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Bernadus Very Christioko
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Fakultas Teknologi Informasi dan Komunikasi, Universitas Semarang, Jl. Soekarno-Hatta Tlogosari Semarang, Central Java, Indonesia
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Jurnal Transformatika
Published by Universitas Semarang
ISSN : 16933656     EISSN : 24606731     DOI : https://doi.org/10.26623/transformatika
Core Subject : Science,
Computer Science & IT
Transformatika is a peer reviewed Journal in Indonesian and English published two issues per year (January and July). The aim of Transformatika is to publish high-quality articles of the latest developments in the field of Information Technology. We accept the article with the scope of Information Systems, Web Technology, Computer Networks, Artificial Intelligence, and Multimedia.
Arjuna Subject : -
Articles 353 Documents
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Implementation IoT On Electrical Monitoring And Consumption Recording System With Web Server And Spreadsheet Integration Catur Pamungkas; Jarot Dian Susatyono; Nur Rokhman
Jurnal Transformatika Vol. 24 No. 1 (2026): July 2026
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v24i1.14641

Abstract

Uncontrolled electrical energy consumption can cause energy waste and increase operational costs, especially in industrial environments with multiple electrical distribution panels. Conventional power meters that only display data locally without historical data storage make monitoring and evaluation processes less effective, making it difficult to analyse electricity usage and identify potential energy waste. This study purpose to make an IoT b electrical energy monitoring system using ESP32, PZEM-004T sensor, and automatic relay control. The system can do monitoring several parameters like voltage, current, power, and energy consumption in real time through a Wi-Fi network. In addition, electricity usage data are automatically stored to google spreadsheet for analysis and energy efficiency evaluation. The proposed system is aim the effectiveness and efficiency of electricity monitoring, simplify energy management, and help reduce energy waste and operational costs through more optimal electrical energy utilization.
Analisis Sentimen Ulasan Aplikasi PLN Mobile Menggunakan Naïve Bayes, SVM, dan Hutan Acak dengan SMOTE Helmy Agta Al Fatah; Rara Sriartati Redjeki
Jurnal Transformatika Vol. 24 No. 1 (2026): July 2026
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v24i1.14934

Abstract

Aplikasi PLN Mobile, seperti saluran layanan digital PT PLN (Persero), menerima ribuan ulasan dari pengguna di Google Play Store, yang sulit diverifikasi secara manual. Tujuan dari penelitian ini adalah untuk membandingkan kinerja tiga algoritma Machine Learing Naïve Bayes, Support Vector Machine (SVM) dan Random Forest untuk mengklasifikasikan sentimen ulasan PLN Mobile ke dalam dua kategori (positif dan negatif). Kebaruan penelitian ini terletak pada kombinasi strategi pengumpulan data yang seimbang berdasarkan kategori evaluasi, penyeimbangan kelas dengan teknik oversampling minoritas sintetis (SMOTE), validasi silang 5 kali, dan penyesuaian hiperparameter SVM. Sebanyak 3.702 ulasan dikumpulkan melalui webscraping setelah prapemrosesan teks dan pembobotan TF-IDF, diperoleh 2.917 data (1.586 negatif dan 1.331 positif) dengan 4.160 fitur. Hasil cross-validation menunjukkan bahwa Naïve Bayes memiliki rata-rata skor F1 tertinggi (0,846) dengan standar deviasi rendah (0,011) yang menunjukkan kinerja stabil. Dalam pengujian yang dilakukan pada 584 poin data, model Naïve Bayes kembali muncul sebagai yang terbaik, dengan skor akurasi, presisi, recall, dan F1 sebesar 84%, diikuti oleh SVM (83%) dan Random Forest (81%). Analisis kata-kata dominan mengungkapkan apresiasi pengguna atas kemudahan dan kecepatan layanan, serta keluhan teratas tentang pemadaman listrik yang lama dan kendala pembayaran dan keluhan. Temuan ini menegaskan keunggulan Naïve Bayes dalam teks revisi bahasa Indonesia yang sederhana sekaligus memberikan masukan praktis untuk meningkatkan kualitas layanan PLN Mobile.
Kalibrasi Sensor Analog IoT Terintegrasi pH, DO, Suhu dan TDS untuk Penentuan Water Quality Index Agus Hartanto; Lenny Margaretta Huizen; Charis Maulana
Jurnal Transformatika Vol. 24 No. 1 (2026): July 2026
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v24i1.15117

Abstract

Water pollution is a serious environmental issue in Indonesia, necessitating an accurate and real-time water quality monitoring system. This study developed an Internet of Things (IoT)-based monitoring system using an ESP32 microcontroller integrated with four analog sensors, namely pH, Dissolved Oxygen (DO), temperature (DS18B20), and Total Dissolved Solids (TDS). The system was designed with a layered architecture comprising a sensing layer, edge processing, a communication layer based on the MQTT protocol on a Linux Ubuntu server with a Mosquitto broker, and an application and storage layer using a MySQL database and a web interface based on Laravel with real-time visualization using JavaScript and CSS. Sensor calibration was performed using a multipoint calibration approach with linear and polynomial regression, accompanied by temperature compensation and digital filtering (median filter and Exponential Moving Average). Performance evaluation was conducted through 30 simultaneous measurements against standard laboratory instruments, resulting in an average system accuracy of 90.9% with R² values ranging from 0.806 to 0.956. The TDS and temperature parameters showed the best accuracy at 94.2% and 93.3%, respectively, whereas the pH and DO achieved 86.8% and 89.3%, respectively. The results of this study indicate that the developed ESP32-based IoT system is capable of generating reliable data (accuracy above 90%) for water quality monitoring in tropical environments. This research provides a practical contribution in the form of a solution that supports the implementation of sustainable monitoring in accordance with Government Regulation Number 22 of 2021 and Sustainable Development Goal (SDG) 6.

Page 36 of 36 | Total Record : 353

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