DA SILVA, Nathalina. (2024) Pengembangan Aplikasi Prediksi Jumlah Penduduk Di Kecamatan Tasifeto Barat. Undergraduate thesis, Universitas Katolik Widya Mandira Kupang.
Text
ABSTRAK.pdf Download (521kB) |
|
Text
BAB I.pdf Download (171kB) |
|
Text
BAB II.pdf Restricted to Repository staff only Download (292kB) |
|
Text
BAB III.pdf Restricted to Repository staff only Download (1MB) |
|
Text
BAB IV.pdf Restricted to Repository staff only Download (1MB) |
|
Text
BAB V.pdf Restricted to Repository staff only Download (103kB) |
|
Text
BAB VI.pdf Download (23kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (196kB) |
Abstract
Population growth is a critical factor in regional development planning. In Tasifeto Barat District, information on population growth predictions is essential to support effective decision-making in development planning and public services. However, to date, Tasifeto Barat District still faces limitations in obtaining accurate and easily accessible population prediction data. The lack of effective tools for predicting population growth can lead to suboptimal development planning and misdirected public services.This study aims to address this issue by developing a population growth prediction application for use by relevant stakeholders in Tasifeto Barat District. The proposed solution in this study is the creation of a web-based application utilizing linear regression and single exponential smoothing methods. In the linear regression method, the equation y = ax + b is used, where the values obtained for predicting the population are a = 218,345.4167 and b = 1,288.85. For predicting migration numbers, the values are a = 1,599.472 and b = 234.150. The results of this study show that the developed application is capable of providing population growth predictions for the next 4 years in Tasifeto Barat District using the linear regression method with a MAPE of 0.04%, and migration predictions for the same period with a MAPE of 1.23%. Additionally, the application also uses single exponential smoothing with the smallest error at alpha 0.9, yielding a MAPE of 0.06% for population predictions and a MAPE of 1.38% for migration predictions. The obtained MAPE values indicate a very high level of accuracy. This application is integrated into a user-friendly web-based platform accessible to the local government with ease.
Item Type: | Thesis (Undergraduate) |
---|---|
Uncontrolled Keywords: | Prediction, Population Linear Regression, Single Exponential Smoothing, Tasifeto Barat District. |
Subjects: | H Social Sciences > HA Statistics J Political Science > JS Local government Municipal government Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
Divisions: | Fakultas Teknik > Program Studi Ilmu Komputer |
Depositing User: | Nathalina Da Silva |
Date Deposited: | 31 Oct 2024 03:18 |
Last Modified: | 31 Oct 2024 03:18 |
URI: | http://repository.unwira.ac.id/id/eprint/17762 |
Actions (login required)
View Item |