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All Journal Jurnal Ilmiah Raflesia Akuntansi JSE Journal of Science and Engineering
Nur Ilham, Muhammad Fauzan
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Earth & Planetary Sciences Economics, Econometrics & Finance Engineering Mechanical Engineering Transportation

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Probalibilitas Manfaat Mobil Listrik Di Indonesia Untuk Menurunkan Emisi Dengan Menggunakan Survey Tik Tok Heriyanto; Hadi Suprapto, Yuyun; Arbansyah; Nur Ilham, Muhammad Fauzan
Jurnal Ilmiah Raflesia Akuntansi Vol. 10 No. 2 (2024): Jurnal Ilmiah Raflesia Akuntansi
Publisher : Politeknik Raflesia Press

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Abstract

Tik Tok merupakan platform media sosial yang paling populer saat ini, Beberapa orang memberikan ulasan positif bahwa aplikasi Tik Tok membantu orang-orang di sektor bisnis. Analisis sentimen digunakan untuk menganalisis opini yang terdapat dalam ulasan yang ditulis oleh pengguna dengan mengelompokkan ulasan positif dan negatif. Teknik yang digunakan dalam penelitian ini menggunakan algoritma Naïve Bayes dan Support Vector Machine (SVM). Model Random Forest yang dioptimalkan mencapai akurasi sebesar 91%, dengan kinerja yang baik dalam mengklasifikasikan ulasan negatif, netral, dan positif. Word Cloud membantu mengidentifikasi kata-kata yang sering muncul dalam ulasan, memberikan wawasan tentang aspek-aspek yang menjadi perhatian khusus pengguna. Penelitian ini menunjukkan efektivitas teknologi analisis sentimen dalam memahami preferensi pengguna dan memberikan masukan yang berharga bagi pengembang untuk meningkatkan Jawaban Baik dari aplikasi Tiktok.
Development Of An IoT-Based Security System For Swiftlet Nests Using Esp32-Cam And Pir Sensor Arbansyah, Arbansyah; Maulidina, Gina; Nur Ilham, Muhammad Fauzan; Sumadi , Muhammad Taufiq
JSE Journal of Science and Engineering Vol. 4 No. 1 (2025): Journal of Science and Engineering
Publisher : LPPI Universitas Muhammadiyah Kalimantan Timur (UMKT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30650/jse.v4i1.4220

Abstract

This study focuses on developing an Internet of Things (IoT)-based security system for swiftlet nests using ESP32-CAM and Passive Infrared (PIR) Sensors. The goal is to address the challenges of securing swiftlet nests located in remote areas, which are prone to theft and hard to monitor manually. The system combines motion detection, image capturing, and notification delivery through Telegram when connected to the internet. If the internet connection is unavailable, captured images are stored on a microSD card as an alternative. The research methodology includes the design of both hardware and software, implementation, and system performance testing. Test results show that the PIR sensor effectively detects motion within a 1-5 meter range, and the ESP32-CAM can capture and send images to Telegram in under 10 seconds when the network is stable. The system also reliably stores images on the microSD card when offline. This research highlights the system's ability to improve the security of swiftlet nests efficiently, offering a practical solution for farmers to monitor their nests in real-time without being physically present. The system’s flexibility and reliability make it a valuable tool for enhancing the security of agricultural resources.
Co-Authors Arbansyah Arbansyah, Arbansyah Hadi Suprapto, Yuyun Heriyanto Maulidina, Gina Sumadi , Muhammad Taufiq