IMPLEMENTASI PENYIMPANAN DATA PADA IOT SMART FARMING

AGUSTYA, AGUSTYA and Ubaya, Huda and Hermansyah, Adi (2022) IMPLEMENTASI PENYIMPANAN DATA PADA IOT SMART FARMING. Diploma thesis, Sriwijaya University.

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Abstract

Perkebunan merupakan salah satu bidang yang menjadi sumber daya yang penting bagi kehidupan masyarakat. Namun, terdapat banyak aspek yang perlu diperhatikan dalam mengelola perkebunan agar mendapatkan hasil yang optimal. Aspek-aspek tersebut terdiri dari beberapa hal seperti kondisi suhu, kelembaban udara, kelembaban tanah, intensitas cahaya, dan kadar garam dalam tanah. Untuk memperhatikan aspek-aspek penting diatas, maka penulis membuat sistem penyimpanan data kondisi kebun secara real time berbasis Internet of Things (IoT) untuk membantu proses pemantauan hingga dapat diambil tindakan berdasarkan kondisi kebun dalam pengelolaannya. Hasil penelitian menunjukkan data kondisi kebun dapat disimpan dengan baik ke dalam database mySQL dengan interval waktu posting data kurang lebih setiap 15 detik sekali, delay sistem pada penghitungan QoS untuk parameter delay juga tergolong baik dengan nilai kurang dari 150ms dan nilai rata – rata delay sebesar 9 ms. Plantation is one of the fields that is an important resource for people's lives. However, there are many aspects that need to be considered in managing plantations in order to get optimal results. These aspects consist of several things such as temperature conditions, air humidity, soil moisture, light intensity, and salt content in the soil. To pay attention to the important aspects above, the authors create a data storage system for the condition of the garden in real time based on the Internet of Things (IoT) to assist the monitoring process so that actions can be taken based on the condition of the garden in its management. The results showed that the garden condition data could be stored properly into the mySQL database with an interval of posting data approximately every 15 seconds, the delay in the QoS calculation system for the delay parameter was also quite good with a value of less than 150ms and an average delay value of 9 min.

Item Type:	Thesis (Diploma)
Uncontrolled Keywords:	Implementasi,Penyimpanan Data
Subjects:	H Social Sciences > HF Commerce > HF5410-5417.5 Marketing. Distribution of products > HF5415.126.R38 Database marketing--Statistical methods. Data mining--Statistical methods. Big data--Statistical methods.
Divisions:	09-Faculty of Computer Science > 56401-Computer Engineering (D3)
Depositing User:	Agustya Agustya
Date Deposited:	08 Aug 2022 08:46
Last Modified:	08 Aug 2022 08:46
URI:	http://repository.unsri.ac.id/id/eprint/76619

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