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All Journal Dinamik Jurnal Teknologi dan Sistem Informasi
Temi Ardiansyah
Universitas Teknokrat Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Environmental Science Social Sciences

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SISTEM INFORMASI RESERVASI PELAYANAN DAN PENYEWAAN FASILITAS LAPANGAN FUTSAL BERBASIS WEB DENGAN METODE WATERFALL Dani Hidayatullah; Temi Ardiansyah; Styawati Styawati
Jurnal Teknologi dan Sistem Informasi Vol 3, No 3 (2022): Volume 3 No. 3 September 2022
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jtsi.v3i3.1994

Abstract

Pada penelitian ini bertujuan untuk mempermudah dalam memberikan informasi penjadwalan, proses penyewaan, dan membuat laporan keuangan. Manfaat penelitian ini dapat mengetahui transaksi pemesanan, laporan keuangan, informasi penjadwalan, serta pelayanan pada Bandar Lampung Sport Center. Untuk metode pengumpulan data menggunakan beberapa metode seperti obeservasi, wawancara, dan studi literature. Sedangkan metode untuk pengembangan sistemnya menggunakan metode waterfall. Lokasi penelitian di Jalan Jati, Tanjung Gading, Kec. Tanjung Karang Timur, Bandar Lampung, Lampung. Untuk hasil dari penelitian ini beruapa sebuah aplikasi berbasis web yang nantinya dapat mempermudah bagi pihak pelanggan maupun pengelola. Hasil dari pengujian yang dilakukan dengan metode Black Box, maka disimpulkan bahwa sistem informasi yang telah dibuat dapat berjalan dengan baik Kata Kunci: Penjadwalan, metode waterfall, aplikasi berbasis web, Black Box.
Analisis Sentimen Publik terhadap Personal Branding Dedi Mulyadi di Tiktok Perbandingan Metode Manual dan Data Mining Cyintia Bella; Temi Ardiansyah
Dinamik Vol 31 No 2 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i2.10524

Abstract

Social media, particularly TikTok, has become a strategic platform for politicians to build personal branding and shape public opinion. This study aims to analyze public sentiment toward Dedi Mulyadi’s personal branding on TikTok and to compare sentiment analysis results obtained through manual labeling and data mining methods using the Naïve Bayes algorithm. This research employs a quantitative descriptive–comparative approach. The dataset consists of 800 manually labeled comments and 3,226 comments collected through web scraping and automatically classified. The results show that sentiment analysis using the manual method produces positive sentiment as the dominant category, accounting for 55.4%, followed by neutral sentiment at 30.6% and negative sentiment at 14.0%. In contrast, the data mining–based sentiment analysis indicates neutral sentiment as the most dominant category at 45.66%, followed by negative sentiment at 28.51% and positive sentiment at 25.83%. These differences are influenced by data volume, labeling techniques, and the limitations of algorithms in interpreting informal language and implicit expressions. This study concludes that both manual and data mining approaches have distinct strengths and limitations; therefore, their combined use can provide a more comprehensive understanding of public sentiment toward political personal branding on social media.
Co-Authors Cyintia Bella Dani Hidayatullah Styawati Styawati