ANALISIS INVESTASI NASABAH BANK XYZ DENGAN NAIVE BAYES MELALUI ANTARMUKA APLIKASI SPREADSHEET

MUHTAR, DWIKY (2022) ANALISIS INVESTASI NASABAH BANK XYZ DENGAN NAIVE BAYES MELALUI ANTARMUKA APLIKASI SPREADSHEET. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

Investasi merupakan kegiatan menyimpan atau menanamkan dana atau modal pada periode tertentu dengan ekpetasi modal tersebut dapat tumbuh dan berkembang. Bank memiliki banyak produk investasi yang ditawarkan kepada nasabah dalam jangka panjang atau jangka pendek. Contoh bentuk dari produk investasi di bank seperti deposito, reksadana, obligasi, dan saham. Di era saat ini banyak nasabah seperti perusahaan ataupun masyarakat umum yang sudah mulai mengerti tentang ada nya investasi dan menempatkan dana nya melalui perusahaan sekuritas yang telah di regulasi oleh bank. Disisi lain dengan keterbatasan sumber daya manusia yang ada di bank, manajemen di tuntut untuk membuat target dalam mengelola keuangan nasabah dengan banyak nasabah yang ada. Berdasarkan permasalahan tersebut dengan pengelolaan data nasabah yang sangat besar dapat diatasi dengan data mining. Penelitian ini bertujuan untuk mengoptimasikan proses prediksi data nasabah menggunakan teknik klasifikasi. Algoritma yang digunakan untuk klasifikasi kelulusan adalah algoritma Naïve Bayes. Dengan menggunakan 1102 data proses untuk memprediksi nasabah yang berpotensi dalam menggambil simpanan investasi memperoleh nilai akurasi sebesar 0,77. Hasil ini dapat dimanfaatkan untuk PT Bank XYZ tumbuh berkembang dan mencapai target dalam mengelola nasabah. Kata Kunci: Klasifikasi, Naive Bayes, Data mining Investment is an activity to save or invest funds or capital for a certain period with the expectation that the capital can grow and develop. The bank has many investment products that are offered to customers in the long or short term. Examples of forms of investment products in banks such as deposits, mutual funds, bonds, and stocks. In the current era, many customers such as companies or the general public have begun to understand the existence of investments and place their funds through securities companies that have been regulated by banks. On the other hand, with limited human resources at the bank, management is required to set targets in managing customer finances with many existing customers. Based on these problems, the management of very large customer data can be overcome by data mining. This study aims to optimize the process of predicting customer data using classification techniques. The algorithm used for graduation classification is the Naïve Bayes algorithm. By using process data to predict customers who have the potential to take investment deposits, the accuracy value is 77%. These results can be used for PT Bank XYZ to grow and achieve targets in managing customers. Key Words: Classification, Naive Bayes, Data mining

Item Type: Thesis (S1)
Call Number CD: FIK/INFO. 22 014
NIM/NIDN Creators: 41517120125
Uncontrolled Keywords: Classification, Naive Bayes, Data mining
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000.01-000.09 Standard Subdivisions of Computer Science, Information and General Works/Subdivisi Standar Dari Ilmu Komputer, Informasi, dan Karya Umum
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: Dede Muksin Lubis
Date Deposited: 11 Jul 2022 02:20
Last Modified: 11 Jul 2022 02:20
URI: http://repository.mercubuana.ac.id/id/eprint/64875

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