Karyawan dituntut memiliki etos kerja yang baik untuk memajukan perusahaan. Hal ini menyebabkan banyak perusahaan memotivasi karyawannya dengan berbagai cara. Tujuan umumnya agar kinerja karyawan lebih baik dan stabil sehingga menguntungkan perusahaan. Imbalan diberikan kepada karyawan yang berprestasi dan mampu mencapai target tertentu, hal ini lebih efektif dalam memotivasi karyawan daripada hukuman sehingga dapat menjadi sumber motivasi bagi karyawan untuk bekerja secara maksimal. Dalam memberikan reward terkadang karyawan tidak sesuai dengan hasil kinerjanya dan tanpa menerapkan perhitungan yang baik. Untuk itu diperlukan suatu sistem rekomendasi untuk mendukung penilaian kinerja karyawan untuk mendapatkan reward. Salah satu metode yang digunakan adalah metode Adaptive Neuro Fuzzy Inference System (ANFIS). Metode ini dipilih karena mampu melengkapi penilaian kinerja karyawan berdasarkan kriteria yang telah ditentukan dan digunakan sebagai acuan dalam pemberian reward. Jumlah data yang diperoleh dan akan digunakan adalah sejumlah 537 data pegawai yang akan dibagi menjadi dua yaitu data latih yang berfungsi sebagai model sebanyak 524 data dan data uji yang berfungsi untuk menguji sistem sebanyak 13 data dan diperoleh Nilai perhitungan validasi model sebesar 0.867189 atau 87%
Employees are required to have a good work ethic in order to advance their company. This causes many companies to motivate their employees in various ways. The general goal is for better and more stable employee performance so that it benefits the company. Rewards are given to employees who excel and are able to achieve certain targets, this is more effective in motivating employees than punishment so that it can be a source of motivation for employees to work optimally. In giving rewards, sometimes employees do not match the results of their performance and without applying good calculations. For that we need a recommendation system to support employee performance appraisal to get rewards. One of the methods used is the Adaptive Neuro Fuzzy Inference System (ANFIS) method. This method was chosen because it is able to complete employee performance appraisals based on predetermined criteria and is used as a reference in giving rewards. The amount of data obtained and will be used is a number of 537 employee data which will be divided into two data, namely training data which functions as a model of 524 data and test data which functions to test the system of 13 data. The training set uses a regression algorithm to form an employee performance appraisal model. This model is a representation of knowledge that will be used to predict the reward status of operator and foreman level employees
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