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All Journal Indonesian Journal of Information System Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Muhammad Raafi'u Firmansyah
Telkom University
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance Engineering Public Health Social Sciences

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Adaptive Integration of Distributed Deep Q-Networks for Enhancing OLSR Routing in Dynamic Mobile Ad-Hoc Networks Alon Jala Tirta Segara; Arief Rais Bahtiar; Muhammad Raafi'u Firmansyah; Fahrudin Mukti Wibowo
Indonesian Journal of Information Systems Vol. 8 No. 2 (2026): February 2026
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v8i2.11760

Abstract

Adaptive routing in Mobile Ad-Hoc Networks (MANETs) poses considerable difficulty owing to the network's dynamic characteristics, lack of stable infrastructure, and swift topology alterations. The Optimized Link State Routing (OLSR) protocol provides a proactive routing mechanism via topology dissemination and MultiPoint Relay (MPR) selection. Nevertheless, it exhibits diminished responsiveness to real-time topology alterations, as it depends on periodic updates and does not explicitly account for link quality. This paper suggests the incorporation of the Deep Q-Network (DQN) methodology into OLSR as a reinforcement learning strategy to improve routing adaptability and efficiency. The DQN model employs network metrics like latency, ETX, buffer occupancy, and neighbor count as state inputs, with actions determined by Q-values obtained via environmental interactions. Simulations conducted with NS-3 and PyTorch demonstrate that OLSR-DQN enhances Packet Delivery Ratio (PDR) by as much as 20%, decreases delay by 15–25%, and markedly boosts throughput in dynamic MANET situations. Keywords: MANET, OLSR, Deep Q-Network, adaptive routing, reinforcement learning
An IoT-Based Smart Solar Dryer Development for Coffee Bean Drying Optimization as an Applied Technology Solution: Optimalisasi Proses Pengeringan Biji Kopi Menggunakan Smart Solar Dryer Berbasis IoT sebagai Solusi Teknologi Tepat Guna Muhammad Agung Nugroho; Muhammad Raafi'u Firmansyah; Anggi Zafia; Aulia Desy Nur Utomo; Rakhmad Maulidi; Nenen Isnaini
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol. 10 No. 3 (2026): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : DPD Jatim Perkumpulan Dosen Indonesia Semesta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36339/je.v10i3.554

Abstract

Drying is a critical stage in coffee post-harvest processing that significantly influences the physical quality, moisture content, and overall quality of green coffee beans. Coffee farmers in the Glodogan Coffee Farmers Group, Glempang Village, Pekuncen District, Banyumas Regency, still rely on the traditional open sun drying method, which is highly dependent on weather conditions, requires a long drying period, produces uneven heat distribution, and increases the risk of contamination and non-uniform moisture content. This community service program aimed to implement an Internet of Things (IoT)-based Smart Solar Dryer as an appropriate technology to improve coffee drying practices. The implementation adopted a Participatory Technology Implementation approach consisting of four stages: partner needs assessment, prototype design and fabrication, technology implementation, and training with evaluation. The developed system integrates a greenhouse-effect drying chamber, temperature and humidity sensors, an ESP32 microcontroller, and a dashboard for real-time monitoring. The implementation demonstrated that the Smart Solar Dryer effectively supported the drying process of both coffee cherries and wet-processed green beans. The monitoring dashboard provided real-time information on drying chamber temperature, humidity, system status, and historical drying records, enabling farmers to monitor the process without opening the drying chamber. Evaluation involving six farmers indicated a Partner Satisfaction Index of 95.33%, with 76.67% of respondents strongly agreeing and 23.33% agreeing with the usefulness of the program and the implemented technology. These findings indicate that the IoT-based Smart Solar Dryer has strong potential to improve coffee post-harvest quality while encouraging the adoption of digital technologies among smallholder coffee farmers.
Co-Authors Alon Jala Tirta Segara Anggi Zafia Arief Rais Bahtiar Aulia Desy Nur Utomo Fahrudin Mukti Wibowo Muhammad Agung Nugroho Nenen Isnaini Rakhmad Maulidi