<![CDATA[The counting of fish seeds at Srikandi Fresh Fish MSME is currently conducted through visual manual calculation, which is prone to human error, requires considerable operational time, and hinders accurate real-time inventory recording. To address these operational constraints, this research implemented an automated, Internet of Things (IoT)-based fish seed counting system using the NodeMCU ESP8266 microcontroller integrated with Google Sheets and a Telegram Bot service. The study utilized the Design Science Research (DSR) methodology, encompassing problem identification, objective definition, architectural design and development, artifact demonstration, functional evaluation, and communication. The developed hardware prototype incorporates an infrared sensor placed along a single-lane counting mechanism to detect individual passing fish seeds, an I2C-interfaced 16×2 liquid crystal display for local output, and NodeMCU ESP8266 as the core processing and communication unit. Telemetry data are logged automatically into Google Sheets via Google Apps Script and subsequently relayed to business operators as instant mobile notifications through a dedicated Telegram Bot after an inactivity period of 30 seconds. Functional validation using black-box testing confirmed that all hardware interfaces and software automated procedures operated as intended. Across 30 experimental trials involving varying seed densities, the counting mechanism achieved an average accuracy rate of 87.01% with an overall error margin of 12.99%, primarily attributed to occasional overlapping during high-density passages. The integrated cloud system also proved reliable during continuous operation, successfully reducing manual recording delays and providing an efficient, automated inventory monitoring solution for aquaculture small businesses.]]>
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