scholarly journals PENERAPAN DATA MINING DENGAN METODE INTERPOLASI UNTUK ESTIMASI PREMI BERDASARKAN PENDAPATAN NASABAH ASURANSI PRUDENTIAL DI YOGYAKARTA

Compiler ◽  
2012 ◽  
Vol 1 (2) ◽  
Author(s):  
Pandapotan Pandapotan ◽  
Anto Setiawan Honggowibowo ◽  
Dwi Nugraheny
Keyword(s):  
Data Mining ◽  
Test Results ◽  
Application System ◽  
Web Based ◽  
Insurance Benefits ◽  
Prudential Value

Premi in a definition can be interpreted as a fee to be paid by the customer, which is a combination of the overall cost of insurance benefits that used, and sometimes also include the amount of money invested by customers. The output of the data mining is a customers is accepted according to the prudential value of the estimated premi be gained from the number of customer revenue.Final project is, created a program of web-based application system to estimate the premi to make it easier for admin (prudential employee)  to determine the amount of premi to be paid by the customer. In this program, admin (prudential employee) just need to know the amount of customer’s income that the program will then process the results of the estimated premi.The test results is concluded that the program estimates the premi can be used easily by the admin (prudential employee) and simplify admin decisions premi estimate to the customer.

scholarly journals C5.0 Algorithm Implementation on Web-Based Software and Usability Evaluation

SISTEMASI ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 394
Author(s):  
Deny Jollyta
Keyword(s):  
Data Mining ◽  
Decision Makers ◽  
Classification Algorithms ◽  
Test Results ◽  
Classification Problems ◽  
Process Data ◽  
Web Based ◽  
Classification Technique ◽  
Software Classification ◽  
Algorithm Implementation

AbstrakPerangkat lunak merupakan alat bantu yang memudahkan pengguna dalam pengolahan data dengan cepat dan tepat. Para pengambil keputusan membutuhkan alternatif perangkat lunak yang dapat digunakan setiap saat dengan teknik klasifikasi data algoritma C5.0 sesuai kriteria yang diinginkan. Namun perangkat lunak yang ada umumnya terdiri dari sejumlah teknik dan belum dapat digunakan secara online. Sebagai salah satu algoritma klasifikasi yang popular dalam ilmu data mining, C5.0 dapat memberikan hasil yang lebih baik. Penelitian bertujuan untuk membangun perangkat lunak yang dapat melakukan klasifikasi data menggunakan algoritma C5.0 berbasis web. Perangkat lunak dapat digunakan oleh siapa saja, terutama para pengambil keputusan. Penelitian ini juga dilengkapi dengan pengujian perangkat lunak usability sebelum digunakan. Hasil pengujian memperlihatkan bahwa perangkat lunak yang dibangun dapat diterima dengan nilai usability 76,892% dan berada pada predikat Baik. Diharapkan melalui penelitian ini, dapat memberikan alternatif perangkat lunak yang mampu menyelesaikan masalah klasifikasi menggunakan algoritma C5.0.Kata kunci: perangkat lunak, klasifikasi, algoritma c5.0, usability AbstractSoftware is a tool that makes it easy for users to process data quickly and precisely. Decision makers need an alternative software that can be used at any time with the C5.0 algorithm data classification technique according to the desired criteria. However, the existing software generally consists of a number of techniques and cannot be used online. As one of the popular classification algorithms in data mining science, C5.0 can provide better results. This study aims to build software that can classify data using the web-based C5.0 algorithm. Software can be used by anyone, especially decision makers. This research is also complemented by testing Usability software before used. The test results showed that the software built can be accepted with a Usability value of 76.892% and is in the Good predicate. It is hoped that through this research, it can provide alternative software that is able to solve classification problems using the C5.0 algorithm.Keywords: software, classification, c5.0 algorithm, usability

Perancangan Aplikasi Prediksi Kelulusan Tepat Waktu Bagi Mahasiswa Baru Dengan Teknik Data Mining (Studi Kasus: Data Akademik Mahasiswa STMIK Dipanegara Makassar)

2015 ◽  
Vol 1 (4) ◽  
pp. 270
Author(s):  
Muhammad Syukri Mustafa ◽  
I. Wayan Simpen
Keyword(s):  
Data Mining ◽  
Nearest Neighbor ◽  
Test Results ◽  
K Nearest Neighbor ◽  
Accuracy Rate ◽  
Sample Data ◽  
New Students ◽  
K Nearest Neighbor Algorithm ◽  
Using Data ◽  
Existing Data

Penelitian ini dimaksudkan untuk melakukan prediksi terhadap kemungkian mahasiswa baru dapat menyelesaikan studi tepat waktu dengan menggunakan analisis data mining untuk menggali tumpukan histori data dengan menggunakan algoritma K-Nearest Neighbor (KNN). Aplikasi yang dihasilkan pada penelitian ini akan menggunakan berbagai atribut yang klasifikasikan dalam suatu data mining antara lain nilai ujian nasional (UN), asal sekolah/ daerah, jenis kelamin, pekerjaan dan penghasilan orang tua, jumlah bersaudara, dan lain-lain sehingga dengan menerapkan analysis KNN dapat dilakukan suatu prediksi berdasarkan kedekatan histori data yang ada dengan data yang baru, apakah mahasiswa tersebut berpeluang untuk menyelesaikan studi tepat waktu atau tidak. Dari hasil pengujian dengan menerapkan algoritma KNN dan menggunakan data sampel alumni tahun wisuda 2004 s.d. 2010 untuk kasus lama dan data alumni tahun wisuda 2011 untuk kasus baru diperoleh tingkat akurasi sebesar 83,36%.This research is intended to predict the possibility of new students time to complete studies using data mining analysis to explore the history stack data using K-Nearest Neighbor algorithm (KNN). Applications generated in this study will use a variety of attributes in a data mining classified among other Ujian Nasional scores (UN), the origin of the school / area, gender, occupation and income of parents, number of siblings, and others that by applying the analysis KNN can do a prediction based on historical proximity of existing data with new data, whether the student is likely to complete the study on time or not. From the test results by applying the KNN algorithm and uses sample data alumnus graduation year 2004 s.d 2010 for the case of a long and alumni data graduation year 2011 for new cases obtained accuracy rate of 83.36%.

Framework and performance analysis of college English testing system based on data mining technology

2021 ◽  
pp. 1-11
Author(s):  
Liu Narengerile ◽  
Li Di ◽  
Keyword(s):  
Data Mining ◽  
Test System ◽  
Test Time ◽  
Testing System ◽  
Test Results ◽  
System Software ◽  
Examination System ◽  
Mining Technology ◽  
College English ◽  
And Performance

At present, the college English testing system has become an indispensable system in many universities. However, the English test system is not highly humanized due to problems such as unreasonable framework structure. This paper combines data mining technology to build a college English test framework. The college English test system software based on data mining mainly realizes the computer program to automatically generate test papers, set the test time to automatically judge the test takers’ test results, and give out results on the spot. The test takers log in to complete the test through the test system software. The examination system software solves the functions of printing test papers, arranging invigilation classrooms, invigilating teachers, invigilating process, collecting test papers, scoring and analyzing test papers in traditional examinations. Finally, this paper analyzes the performance of this paper through experimental research. The research results show that the system constructed in this paper has certain practical effects.

scholarly journals Development of a Web-Based Query Tool for Quality Assurance of Clinical Molecular Genetic Test Results

2007 ◽  
Vol 9 (1) ◽  
pp. 95-98 ◽  
Author(s):  
Matthew J. McGinniss ◽  
Rebecca Chen ◽  
Victoria M. Pratt ◽  
Arlene Buller ◽  
Franklin Quan ◽  
...  
Keyword(s):  
Quality Assurance ◽  
Genetic Test ◽  
Molecular Genetic ◽  
Test Results ◽  
Web Based ◽  
Genetic Test Results ◽  
Query Tool ◽  
Molecular Genetic Test

Implementasi Metode Unsupervised Learning Pada Sistem Keamanan Dengan Optimalisasi Penyimpanan Kamera IP

2021 ◽  
Vol 5 (6) ◽  
pp. 1099-1105
Author(s):  
Desta Yolanda ◽  
Mohammad Hafiz Hersyah ◽  
Eno Marozi
Keyword(s):  
Unsupervised Learning ◽  
Night Vision ◽  
Raspberry Pi ◽  
Monitoring Systems ◽  
Test Results ◽  
Storage Process ◽  
File Size ◽  
Web Based ◽  
Security Monitoring ◽  
Human Faces

Security monitoring systems using face recognition can be applied to CCTV or IP cameras. This is intended to improve the security system and make it easier for users to track criminals is theft. The experiment was carried out by detecting human faces for 24 hours using different cameras, namely an HD camera that was active during the day and a Night Vision camera that was active at night. The application of Unsupervised Learning method with the concept of an image cluster, aims to distinguish the faces of known or unknown people according to the dataset built in the Raspberry Pi 4. The user interface media of this system is a web-based application built with Python Flask and Python MySQL. This application can be accessed using the domain provided by the IP Forwarding device which can be accessed anywhere. According to the test results on optimization of storage, the system is able to save files only when a face is detected with an average file size of ± 2.28 MB for 1x24 hours of streaming. So that this storage process becomes more efficient and economical compared to the storage process for CCTV or IP cameras in general.

Urgensi Autentikasi dan Legalisasi Arsip Pertanahan Hasil Digitalisasi

Tunas Agraria ◽  
2020 ◽  
Vol 3 (3) ◽  
Author(s):  
Farista Dewi Anindyati ◽  
Abdul Haris Farid ◽  
Dwi Wulan Titik Andari
Keyword(s):  
Qualitative Method ◽  
Application System ◽  
Web Based ◽  
Research Results ◽  
Descriptive Approach ◽  
Original File ◽  
Land Records

Land archive is the living archive of that must be fully maintained. As things goes, Sleman Land Office does digitalization archives to Gambar Ukur, Surat Ukur, Buku Tanah and Warkah by using a web-based application system which is called the Laris application. The research is aimed at finding out the reason why the office is doing digitalization with Laris application and finding out wheter this digitalized archive has been able to replace the original file in the form of paper. This research was conducted with a qualitative method with a descriptive approach Based on research results, obtained information that the digitalization of land records carried out in the Sleman’s Land office which has been done since year 2014 not solely done to change the format of analog files to digital files, but is expected to able provide more comprehensive benefits related to the acceleration of land services so that in practice it uses the Laris application.  However, the existence of this digitalized archive still not able to replace the position of analog archive in manner so that the analog archive is still maintained. Therefore, its important to authentication and legalization so the archive of digitalization result legally strong.

Sign in / Sign up

Export Citation Format

Share Document