Sumber Daya Manusia merupakan aset penting pada perusahaan untuk dapat mencapai tujuan perusahaan, Pemilihan karyawan terbaik merupakan suatu cara yang dilakukan perusahaan untuk memotivasi kinerja karyawan. Pimpinan perusahaan biasanya mendapat kesulitan dalam mengevaluasi kinerja karyawan dengan berbagai indikator penilaian yang ada. Hal ini menyebabkan hasil keputusan yang tidak objektif, untuk dapat mengolah data pemilihan karyawan terbaik yang lebih akurat hasilnya dan lebih objektif. Maka dibutuhkan Sistem Pendukung Keputusan dalam pemilihan karyawan terbaik. Dalam penelitian ini ada 25 Alternatif Karyawan yang telah memenuhi persyaratan pemilihan karyawan terbaik yang diolah menggunakan metode Simple Additive Weighting dan berdasarkan 5 kriteria penilaian yaitu kriteria loyalitas, tanggung jawab, perilaku/etika, kerjasama, dan kehadiran. Dari hasil perhitungan terhadap metode SAW ini diperoleh rangking 10 besar dan diperoleh juga bahwa Loyalitas kerja karyawan sangat berpengaruh terhadap hasil perhitungan dengan bobot 30% dari bobot keseluruhan.

Campus Youth Minimarket is one type of business in the field of selling daily necessities. For decision making in determining the amount of product inventory that can be adjusted to market demand, the Campus Youth Minimarket has not used the system and is still calculated manually. Therefore, this research was conducted with the aim of implementing the K-means Clustering method in grouping sales data at the Bengkulu Campus Youth minimarket. So that it can easily determine and classify high, medium and low product sales. The implementation of the system uses the PHP programming language and MySQL database and the method used in this research is the waterfall method. After the K-means process was carried out at the Campus Youth Minimarket with 15 data data tests, 3 clusters of goods were obtained, namely cluster 1 as a high sales cluster with 7 items, cluster 2 with moderate sales of 4 items and 4 items in a low sales cluster. Based on the results of processing 278 data on sales of goods in December 2021 at the Campus Youth Minimarket using the K-Means Clustering Method, the results of the grouping of product sales levels at the Bengkulu Campus Youth Minimarket were 3 clusters. Namely cluster 1 group with a high level of product sales with a total of 54 product data, cluster 2 with a moderate level of product sales with 165 types of products and cluster 3 with a low level of product sales with 51 total products. Based on the data cluster, it can be used as a reference by the Campus Youth Minimarket for the following month's product inventory. Which product clusters that have a high level of sales have a high or stable number of orders as before. Then product clusters with low sales levels, then the amount of product inventory for the next is reduced so that there is no accumulation of products in the warehouse and experiencing expiration.

Abstract—The necessities of life force people to work to fulfill their daily lives. In general, humans work during the day and rest at night. A lot of time spent working requires humans to rest to recover their physical condition. Sleep is an important phase in daily activities that is useful for balancing human life. Everyone's sleep needs are different. Many people are long-sleepers who need 9 to 10 hours of sleep a night while others are short-sleepers who only need less than 6 hours of sleep each night. Long sleep is not always associated with sleep disturbances. Besides that most people are not medically trained, therefore the authors intend to design an "expert system for diagnosing sleep disorders using the web-based forward chaining method" which can be accessed via http://puskesmastelagadewa.com/. This application is expected to be used by the community in early diagnosis as a prevention of more severe disease. This system is designed using the PHP programming language and MySQL database, the resulting expert system is able to help patients diagnose sleep disorders while providing solutions to the disease. From the test results, it is obtained that 100% functionality runs according to system requirements. In the system testing carried out at the Telaga Dewa Health Center UPTD, Bengkulu City, symptoms and diseases were obtained from 7 existing sample data.