Modified Regression Approach for Predicting Number of Dengue Fever Incidents in Malang Indonesia

Wiwik Anggraeni*, Rafika Nurmasari, Edwin Riksakomara, Febriliyan Samopa, Radityo Prasetyanto Wibowo, Lulus T. Condro, Pujiadi

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

12 Citations (Scopus)


This paper adopted regression approach with Least Square and Natural Logarithmic transformation in response variables to predict the number of Dengue fever attacks in Malang Regency, Indonesia. The prediction involved weather factors. 8 models were prepared, and it was found that the weather factor was the most influential. Some tests, including hypothesis test, were adopted to identify the significance of the model found. The model using response variable with logarithmic natural transformation resulted better model compared to the ones without transformation. It was also supported by the average MAPE of the model that was less than 10%. Therefore, it was identified that the regression approach will work well if both dependent and independent variables have relatively similar variances so that the variability of the dependent variables can be well explained by the independent variable.

Original languageEnglish
Pages (from-to)142-150
Number of pages9
JournalProcedia Computer Science
Publication statusPublished - 2017
Externally publishedYes
Event4th Information Systems International Conference 2017, ISICO 2017 - Bali, Indonesia
Duration: 6 Nov 20178 Nov 2017


  • Dengue Fever
  • Natural Logarithm
  • Ordinary Least Square
  • Prediction
  • Regression


Dive into the research topics of 'Modified Regression Approach for Predicting Number of Dengue Fever Incidents in Malang Indonesia'. Together they form a unique fingerprint.

Cite this