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All Journal INTI Nusa Mandiri Jurnal Komputasi
Agus Sofwan
INSTITUT SAINS DAN TEKNOLOGI NASIONAL
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Evaluasi Crossover pada Systematic Random Sampling Sebagai Optimasi Quick Count Agus Sofwan; Riadi Marta Dinata; Kun Wardana; Ariman Ariman; Baskoro Abie P
Jurnal Komputasi Vol. 13 No. 1 (2025)
Publisher : Jurusan Ilmu Komputer Fakultas MIPA Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/komputasi.v13i1.277

Abstract

Proses hitung cepat hasil pemilu atau Quick Count memerlukan metode komputasi yang tepat agar menghasilkan prediksi yang mendekati nilai aktualnya dengan biaya murah dan waktu hitung yang cepat.Dimulai dengan teknik penentuan jumlah responden (suara pemilih), berikut list Tempat Pemungutan Suara (TPS) mana saja yang harus di tempati relawan quick-count. Data sampling didapat dari web Hasil Hitung Suara Pemilu Presiden & Wakil Presiden RI 2019 Propinsi Lampung. Dan penggunaan metode optimasi pada Systematic Random Sampling (SYS) menghasilkan nilai akurasi yang lebih baik. Puncak efektif dan efisiensi suatu proses Quick Count berada pada nilai Kepercayaan 99%, Margin of Error 0.01%, dengan jumlah TPS dipilih 0.21% dari populasi. Dan metode evaluasi menggunakan Systematic Sampling memberikan hasil rata-rata yang lebih mendekati nilai aktual rerata 3% daripada Metode SYS yang tanpa evaluasi
PENGEMBANGAN SISTEM ROBOT PENJELAJAH BERBASIS MQTT MITIGASI BENCANA DENGAN DUKUNGAN IMAGE PROCESSING Riadi Marta Dinata; Muhammad Ikrar Yamin; Agus Sofwan; Ariman Ariman; Niko Purnomo Niko
INTI Nusa Mandiri Vol. 20 No. 1 (2025): INTI Periode Agustus 2025
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v20i1.7047

Abstract

Disaster mitigation is a global challenge that requires innovation to enhance the effectiveness of emergency response, particularly in the rapid and safe detection of victims. Although much research focuses on optimizing individual components such as sensors or algorithms, a gap remains in the development of holistically integrated frameworks. This study develops and evaluates an integrated explorer robot system based on Message Queuing Telemetry Transport (MQTT) and artificial intelligence for real-time disaster victim detection. Using a Design Science Research approach, the system architecture integrates an explorer robot based on ESP32-CAM and GPS for data acquisition, a central server running the You Only Look Once (YOLO) algorithm for image analysis, and involves a human operator for critical decision validation. Experimental results show that the system can detect victims with an average accuracy of 87.3% across various simulated scenarios. Communication via the MQTT protocol proved to be highly reliable and efficient, with an average latency of 127 ms and a packet loss rate of only 2.3%, enabling swift coordination between components. This research successfully validates an effective and replicable end-to-end architectural model, thereby presenting a practical blueprint for the development of low-cost Search and Rescue (SAR) robotic systems
Co-Authors Ariman Ariman Baskoro Abie P Kun Wardana Muhammad Ikrar Yamin Niko Purnomo Niko Riadi Marta Dinata Riadi Marta Dinata