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All Journal Jurnal Ilmu Manajemen Terapan (JIMT) Jurnal Manajemen dan Penelitian Akuntansi (JUMPA) International Journal of Applied Mathematics, Sciences, and Technology for National Defense
Prakosa, Setya Widyawan
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Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Physics Social Sciences

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Prototype smart integrated fire detection based on deep learning YOLO v8 and IoT (internet of things) to improve early fire detection Firdaus, Muhammad Azka; Dahlan, Iqbal Ahmad; Rimbawa, H A Danang; Versantariqh, Muhammad Azka; Prakosa, Setya Widyawan
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 2 No. 2 (2024): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v2i2.437

Abstract

The high incidence of fires in Indonesia in 2018-2023 is 5,336 fire incidents have caused many deaths and enormous material losses. This system is designed to identify early signs of fire through object detection and sensor technology, which is integrated with the Blynk IoT platform for real-time sensor monitoring and Telegram for instant notifications to users. The waterfall prototype method was designed through observation, system design, program code creation, tool testing, and tool implementation. This research uses Deep Learning YOLOv8 technology and IoT using ESP 32 as a microcontroller. Based on the training datasets, it produces precision=0.95872; recall=0.91; mAP50=0.97; mAP50-95 =0.66. The system uses the integration of a multisensor KY-026 flame sensor, DHT 22 temperature and humidity sensor, and MQ-2 sensors can detect CO, LPG, and smoke gas. All these multisensors can be monitored on Blynk IoT and Telegrambot in real time.
Unmanned aerial vehicle classification and detection system based on deep learning, internet of military things, and PID control system Lesmana, Azka Versantariqh; Dahlan, Iqbal Ahmad; Tjahjadi, Hendrana; Prakosa, Setya Widyawan; Firdaus, Muhammad Azka
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 2 No. 3 (2024): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def..v2i3.439

Abstract

Indonesia is an archipelagic country situated between two continents and two oceans. With numerous islands, it is rich in natural resources but faces various military and non-military threats. One significant threat to maritime nations like Indonesia is from the air, which includes direct attacks from manned and unmanned aircraft and using aerial vehicles for intelligence and surveillance. The primary weapon system is crucial for national defense against such threats. Therefore, developing defense equipment in Indonesia must align with technological advancements to ensure quick and efficient operation. This research focuses on creating a classification and reconnaissance system for flying vehicles to enhance air defense capabilities. In the surveillance system, two servos are used for yaw and pitch axes, controlled by a Proportional, Integrative, and Derivative (PID) system. This PID control significantly improves servo movement both dynamically and statically. The system sends notifications via Telegram for monitoring, with an average FPS of 9.6. Flask is used for the website interface, averaging 6.8 FPS, and MIT App Inventor is used for the smartphone interface, averaging 7.6 FPS. This flying vehicle classification and reconnaissance system enhances Indonesia's air defense, utilizing YOLOv8 for classification, PID control for servo movements, and integrated notifications and interfaces for both web and smartphones.
Peramalan Permintaan Ayam Segar Menggunakan Simulasi Monte Carlo untuk Pengelolaan Persediaan pada Restoran XYZ Maridelana, Vanya Pinkan; Noviasari, Tria Putri; Prakosa, Setya Widyawan
Jurnal Manajemen dan Penelitian Akuntansi (JUMPA) Vol 18 No 2 (2025): Juli-Desember
Publisher : Sekolah Tinggi Ilmu Ekonomi Cendekia Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58431/jumpa.v18i2.361

Abstract

ayam segar pada Restoran XYZ selama masa libur mahasiswa menggunakan simulasi Monte Carlo. Penurunan permintaan sebesar 40–50% selama periode libur menyebabkan tingginya risiko ketidaksesuaian antara stok dan kebutuhan aktual, sehingga diperlukan pendekatan prediksi yang mampu menangkap ketidakpastian permintaan bahan baku yang bersifat perishable. Data historis permintaan selama 60 hari digunakan untuk membangun distribusi probabilitas dan probabilitas kumulatif yang menjadi dasar pembangkitan bilangan acak melalui metode Linear Congruential Generator (LCG). Hasil simulasi menunjukkan bahwa rata-rata permintaan ayam segar sebesar 17.15 kg per hari, yang mengindikasikan tingkat akurasi model sebesar 100.41%. Nilai simpangan baku simulasi yang lebih tinggi (5.92) dibandingkan historis (4.97) menunjukkan peningkatan volatilitas permintaan yang perlu diantisipasi. Berdasarkan hasil ini, penelitian merekomendasikan penetapan stok harian sekitar 23.07 kg (rata-rata + SD) sebagai safety stock untuk meminimalkan risiko stock-out dan menjamin kelancaran operasi. Temuan ini membuktikan bahwa simulasi Monte Carlo merupakan pendekatan yang efektif, realistis, dan aplikatif dalam perencanaan persediaan restoran berbasis produk segar di tengah fluktuasi permintaan musiman.
Evaluasi Kualitas Layanan OTA dalam Perspektif Manajemen Operasi Jasa: Pendekatan Text Mining dan Sentiment Analysis pada Aplikasi Traveloka Maridelana, Vanya Pinkan; Prakosa, Setya Widyawan; Noviasari, Tria Putri
Jurnal Ilmu Manajemen Terapan Vol. 7 No. 3 (2026): Jurnal Ilmu Manajemen Terapan (Januari - Februari 2026)
Publisher : Dinasti Review Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jimt.v7i3.7825

Abstract

Penelitian ini bertujuan untuk menganalisis kualitas layanan aplikasi Traveloka berdasarkan ulasan pengguna di Google Play Store menggunakan pendekatan text mining dan sentiment analysis berbasis IndoBERT. Data yang digunakan terdiri dari 121.498 ulasan berbahasa Indonesia di sepanjang tahun 2025. Analisis dilakukan melalui tahapan preprocessing, klasifikasi sentimen, serta pemetaan ulasan ke dalam empat dimensi E-S-QUAL yaitu efficiency, fulfillment, system availability, dan privacy. Hasil analisis menunjukkan bahwa 48,8% ulasan bersentimen positif dan 23,7% bersentimen negatif dengan rasio 2:1. Model IndoBERT menunjukkan performa yang baik dengan akurasi 89,2% dan skor F1 89,3%. Pengukuran skor kualitas layanan menunjukkan bahwa dimensi efficiency memperoleh skor positif (+0,39), sementara fulfillment (-0,26), system availability (-0,44), dan privacy (-0,71) menunjukkan skor negatif. Temuan ini mengindikasikan bahwa meskipun aplikasi dinilai mudah digunakan, masih terdapat permasalahan pada proses pemenuhan layanan, stabilitas sistem, dan keamanan data. Secara praktis, penelitian ini memberikan kontribusi bagi Traveloka dalam mengidentifikasi area prioritas perbaikan operasional berbasis data ulasan pengguna secara real-time, khususnya pada penguatan integrasi sistem dengan mitra layanan, peningkatan keandalan infrastruktur teknologi, serta optimalisasi perlindungan data dan keamanan transaksi. Pendekatan ini juga dapat dimanfaatkan sebagai mekanisme monitoring kualitas layanan digital secara berkelanjutan guna mendukung strategi peningkatan kepuasan dan loyalitas pengguna.
Co-Authors Dahlan, Iqbal Ahmad Firdaus, Muhammad Azka Lesmana, Azka Versantariqh Noviasari, Tria Putri Rimbawa, H A Danang Tjahjadi, Hendrana Vanya Pinkan Maridelana Versantariqh, Muhammad Azka