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Edukasi Pemanfaatan Limbah Bambu Melalui Pembuatan Biochar di Desa Banjarwaru Kecamatan Nusawungu Kabupaten Cilacap Sari Widya Utami; Artdhita Fajar Pratiwi; Galih Mustiko Aji
I-Com: Indonesian Community Journal Vol 3 No 3 (2023): I-Com: Indonesian Community Journal (September 2023)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/icom.v3i3.2995

Abstract

Desa Banjarwaru adalah salah satu sentra industri kerajinan anyaman bambu, telah menciptakan berbagai inovasi-inovasi terbaru terhadap kerajinan anyaman bambunya. Namun, Petani tetaplah menjadi mata pencaharian utama penduduk. Meskipun, permasalahan pertanian di desa ini adalah tingkat kesuburan tanah yang rendah (kadar pH rendah), sehingga pemberian pupuk dalam jumah yang tinggi pun tidak mampu memberikan hasil yang baik pada pertumbuhan tanaman. Oleh sebab itu, dibutuhkan bahan pembenah yang mampu memperbaiki kesuburan tanah dengan meningkatkan pH tanah mendekati netral, seperti Biochar. Biochar dapat diperoleh dengan memanfaatkan sisa bambu yang tidak terpakai dalam produksi kerajinan bambu dan tidak dikelola dengan baik akibat kurangnya pengetahuan penduduk. Dalam kegiatan PkM ini, memperkenalkan biochar bambu dan manfaatnya sebagai bahan pembenah tanah, serta pembuatannya menggunakan metode soil-pit. Kegiatan ini telah mendorong masyarakat, untuk mengembangkan nilai lebih dari limbah bambu terutama untuk dimanfaatkan menjadi biochar untuk memperbaiki kualitas tanah pertanian di Desa Banjarwaru.
Design of Power Factor Monitoring System Based on Android Application Fadhillah Hazrina; Inu Yuni Erawati; Galih Mustiko Aji; Devi Taufiq Nurrohman
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 3 No. 2 (2023): November 2023
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v3i2.62

Abstract

Electrical energy is an essential resource for human needs. The prolific utilization of electrical devices accounts for high energy consumption patterns. Resistive and inductive loads characterize conventional electrical equipment. In practice, the properties of electrical loads impact energy demand and system efficiency. Thus, power factor correction presents a viable strategy to improve electrical energy efficiency. This research aims to develop an Internet of Things-integrated power factor monitoring system. When connected to Wi-Fi, the system employs a PZEM-004T sensor to monitor current, voltage, power, and power factor measurements from the load in the absence of active monitoring. The ESP32 microcontroller processes the sensor data. Then, control programs running on the microcontroller instruct a relay to engage capacitive banks accordingly. The system displays output metrics on a Liquid Crystal Display and Android application. Experimental results indicate that a single-phase electric motor operates at a baseline power factor of 0.31. However, integration of the factor correction tool detailed herein improves the power factor to 0.98 for the given load.
Design of Power Factor Monitoring System Based on Android Application Fadhillah Hazrina; Inu Yuni Erawati; Galih Mustiko Aji; Devi Taufiq Nurrohman
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 3 No. 2 (2023): November 2023
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v3i2.62

Abstract

Electrical energy is an essential resource for human needs. The prolific utilization of electrical devices accounts for high energy consumption patterns. Resistive and inductive loads characterize conventional electrical equipment. In practice, the properties of electrical loads impact energy demand and system efficiency. Thus, power factor correction presents a viable strategy to improve electrical energy efficiency. This research aims to develop an Internet of Things-integrated power factor monitoring system. When connected to Wi-Fi, the system employs a PZEM-004T sensor to monitor current, voltage, power, and power factor measurements from the load in the absence of active monitoring. The ESP32 microcontroller processes the sensor data. Then, control programs running on the microcontroller instruct a relay to engage capacitive banks accordingly. The system displays output metrics on a Liquid Crystal Display and Android application. Experimental results indicate that a single-phase electric motor operates at a baseline power factor of 0.31. However, integration of the factor correction tool detailed herein improves the power factor to 0.98 for the given load.