Abstract:
The objectives of this study were 1) to
develop a mobile application for identifying 10
dangerous creatures in the rainy season; and 2) to
evaluate user satisfaction with a mobile application for
classifying 10 pernicious animals in the rainy season.
The researcher used the analysis and design principles
using CRISP-DM to develop an image classification
model with Teachable Machine, and Android Studio
was employed to develop applications on mobile
devices. The tools used in this present study were
pictorial models of 10 poisonous animals and user
satisfaction questionnaires, while means and standard
deviations were reported. Here, the results show that
a mobile application for analyzing 10 venomous
species in the rainy season used a camera to scan into
the developed program. The system was able to
display the name of the animal type correctly.
According to overall satisfaction evaluation results
from 35 users of the image model of 10 poisonous
animals in the rainy season, the mean was 4.52 or in
the highest level.