KLASIFIKASI DATA KELUARGA SEJAHTERA MENGGUNAKAN METODE NAIVE BAYES ( STUDI KASUS KANTOR PERWAKILAN BADAN KEPENDUDUKAN DAN KELUARGA BERENCANA NASIONAL PROVINSI SULAWESI TENGAH )

ANDI AHMAD HAKIKI ALAM (2023) KLASIFIKASI DATA KELUARGA SEJAHTERA MENGGUNAKAN METODE NAIVE BAYES ( STUDI KASUS KANTOR PERWAKILAN BADAN KEPENDUDUKAN DAN KELUARGA BERENCANA NASIONAL PROVINSI SULAWESI TENGAH ). Undergraduate Theses thesis, Universitas Tadulako.

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Abstract

Simultaneous family data collection is routinely carried out by the BKKBN every five years throughout Indonesia. In family data collection there are several indicators, one of which is an indicator that can determine the status of family welfare in an area, but the data processing carried out by the central government lasts for a long period of time, thus hampering local governments in seeking to increase prosperous families, with this and as an effort to assist local governments in seeking to improve the quality of family welfare, a website-based application for classification of prosperous families was made. The application of the method used in building the system is a classification method using the nave Bayes algorithm which can classify data based on the probability of data appearing by predicting future opportunities based on past experience. This application design process uses UML design, Visual Studio Code as developer software, and Mysql as a database. With this application, it is hoped that it can be a solution in helping local governments in efforts to increase the level of family welfare and can facilitate the government in terms of databases in order to realize the central government's goal of realizing one data for one Indonesian family. Keywords : Classification, Naïve Bayes, UML, Visual Studio Code, Mysql.

Item Type: Thesis (Undergraduate Theses)
Subjects: University Structure > Faculty of Engineering > Informatics Engineering
S1 - Undergraduate Thesis > Faculty of Engineering > Informatics Engineering
Divisions: Faculty of Engineering > Informatics Engineering
Tadulako Subject Areas > S1 - Undergraduate Thesis > Faculty of Engineering > Informatics Engineering
Depositing User: system estd estd
Date Deposited: 02 Feb 2023 07:03
Last Modified: 02 Feb 2023 06:35
URI: http://repository.untad.ac.id/id/eprint/14601

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