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Implementasi SMARCOS: Smart Water Conditioning System Berbasis Web-IoT di Balai Benih Ikan Kecamatan Mijen Semarang Nugroho, Anan; Subagja, Mona; Hidayat, Syahroni; Budiwirawan, Agung; Diyanasari, Ledi; Simanjuntak, Jhonatur Stheven; Wahyudi, Tri Agus; Fikri, Akmal
Journal of Community Development Vol. 6 No. 1 (2025): August
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/comdev.v6i1.1459

Abstract

Effective water quality management is crucial for fish hatcheries to ensure survival and productivity. At the Fish Hatchery Center (BBI) Cangkiran Mijen, water quality monitoring is still conducted manually, leading to unstable pond conditions. To improve monitoring efficiency, SMARCOS (Smart Water Conditioning System) was developed as a Web-IoT-based system for automated monitoring of water parameters such as pH, oxygen, and temperature. The program involved pond data collection, expert consultation, system design, testing, implementation, and partner training. Evaluation was conducted through satisfaction surveys and system performance monitoring. Results showed that SMARCOS effectively corrected water quality parameters automatically, enhanced monitoring efficiency, and provided easy access to information via an IoT-based website. Surveys indicated that partners were satisfied with the system’s usability. The adoption of IoT for water quality monitoring significantly improved the efficiency and accuracy of hatchery pond management. Training sessions also increased partner understanding of IoT technology. The success of SMARCOS demonstrates that IoT can be an innovative solution for fisheries modernization, with potential replication in other hatcheries to enhance productivity and efficiency in aquaculture.
LSTM-Based NLP Chatbot for Fish E-Marketplace at BBI Cangkiran Mijen Wahyudi, Tri Agus; Putri, Riana Defi Mahadji; Arief, Ulfah Mediaty; Sulistyawan, Vera Noviana
SISTEMASI Vol 14, No 5 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i5.5170

Abstract

Efficient and responsive information services are essential to support the fish sales process at the Cangkiran Mijen Fish Hatchery Center (Balai Benih Ikan), Semarang City. Interviews with hatchery staff revealed that the fish trading process is still conducted conventionally, requiring buyers to visit the hatchery in person. Currently, information regarding fish sales is only available through the official Semarang City Government website and Google Maps, which provides limited and often incomplete details. To obtain more comprehensive information, the public must contact staff via WhatsApp or visit the site directly. Moreover, customer inquiries tend to be repetitive, making the information service less effective. To address these issues, this study aims to develop a web-based fish e-marketplace system integrated with a natural language processing (NLP) chatbot using the Long Short-Term Memory (LSTM) algorithm. The system is expected to provide more informative, responsive, and always-available information services without relying on staff availability. The chatbot was trained using 757 question-and-answer pairs as training data. The system was developed using the Software Development Life Cycle (SDLC) waterfall model. Testing results indicate that the system demonstrates good functionality, is compatible across multiple devices and web browsers, and received positive feedback from users regarding ease of interaction and the relevance of chatbot responses. Algorithm validation results show an accuracy of 97%, precision of 94%, and recall of 95%.