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 need for information in the world of education in this modern era is very important in determining the progress of an institution. By implementing and utilizing information technology can facilitate school institutions in organizing data and will produce a database file that will make it easier for users to access data. However, the use of information technology at SDIT Ibnu Khaldun Cirebon has not been used optimally. This is where the author's desire to create a Smart School application emerged, which is an application that functions as an academic information application to support daily activities at the school.This study aims to improve the quality of schools and meet the needs of schools and parents in disseminating general school information, and student academic information at SDIT Ibnu Khaldun Cirebon.The method used in this research is the research and development method. Data collection techniques in this study using interviews. This research was conducted at SDIT Ibnu Khaldun by involving teachers, principals, students, and parents of students as research subjects.Based on the results of testing with the black box method on the Smart School application, it can be concluded that functionally it produces results that are in line with expectations
Monitoring data claim customer di PT. Dharma Electrindo Manufacturing Plant Cirebon merupakan kegiatan rutin untuk melaporkan claim dari customer berupa komplain produk melalui aplikasi Whatsaap bahwa produk yang dikirim ke customer telah terjadi kegagalan fungsi atau kesulitan penginstalan di unit kendaraan motor atau mobil. Proses monitoring claim customer dilakukan dengan mencatat data claim customer melalui buku catatan claim customer yang kemudian diinputkan melalui aplikasi ms. excel untuk dilaporkan kepada pimpinan sebagai bahan evaluasi perbaikan dan untuk disampaikan kepada karyawan bahwa telah terjadi kegagalan produk di customer. Kesulitan yang dihadapi oleh staff quality adalah mengelompokkan data claim customer dengan kriteria pengelompokkan data percustomer sehingga sulit untuk dijadikan bahan evaluasi perbaikannya dan data claim yang lampau lama untuk didapat. Solusi yang dapat dilakukan untuk mengatasi permasalahan tersebut yaitu dengan menerapkan sebuah sistem informasi berbasis website untuk memudahkan monitoring data claim customer berdasarkan kriteria pengelompokkan data percustomer dan data claim yang lampau mudah didapat. Metode pengembangan perangkat lunak yang digunakan untuk mengembangkan sistem informasi data claim customer adalah dengan menerapkan metode SDLC. Tahapannya adalah perencanaan, analisa, desain, pengujian dan perawatan. Hasil akhir penelitian di PT. Dharma Electrindo Manufacturing plant Cirebon ini menghasilkan sistem informasi berbasis web yang meningkatkan sebesar 82% untuk memudahkan sistem monitoring data claim customer.
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