Article Per Year (5 Year)
p-Index From 2020 - 2025
0.444
P-Index
This Author published in this journals
All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Innovative: Journal Of Social Science Research
Haliza, Dinda
Unknown Affiliation
Humanities Computer Science & IT Law, Crime, Criminology & Criminal Justice Public Health Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Sistem Monitoring Karyawan PT Telkom Akses Medan Menggunakan Teknologi GPS Haliza, Dinda; Mahfudza, Nurbaiti
Innovative: Journal Of Social Science Research Vol. 3 No. 6 (2023): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Teknologi berkembang semakin cepat, dan hampir semua layanan dirancang untuk memberi manfaat bagi kehidupan manusia. Seiring dengan kemajuan teknologi, semakin mudah untuk menemukan seseorang. Perkembangan ini memungkinkan untuk mengetahui keberadaan karyawan dengan tujuan untuk meningkatkan semangat kerja karyawan dan mencegah terjadinya ketidakjujuran di kalangan karyawan. Oleh karena itu, pada penelitian ini kami mengembangkan program yang memanfaatkan teknologi GPS untuk memantau langsung lokasi karyawan dan mendukung kinerja karyawan. Teknologi GPS memudahkan orang menemukan objek yang dicarinya dengan layanan Open StreetMaps yang dapat melihat lokasi tujuan dalam bentuk peta digital. Metode penelitian yang digunakan dalam penelitian ini adalah pengamatan, studi lieratur dan metode SDLC untuk mengembangkan sistem. Informasi yang ditampilkan dalam aplikasi ini diharapkan untuk membantu perusahaan memverifikasi lokasi karyawannya.
Sentiment Analysis on Public Perception of the Nusantara Capital on Social Media X Using Support Vector Machine (SVM) and K-Nearest Neighbor (K-NN) Methods Haliza, Dinda; Ikhsan, Muhammad
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9318

Abstract

The relocation and development of the National Capital City (IKN) as the center of government activities has become a hot topic, sparking diverse opinions among the public. The proposal to move the capital from DKI Jakarta to East Kalimantan has drawn significant attention from online communities, particularly on social media platform X (Twitter). This study aims to explore public sentiment regarding the development of IKN by applying artificial intelligence-based classification algorithms, namely Support Vector Machine (SVM) and K-Nearest Neighbor (K-NN). Sentiments are categorized as positive or negative to provide deeper insights into public perceptions. Through web crawling techniques, a total of 4,000 data points were collected. After the preprocessing stage, 3,608 data points remained, which were then translated into English to facilitate labeling using the Vader Sentiment method. The analysis results indicate that negative sentiment (1,873) is more dominant than positive sentiment (1,735). The data was then split into two sets: 80% for training (2,886 data points) and 20% for testing (722 data points). Based on the evaluation results, SVM and K-NN proved to be effective for sentiment analysis. SVM achieved an accuracy of 76%, precision of 78%, recall of 81%, and an f1-score of 79%, while K-NN attained an accuracy of 65%, precision of 62%, recall of 98%, and an f1-score of 76%. With superior performance, SVM emerges as a more reliable method for classifying public sentiment regarding the IKN development policy.
Co-Authors Mahfudza, Nurbaiti Muhammad Ikhsan