Analisi Prediksi Tingkat Kesejahteraan Masyarakat Nelayan Lombok Timur Dengan Algoritma Naïve Bayes
DOI:
https://doi.org/10.29408/jit.v7i2.26543Keywords:
Naive Bayes, Classification, Fisherman, PedictionAbstract
The water area in Indonesia is wider than the land area, therefore Indonesia is known as a maritime country. Indonesia also has many natural resources that come from the ocean, for example fish. Coastal communities use fish as their livelihood, where most of them become fishermen. Fishing is a daily job to meet the family's economic needs. The Fishermen's Community can be called a group of people who mostly work as fishermen. This group of people is different from people who live in lowland and highland areas, they have different characteristics, natural factors have changed their lifestyle and also their economy. It is because of the uniqueness of their lifestyle that makes the author interested in conducting research. This research uses existing data to obtain new information from that data. Researchers will predict the level of welfare of fishing communities in East Lombok using the Naive Bayes algorithm. To support the results of the decisions that will be evaluated, researchers use five variables, namely: Education, family members, wells, employment and housing. From these five variables, researchers hope to get good final results that can be used to predict the level of welfare of the fishing community in East Lombok. Evaluation is carried out using the Naive Bayes algorithm, this algorithm was chosen because it suits the characteristics of the data we have. Naive Bayes is a simple algorithm. The final results of this research were 99% for accuracy value, 81% for precision value and 100% for recall
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