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All Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA) INTECH - Informatika Dan Teknologi
Junjung Rahmat Santosa
Universitas Baturaja
Automotive Engineering Computer Science & IT Control & Systems Engineering

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Sistem Informasi Geografis Pemetaan Lokasi Kos – Kosan Di Wilayah Baturaja Junjung Rahmat Santosa; Rangga Apriwijaya; Wahyu alvikri; Ilham Ardiyansah; Pujianto
INTECH Vol. 6 No. 1 (2025): INTECH (Informatika Dan Teknologi)
Publisher : Informatics Study Program, Faculty of Engineering and Computers, Baturaja University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54895/intech.v6i1.2781

Abstract

Penelitian ini dilatar belakangi oleh terbatasnya informasi tentang lokasi kos-kosan di Baturaja, yang sering kali menyebabkan pelajar atau pekerja baru pindah ke wilayah tersebut kesulitan mendapatkan tempat kos yang sesuai dengan kebutuhan mereka. Tujuan dari penelitian ini adalah untuk merancang sebuah aplikasi Sistem Informasi Geografis (SIG) berbasis web untuk memetakan kos-kosan di sekitar wilayah Baturaja, sehingga memudahkan pengguna, terutama pelajar, dalam mencari kos-kos yang sesuai dengan preferensi seperti harga, fasilitas, dan jarak dari tempat kuliah atau kerja. Sistem ini dirancang untuk menyediakan informasi yang lengkap dan interaktif tentang lokasi kos, mencakup harga, fasilitas, kontak pemilik, serta ukuran kamar. Dengan memanfaatkan Sistem Informasi Geografis (SIG), sistem ini diharapkan dapat menjadi solusi efektif dalam mempermudah pencarian kos di Baturaja.
Public Sentiment Analysis on the Issuance of Panda Bonds as an Effort for Rupiah Stability using SVM Algorithm on Youtube Social Media Junjung Rahmat Santosa; Rangga Apriwijaya; Ilham Ardiasyah; Rangga Apriansyah; Destiarini
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2350

Abstract

The stability of the Rupiah exchange rate is a crucial indicator of Indonesia's economic health, one of which is pursued through the issuance of Panda Bonds. However, this policy has triggered dynamic discourse on social media, particularly YouTube. This study aims to map public perception and test the performance of the Support Vector Machine (SVM) algorithm in classifying sentiments related to this issue. The research methodology includes scraping YouTube comment data, text preprocessing, automated labeling using the Lexicon-based method, and classification using SVM with a Linear kernel. From a total of 659 collected data, the results show that public sentiment is dominated by positive responses at 51.9%, followed by neutral sentiment at 29.0%, and negative sentiment at 19.1%. While public concerns focus on the debt burden and foreign currency dependence, there is overall support for economic stability efforts. The model evaluation demonstrates excellent performance, achieving an accuracy rate of 87.86%, precision of 88.79%, and an F1-score of 87.96%. This proves that a hybrid approach between Lexicon-based and SVM is effective in analyzing complex public opinions within the economic domain on social media.
Co-Authors Destiarini Destiarini Ilham Ardiasyah Ilham Ardiyansah Pujianto Rangga Apriansyah Rangga Apriwijaya Rangga Apriwijaya Wahyu alvikri