Framework Smart Mushroom Farming Berbasis IoT dan AI Menggunakan Pendekatan Multimodal untuk Budidaya Jamur Merang

Yenny Desnelita; Gustientiedina Gustientiedina; Ramalia Noratama Putri; Alyauma Hajjah; Yulvia Nora Marlim; Irwan Irwan

doi:10.55382/jurnalpustakarobotsister.v4i2.2451

Authors

Yenny Desnelita Institut Bisnis dan Teknologi Pelita Indonesia
Gustientiedina Gustientiedina Institut Bisnis dan Teknologi Pelita Indonesia
Ramalia Noratama Putri Institut Bisnis dan Teknologi Pelita Indonesia
Alyauma Hajjah Institut Bisnis dan Teknologi Pelita Indonesia
Yulvia Nora Marlim Institut Bisnis dan Teknologi Pelita Indonesia
Irwan Irwan Institut Bisnis dan Teknologi Pelita Indonesia

DOI:

https://doi.org/10.55382/jurnalpustakarobotsister.v4i2.2451

Keywords:

Convolutional Neural Network, Design Science Research, Internet of Things, Jamur Merang, Pendekatan Multimodal, Smart Farming

Abstract

Budidaya jamur merang (Volvariella volvacea) sangat bergantung pada kestabilan mikroklimat yang selaras dengan tahapan pertumbuhannya, sehingga data lingkungan dan perkembangan visual jamur perlu dianalisis secara terpadu agar pengelolaan budidaya dapat dilakukan secara lebih presisi. Penelitian ini mengusulkan sebuah framework Smart Mushroom Farming berbasis Internet of Things (IoT) dan Artificial Intelligence (AI) dengan pendekatan multimodal untuk mendukung pemantauan lingkungan sekaligus analisis fase pertumbuhan jamur merang. Framework disusun melalui pendekatan Design Science Research (DSR) dan diwujudkan dalam arsitektur empat lapisan, yaitu sensing, communication, processing, dan application layer. Pada lapisan akuisisi data, parameter suhu, kelembapan relatif, konsentrasi CO₂, intensitas cahaya, dan kelembapan media dipadukan dengan citra RGB perkembangan jamur sebagai representasi kondisi visual. Seluruh data tersebut ditransmisikan melalui protokol MQTT dan dikelola dalam basis data berbasis cloud. Pada lapisan pemrosesan, pendekatan multimodal dirancang untuk menggabungkan fitur mikroklimat dengan fitur visual yang diekstraksi menggunakan Convolutional Neural Network (CNN), sebagai dasar konseptual bagi identifikasi fase pertumbuhan mulai dari miselium, primordia (tiny button), button (egg), elongation, hingga fase matang/siap panen. Framework yang diusulkan menghubungkan tahapan akuisisi data, komunikasi IoT, integrasi data multimodal, analisis berbasis AI, visualisasi, hingga keluaran pengendalian mikroklimat dalam satu arsitektur yang saling terhubung. Kontribusi utama penelitian ini terletak pada penyediaan dasar konseptual dan teknis bagi pengembangan sistem budidaya jamur merang yang adaptif dan berbasis data, yang selanjutnya dapat diuji lebih lanjut melalui tahap implementasi dan validasi eksperimental.

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