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All Journal Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Journal of Applied Data Sciences
Mimmy Sari Syah Putri
Universitas Sumatera Utara
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Law, Crime, Criminology & Criminal Justice Social Sciences

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Application of Internet of Things (IoT) Technology Automatic Plant Watering Using Arduino Program on Corn Plants of Sadar Tani Farmers Group Mimmy Sari Syah Putri; Saib Suwilo; Aghni Syahmarani; Putri Cahaya Situmorang; Alberto Tondang
ABDIMAS TALENTA: Jurnal Pengabdian Kepada Masyarakat Vol. 10 No. 2 (2025): ABDIMAS TALENTA: Jurnal Pengabdian Kepada Masyarakat
Publisher : Talenta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/abdimastalenta.v10i2.18053

Abstract

The technology of the Internet of Things (IoT) is advancing and being implemented in a variety of sectors, including agriculture. The Sadar Tani farmer group's automatic plant watering system for maize plants is the focus of this research, which investigates the application of IoT technology. The primary controller of this system is an Arduino device, which is connected to a communication module and soil moisture sensor to transmit data in real-time. The water pump is automatically activated to irrigate the plants until the humidity level returns to normal when the soil moisture level falls below the specified limit. This implementation has yielded enhanced corn plant health, reduced farmer workload, and increased water use efficiency. Furthermore, this system enables the remote surveillance of crop conditions, which offers supplementary advantages in the management of larger agricultural lands. As a result, the implementation of IoT technology offers a viable solution to the issue of watering plants on expansive agricultural land, in addition to promoting precision agriculture that is more environmentally favorable and sustainable. This research has the potential to serve as a reference for future development in the application of similar technology to other crops and the enhancement of features to optimize agricultural yields.
A Data-Driven Mixed Integer Nonlinear Programming Model for Cost-Optimal Scheduling of Perishable Production and Workforce Mimmy Sari Syah Putri; Herman Mawengkang; Saib Suwilo; Tulus Tulus
Journal of Applied Data Sciences Vol 6, No 4: December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i4.1019

Abstract

This study presents a data-driven, Mixed Integer Nonlinear Programming (MINLP) framework for optimizing the multi-period production scheduling of perishable products with integrated workforce planning. Its primary novelty is the holistic integration of a continuous exponential decay function for product deterioration with dynamic workforce planning, creating a unified model that optimizes production, inventory, and labor simultaneously. This approach addresses key challenges in perishable inventory systems by treating labor as a controllable resource rather than a fixed constraint. Mathematically, the model includes nonlinear inventory balance equations with decay terms and resource-dependent capacity constraints. The objective is to minimize total operational cost, comprising production, holding, and spoilage costs. Computational experiments, based on a realistic case study, demonstrate that the proposed model reduces total system cost by 6.2% and spoilage costs by 43.2% compared to a standard heuristic benchmark. The resulting production and labor schedules align closely with demand fluctuations, supporting both economic and operational efficiency. This unified framework advances the mathematical modeling of sustainable production planning and offers a practical tool for real-world industries such as food processing and pharmaceuticals.
Co-Authors Aghni Syahmarani Alberto Tondang Herman Mawengkang Putri Cahaya Situmorang Saib Suwilo Tulus Tulus