Handayani, Firin (2020) Peramalan Jumlah Kasus Demam Berdarah Di Kabupaten Malang Menggunakan Metode Random Forest. Other thesis, Institut Teknologi Sepuluh Nopember.
Preview |
Text
05211640000006-Undergraduate_Thesis.pdf Download (3MB) | Preview |
Abstract
Demam Berdarah Dengue (DBD) adalah suatu penyakit yang disebabkan oleh nyamuk jenis Aedes Aegypti yang sering terjadi di daerah tropis dan subtropis. Banyak faktor yang dapat memengaruhi perkembangbiakan nyamuk tersebut seperti perubahan suhu udara, kelembapan, curah hujan, mobilitas penduduk, kondisi lingkungan, genangan air, dan perilaku masyarakat yang tidak sehat. Salah satu faktor yang paling besar memengaruhi penularan Virus nyamuk Aedes Aegypti yaitu mobilitas penduduk. Penularan Virus nyamuk Aedes Aegypti akan semakin meningkat sebanding dengan tingkat perubahan kepadatan penduduk.
Penyakit DBD menjadi permasalahan yang sangat serius dalam bidang kesehatan karena dapat menyebabkan kematian. Berdasarkan World Health Organization (WHO), penyakit demam berdarah mengalami peningkatan setiap tahun. Penyakit ini banyak terjadi di negara Asia Tenggara. Selain itu, menurut WHO negara Indonesia termasuk ke dalam delapan negara di Asia yang mengalami peristiwa demam berdarah tertinggi. Jumlah KDBdi Indonesia cenderung mengalami peningkatan. Kejadian kasus DBD tertinggi berada di Kabupaten Malang, Jawa Timur. Oleh karena itu, perlu adanya suatu peramalan dimana hasil dari peramalan yang akurat dapat digunakan sebagai informasi untuk pihak Dinas Kesehatan Malang. Selain itu, proses perencanaan dan pencegahan dapat digunakan dalam menanggulangi jumlah KDB di masa mendatang.
Metode yang digunakan untuk meramalkan jumlah KDBpada penelitian ini yaitu metode Random Forest Regression. Metode ini dapat digunakan untuk data peramalan time series yang manghasilkan output numerik dengan melakukan berbagai proses pengolahan data.
Model terbaik yang dihasilkan di dataran rendah dan sedang memiliki nilai Root Mean Square Error sebesar 2.2568 dan 2.5964. Sedangkan model terbaik di dataran tinggi memilki nilai Root Mean Square Error paling kecil yaitu 1.3437.
=========================================================
Dengue Fever is a disease caused by Aedes Aegypti mosquitoes that often occur in tropical and subtropical regions. Many factors can influence the breeding of mosquitoes such as changes in temperature, humidity, rainfall, population mobility, environmental conditions, standing water, and unhealthy community behavior. One of the biggest factors influencing the transmission of the Aedes Aegypti mosquito Virus is population mobility. The transmission of the Aedes Aegypti mosquito Virus will increase in proportion to the rate of change in population density.
Dengue Fever becomes a very serious problem in the health field because it can cause death. Based on the World Health Organization (WHO), dengue fever has increased every year. This disease is common in Southeast Asian countries. Also, according to WHO, Indonesia is one of eight countries in Asia with the highest incidence of dengue. The number of dengue cases in Indonesia tends to increase. The highest incidence of Dengue Fever cases is in Malang Regency, East Java. Therefore, there needs to be a forecast where the results of accurate forecasting can be used as information for the Malang Health Office. Also, the planning and prevention process can be used in tackling the number of dengue cases in the future.
The method used to predict the number of dengue cases in this research is the Random Forest Regression method. This method can be used for time series forecasting data which generates numerical output by performing various data processing processes.
The best model produced in the lowlands and medium has a Root Mean Square Error value of 2.2568 and 2.5964. While the best model in the highlands has the smallest Root Mean Square Error value of 1.3437.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Demam Berdarah Dengue, Peramalan, Random Forest Regression, Root Mean Square Error, Dengue Fever, Forecasting, Random Forest Regression, Root Mean Square Error. |
| Subjects: | Q Science > QA Mathematics > QA76.9.D343 Data mining. Querying (Computer science) |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 57201-(S1) Undergraduate Thesis |
| Depositing User: | FIRIN HANDAYANI |
| Date Deposited: | 14 Aug 2020 08:36 |
| Last Modified: | 16 Jun 2023 07:47 |
| URI: | http://repository.its.ac.id/id/eprint/78182 |
Actions (login required)
 |
View Item |