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All Journal Tekno : Jurnal Teknologi Elektro dan Kejuruan Elkom: Jurnal Elektronika dan Komputer Journal of Telematics and Informatics Jurnal Teknik Elektro dan Komputer TRIAC Infotronik : Jurnal Teknologi Informasi dan Elektronika Infotekmesin Jurnal E-Komtek Indonesian Journal of Electrical Engineering and Computer Science Journal of Energy and Electrical Engineering (JEEE) Madani : Indonesian Journal of Civil Society Journal of Electrical Engineering and Computer (JEECOM) Jurnal Jaringan Telekomunikasi E-JOINT (Electronica and Electrical Journal Of Innovation Technology) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Urecol Journal. Part E: Engineering
Zaenurrohman Zaenurrohman
Politeknik Negeri Cilacap
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Monitoring Konsumsi Daya Listrik Menggunakan Google Spreadsheet Zealita, Zarah; Prasetia, Vicky; Zaenurrohman
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2523

Abstract

The lack of detailed information on the daily electricity consumption of each electronic device can hinder the accurate calculation of electricity consumption costs. This can affect the accuracy and ease of access to electricity consumption data. This research aims to develop an electric power reading system using the PZEM-004T sensor, an electricity power monitoring system, and the cost of electricity usage through Google Sheets. The system is designed to measure current, voltage, power, and electricity costs with high accuracy. The test results show that the KWH meter reading system can measure electricity consumption using the PZEM-004T sensor with accuracy values of 99.805% for voltage (volts), 89.71% for current (amperes), and 99.98% for power (watts) in each test. The data from the sensor monitoring system and cost calculations can be effectively displayed on Google Sheets, which functions well for measuring and displaying data for current, voltage, power, and electricity billing.
Handling missing values and clustering industrial liquid waste using K-medoids Maharrani, Ratih Hafsarah; Abda'u, Prih Diantono; Ikhtiagung, Ganjar Ndaru; Rahadi, Nur Wahyu; Zaenurrohman, Zaenurrohman
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 2: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i2.pp1411-1420

Abstract

The textile industry is a significant contributor to environmental pollution due to its wastewater, which contains hazardous substances such as dyes, heavy metals, and chemicals that can severely harm aquatic ecosystems. Effective management of this wastewater is crucial to mitigate its environmental impact. This study focuses on classifying industrial liquid waste data using the K-medoids clustering method, chosen for its robustness to noise and outliers compared to K-means. To address challenges in wastewater data processing, such as missing values and varying data scales, two approaches are compared: replacing missing values with zero and K-nearest neighbors (KNN) imputation, alongside Z-score normalization for data uniformity. The clustering quality is evaluated using the Davies-Bouldin index (DBI) for cluster variations of k=2, 3, 4, and 5. The results show that the best clustering quality is achieved at k=2, with the smallest DBI values obtained using KNN imputation (0.139) and zero replacement (0.149). The superior performance of KNN imputation highlights its effectiveness in handling missing data. These findings provide valuable insights into the characteristics of textile industry wastewater pollution, offering a robust framework for effective wastewater management. The study concludes with practical recommendations for policymakers and industry stakeholders to adopt advanced data-driven approaches for sustainable wastewater treatment strategies.
Rancang Bangun Monitoring Early Warning System Bencana Banjir Berdasarkan Ketinggian Aliran Sungai Mengunakan Modem SIM900 dan Internet of Things Sumardiono, Arif; Alimudin, Erna; Zaenurrohman; Susanti, Hera
Infotekmesin Vol 13 No 1 (2022): Infotekmesin: Januari, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i1.1019

Abstract

The rainfall in the Cilacap region is high, about 80-100mm in October-March. The high rainfall that causes the overflow of river water is unpredictable. The high water discharge is not realized until the river water overflows and causes flooding. Therefore, a river water level monitoring system is needed to detect river overflows early. This tool uses a solar cell as a power supply. The monitoring system is divided into two points of river water level monitoring system with a distance between points for the laboratory scale stage, which is 100 meters. Sensors that measure the height of river flow are ultrasonic sensors. The sensor results are processed by microcontroller and SIM 900 L module to be sent to the database. When the water level is in the Alert level 3, the buzzer will sound as a warning. The ultrasonic sensor test results have a very small error. Sensor 1 has an average error of 0.00023% and ultrasonic sensor 2 has an error of 0.00016%. The system is able to transmit river water level data that can be accessed through the website.
Monitoring Konsumsi Daya Listrik Menggunakan Google Spreadsheet Zealita, Zarah; Prasetia, Vicky; Zaenurrohman
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2523

Abstract

The lack of detailed information on the daily electricity consumption of each electronic device can hinder the accurate calculation of electricity consumption costs. This can affect the accuracy and ease of access to electricity consumption data. This research aims to develop an electric power reading system using the PZEM-004T sensor, an electricity power monitoring system, and the cost of electricity usage through Google Sheets. The system is designed to measure current, voltage, power, and electricity costs with high accuracy. The test results show that the KWH meter reading system can measure electricity consumption using the PZEM-004T sensor with accuracy values of 99.805% for voltage (volts), 89.71% for current (amperes), and 99.98% for power (watts) in each test. The data from the sensor monitoring system and cost calculations can be effectively displayed on Google Sheets, which functions well for measuring and displaying data for current, voltage, power, and electricity billing.
Co-Authors Adrian Putra Ramadhan Agus Santoso Alimudin, Erna Anna Nurdiasari Arif Sumardiono Arif Sumardiono Desyandri Desyandri Erna Alimudin Erna Alimudin Erna Alimudin Fadhillah Hazrina Fadhillah Hazrina Firman Burhani Hazrina, Fadhillah Hendi Purnata Hera Susanti Hera Susanti Hera Susanti, Hera Ikhtiagung, Ganjar Ndaru Julian Nurachman Wijaya Mafaza Harris, Ridho Ihsan Maharrani, Ratih Hafsarah Mohamad Iqbal Husain Novita Asma Ilahi Prasetia, Vicky Prih Diantono Abda`u Purwiyanto Purwiyanto Rahadi, Nur Wahyu Ratih Hafsarah Maharrani Rio Guntur Dany Rafi Riyadi Purwanto Saepul Rahmat Saepul Rahmat Saepul Rahmat Sugeng Dwi Riyanto Sumardiono, Arif Supriyono Supriyono Susanti , Hera Susanti, Hera Utis Sutisna Zealita, Zarah