Abstrak: FIF adalah salah satu Lembaga keuangan yang menyediakan berbagai macam alternatif pinjaman uang bagi nasabah. Sejatinya dalam pemberian kredit kepada nasabah pihak Lembaga keuangan mengalami berbagai masalah atau resikko. Salah satu masalah atau resiko yang dialami Lembaga Keuangan dalam pemberian kredit adalah perilaku nasabh yang macet dalam pembayaran kredit yang pada akhirnya menyebabkan kredit macet. Hal ini merupakan masalah yang serius yang perlu diperhatikan oleh pihak penyedia layanan keuangan untuk lebih berhati-hati dalam menentukan nasabah karena dalam pemberian kredit sangat beresiko khusuusnya pada PT FIF Goup Cabang Arjawinangun. Teknik Pengambilan data yang digunakan dalam pembuatan tugas akhir ini adalah dengan menggunakan observasi, wawancara, studi dokumentasi, dan data nasabah PT FIF Goup Cabang Arjawinangun. Sementara itu Teknik pengolahan data menggunakan prinsip tahapan knowledge discovery in database (KDD) yang terdiri dari data, Data Cleaning, Data Information, Data mining, Patternevalution, knowledge. Sementara itu atribut yang digunakan adalah dari nomort NIK, Kelancaran, Prediksi, Confident macet, confident lancer asset, dan omset perbulan dari nasabah. Metode K-NN dengan jumlah dataset sebanyak 296 data menghasilkan nilai akurasi sebesar 71%.   Kata kunci: Kredit, K-Nearest Neighbor (KNN), Prediksi.   Abstract: FIF is a financial institution that provides various kinds of money loan alternatives for customers, one of which is through the provision of loans in the form of credit to customers. In fact, in providing credit to customers, financial institutions experience various problems or risks. One of the problems or risks experienced by financial institutions In the provision of credit is the behavior of customers who are bad in credit payments which ultimately causes bad credit. This is a serious problem that financial service providers need to pay attention to to be more careful in determining customers because in providing credit is very risky, especially at PT FIF Goup Cabang Arjawinangun The data collection technique used in the making of this final project is to use observation, interviews, study documentation, and customer data of PT FIF Goup Cabang Arjawinangun Meanwhile, data processing techniques use the principles of knowledge discovery in databases (KDD) stages consisting of data, data cleaning, data transformation, data mining, pattern evolution, knowledge. Meanwhile, the attributes used are the NIK number, fluency, prediction, bad confidence, smooth confidence, assets, and turnover per month from customers. The K-NN method with a total dataset of 296 data yields an accuracy value of 71%.   Keywords: Credit, K-Nearest Neighbor (KNN), Prediction.

The development of information and technology is a development that can be felt in everyday life, almost all activities already use digital. The problem in the barbershop business is the length of the queue which causes customers to feel bored or there are also busy customers. Therefore, technology is needed in the barbershop business. Based on these problems, it can be concluded that there is a need to build an android-based ordering application. The purpose of this research is to increase productivity, creativity, revenue and customer satisfaction. This study uses the stages of the Waterfall method. The Waterfall method is used as a reference in the process of making the online ordering application. The results of this study are an android-based online ordering application, this application is enough to help customers so they don't have to bother waiting in line at the barbershop because customers can set schedules on the application, especially during a pandemic like today. This application displays information about available time slots and those that have been booked by other customers so that customers can adjust their free time. The barbershop also does not need to register customers who place orders manually. This online booking application has passed trials with white box testing and black box testing methods. The result is that all the components contained in this online booking application system work as expected.