RANCANG BANGUN SISTEM MISTING BERDASARKAN SENSOR SUHU DAN CAHAYA MENGGUNAKAN FUZZY LOGIC BERBASIS INTERNET OF THINGS

Aqilah Al Haura, . (2025) RANCANG BANGUN SISTEM MISTING BERDASARKAN SENSOR SUHU DAN CAHAYA MENGGUNAKAN FUZZY LOGIC BERBASIS INTERNET OF THINGS. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

[img] Text
ABSTRAK.pdf

Download (420kB)
[img] Text
AWAL.pdf

Download (2MB)
[img] Text
BAB 1.pdf
Restricted to Repository UPNVJ Only

Download (1MB)
[img] Text
BAB 2.pdf
Restricted to Repository UPNVJ Only

Download (802kB)
[img] Text
BAB 3.pdf
Restricted to Repository UPNVJ Only

Download (1MB)
[img] Text
BAB 4.pdf
Restricted to Repository UPNVJ Only

Download (994kB)
[img] Text
BAB 5.pdf

Download (556kB)
[img] Text
DAFTAR PUSTAKA.pdf

Download (603kB)
[img] Text
RIWAYAT HIDUP.pdf
Restricted to Repository UPNVJ Only

Download (367kB)
[img] Text
LAMPIRAN.pdf
Restricted to Repository UPNVJ Only

Download (1MB)
[img] Text
HASIL PLAGIARISME.pdf
Restricted to Repository staff only

Download (10MB)
[img] Text
ARTIKEL KI.pdf
Restricted to Repository staff only

Download (185kB)

Abstract

One of the most important factors for plants is water. However, both a deficiency and an excess of water can lead to plant death. One method of irrigation is the misting system. The plant used as the basis for determining water needs in this study is a grape seedling. Several parameters can be used to control an irrigation system, such as temperature, light, or soil moisture, depending on the plant’s needs. This research designs an automatic misting system based on temperature and light parameters. The DHT11 sensor is used to detect ambient temperature in degrees Celsius, while the BH1750 sensor measures light intensity in lux. Data from both sensors are processed using the Mamdani fuzzy logic method. The output is displayed on an LCD and sent to the Blynk IoT application for monitoring purposes. The results show that the temperature sensor (DHT11) achieved an accuracy rate of 98.85%, the BH1750 light sensor reached an accuracy of 99.10%, and the pump performance accuracy was calculated at 99.20%. Based on the confusion matrix, the fuzzy system achieved an accuracy rate of 98% from 50 test iterations. Additionally, data was successfully transmitted to the Blynk application with an average delay of 1.01 seconds across 20 test samples.

Item Type: Thesis (Skripsi)
Additional Information: [No.panggil: 2010314022] [Pembimbing: Ni Putu Devira Ayu Martini] [Penguji 1: Silvia Anggraeni] [penguji 2: Andre Suwardana Adiwidya]
Uncontrolled Keywords: Fuzzy Logic, IoT, Light, Misting System, Temperature
Subjects: S Agriculture > SB Plant culture
T Technology > T Technology (General)
Divisions: Fakultas Teknik > Program Studi Teknik Elektro (S1)
Depositing User: AQILAH AL HAURA
Date Deposited: 25 Aug 2025 01:37
Last Modified: 25 Aug 2025 01:37
URI: http://repository.upnvj.ac.id/id/eprint/39620

Actions (login required)

View Item View Item