Update Artikelilmiah: 50258

FUAD ABDULLOH

NIM

Judul Artikel

Abstrak (Bhs. Indonesia)

Metode resistivitas dalam geofisika menggunakan resistivity meter untuk mengukur 
nilai resistivitas bawah permukaan melalui injeksi arus dan pengukuran tegangan. 
Proses akuisisi data konvensional masih menggunakan perpindahan elektroda manual 
yang membutuhkan waktu lama dan rentan terhadap kesalahan operator. Penelitian ini 
bertujuan merancang smart resistivity meter multi-channel berbasis Internet of Things 
(IoT) yang dapat mengefisienkan proses akuisisi data dengan sistem switching 
elektroda otomatis untuk konfigurasi Schlumberger, Wenner, dan Dipole-dipole. 
Penelitian menggunakan metode eksperimental dengan merancang sensor arus berbasis 
shunt resistor dan sensor tegangan menggunakan rangkaian pembagi tegangan. Sistem 
terintegrasi dengan mikrokontroler ESP32 dan Arduino Uno untuk mengontrol 8 
elektroda melalui relay switching. Data tersimpan otomatis pada cloud storage dan 
dapat dikontrol melalui aplikasi mobile berbasis MIT App Inventor. Hasil pengujian 
menunjukkan sistem dapat beroperasi dengan error pembacaan tegangan 3% dan arus 
2%, presisi tegangan 92% dan arus 96%, dengan range pengukuran 0-100V dan 0-
100mA. Sistem berhasil melakukan switching elektroda otomatis sesuai konfigurasi 
yang dipilih dan mengunggah data real-time ke cloud storage. Konsumsi daya sistem 
sebesar 4,23 watt dengan kemampuan multi-channel 8 elektroda. Kesimpulan 
penelitian menunjukkan smart resistivity meter multi-channel berhasil meningkatkan 
efisiensi akuisisi data geolistrik dengan fitur switching otomatis, penyimpanan cloud, 
dan kontrol aplikasi mobile yang user-friendly untuk tiga konfigurasi utama survei 
resistivitas.

Abtrak (Bhs. Inggris)

The resistivity method in geophysics utilizes a resistivity meter to measure subsurface 
resistivity values through current injection and voltage measurement. Conventional 
data acquisition processes still rely on manual electrode displacement, which is time
consuming and prone to operator errors. This research aims to design an Internet of 
Things (IoT)-based smart multi-channel resistivity meter that can enhance data 
acquisition efficiency through automatic electrode switching systems for 
Schlumberger, Wenner, and Dipole-dipole configurations. The research employed an 
experimental method by designing a current sensor based on shunt resistor and a 
voltage sensor using voltage divider circuits. The system is integrated with ESP32 and 
Arduino Uno microcontrollers to control 8 electrodes through relay switching. Data is 
automatically stored in cloud storage and can be controlled through a mobile 
application based on MIT App Inventor. Test results demonstrate that the system can 
operate with voltage reading error of 3% and current error of 2%, voltage precision 
of 92% and current precision of 96%, with measurement ranges of 0-100V and 0-
100mA. The system successfully performs automatic electrode switching according to 
the selected configuration and uploads real-time data to cloud storage. System power 
consumption is 4.23 watts with 8-electrode multi-channel capability. The research 
conclusion indicates that the smart multi-channel resistivity meter successfully 
improves geoelectric data acquisition efficiency with automatic switching features, 
cloud storage, and user-friendly mobile application control for three main resistivity 
survey configurations.

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