Classification of Neighborhood Unit Cadres’ Satisfaction Levels with the Carik App Using the Naïve Bayes Method in Semper Barat Subdistrict - Frencis Matheos Sarimole; Sugiyono Sugiyono; Aditya Zakaria Hidayat; Wida Lestari (International Journal of Information Engineering and Science, 2026)
This study aims to classify the level of satisfaction of Dasawisma cadres with the Carik application in West Semper Village by utilizing the Naive Bayes method. Data was obtained through questionnaires, which were compiled based on three main aspects: ease of use, speed of access, and the usefulness of applications in supporting cadre tasks. After the data is collected, a pre-processing and labeling process is carried out, where the level of satisfaction of respondents is categorized into two classes, namely "satisfied" and "dissatisfied". The Naive Bayes algorithm is applied to predict satisfaction classes based on questionnaire answers. The results of the analysis show that the Naive Bayes method is able to perform classification with sufficient accuracy, so that it can be used as an evaluation tool and decision support in the development of the carik application. This method can also help the management understand user perceptions and improve the system based on objective and routine data in line with the needs of field cadres.