenis obat yang termasuk ke dalam tingkat pemakaian tinggi
Stroke is a disease caused by brain damage caused by disruption of the blood supply to the brain. At this time in general, people are still not very familiar with how this stroke disease or do not realize the symptoms that may have appeared from the start. People also tend to be hesitant to visit the hospital to check their symptoms and feel they are delaying further examinations. This is certainly a scourge that continues to make the number of strokes increase. In assisting the community in identifying stroke disease, an expert system is needed that is able to identify the type of stroke based on the symptoms felt. The data used in this study were obtained from Brain Hospital. Dr. Drs. M. Hatta Bukittinggi which was later developed into a website-based system using the PHP Framework Laravel programming language and MySQL as the database. The system is built based on the Naive Bayes method which is one of the Expert System methods that has a high accuracy value. The use of this system is expected to be able to provide knowledge to the public about the symptoms that might lead to what type of stroke the user might suffer, so that the user can use the results of the system as a reference to visit the hospital and immediately get more targeted help. This system can perform calculations that match the results of the doctor's diagnosis with an accuracy value of 100% in identifying the type of stroke from 10 data samples used.
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