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Journal : Infotech: Journal of Technology Information

FAKTOR-FAKTOR YANG MEMPENGARUHI MINAT CALON MAHASISWA BARU MENDAFTAR PADA FTII UHAMKA MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR (K-NN) Rahman Malik, Luqman Abdur; Kamayani, Mia; Hasan, Firman Noor
Infotech: Journal of Technology Information Vol 9, No 1 (2023): JUNI
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v9i1.163

Abstract

In accepting new students at Prof. University. Dr. Hamka, many prospective students or parents of students are looking for registration information, this is a great opportunity for Uhamka to gain the sympathy of prospective students to register at Uhamka, especially the Faculty of Industrial and Informatics Technology. The problem in this study is that there is no data processing related to the factors that influence the interest of prospective new students to choose the Faculty of Industrial and Informatics Technology (FTII) Uhamka. The purpose of this study was to determine the factors that influence the interest of prospective new students in choosing majors at the Faculty of Industrial and Information Technology (FTII) Uhamka. The attributes used in this study were 10 attributes, namely full name, major, tuition fee, FII location with domicile, presence of friends/family, accreditation, facilities, PMB services, PMB information, and information of interest. The method that researchers use in this study is the K-Nearest Neighbor Algorithm (K-NN). From the results of testing the researchers used the K-5 fold technique and the confusion matrix obtained an average accuracy of 72.5%, which means it is good.
ANALISIS SENTIMEN TERHADAP MINAT MASYARAKAT JAKARTA YANG MEMILIH KENDARAAN UMUM MENGGUNAKAN ALGORITMA NAÏVE BAYES Dewanto, Yogga Tolly; Wiranata, Ade Davy; Sulaeman, Mia Kamayani
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.407

Abstract

The worsening traffic congestion in Jakarta highlights the need to understand public interest in using public transportation. Social media platforms such as X serve as valuable sources of real-time public opinion data. This study aims to analyze the sentiments of Jakarta residents toward public transportation to identify the factors influencing their interest in using it. Data was collected from X and analyzed using the Naïve Bayes algorithm through the RapidMiner application. The analysis was conducted by splitting the dataset into 60% training data and 40% testing data. The results of the study show 203 positive sentiment data, 135 negative sentiment data, and 138 neutral sentiment data. Positive sentiments were mostly associated with affordability and ease of access, while negative sentiments were related to discomfort and lack of punctuality. This research is expected to serve as a reference for policymakers in improving the quality of public transportation services in Jakarta.