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All Journal G-Tech : Jurnal Teknologi Terapan Teknosains : Jurnal Sains,Teknologi dan Informatika
Dwi Hartanti
Universitas Duta Bangsa Surakarta, Indonesia
Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Energy Engineering

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Monitoring Suhu Box Panel dan Voltase Pengisian Baterai pada Base Transceiver Station Berbasis IoT Andy Ariyanto; Nurchim Nurchim; Dwi Hartanti
G-Tech: Jurnal Teknologi Terapan Vol 8 No 1 (2024): G-Tech, Vol. 8 No. 1 Januari 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v8i1.3803

Abstract

Started with the frequent running out of backup battery power at the Wifi Base Transceiver Station (BTS) due to frequent power outages in the BTS area and the high temperature inside the panel box. This problem can be overcome by research into a panel box temperature monitoring system and battery charging voltage in IoT-based BTS. The system development used is a prototype method, which can overcome problems between users and researchers. Researchers used ESP32 Wrover as a microcontroller, voltage divider as a voltage sensor and DHT11 as a temperature sensor. If the charging voltage is less than 11 volts and/or the voltage is more than 15 volts then the ESP32 Wrover will send a Telegram message to the user and if the temperature read by the DHT11 sensor is more than 40 degrees Celsius then the system will turn on the relay connected to the cooling fan, the fan will be turned off when the temperature drops to 30 degrees Celsius.
Perancangan aplikasi belajar bahasa inggris berbasis website Asa Dilla Safitri; Atik Sulami; Jamilatun Safitri; Dwi Hartanti
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 10 No 1 (2023): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK-Sekolah Tinggi Teknologi Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v10i1.253

Abstract

In times of a pandemic like this, all learning activities are carried out online via the internet with the help of learning applications that can support one's education. In the current era, there is a great need for interactive distance learning applications. An interactive English learning application in web form will be easily accessed and used by anyone. Therefore, on this occasion we created a website-based learning application, especially for English subjects because that language is an international language. In this research, an English learning application will be built that can be run on a web-based basis. The material displayed in this application is tenses, listening, speaking, idioms, expressions, regular and irregular verbs, and slang. This application is designed with UML modeling, developed using HTML programming language. We also use the waterfall software process model in designing the BeBI (Learning English) application system. The purpose of making this application is to make it easier to learn English with material that is easy to understand and this application has an easily accessible interface. The waterfall model that we use is the Sommerville waterfall with the consideration that the system design steps will be organized, focused, and easy to follow. Where the result of designing this application is an educational application system for users which is expected to help the community in learning English and make it easier for someone to prepare themselves to take English tests such as TOEFL and TOEIC. For further development, it is hoped that this application can be accessed on various platforms.
Pengembangan Sistem Deteksi Penyakit Tanaman Tomat Melalui Citra Daun dengan Metode You Only Look Once (YOLO) Berbasis Android Bagus Erwanto; Afu Ichsan Pradana; Dwi Hartanti
G-Tech: Jurnal Teknologi Terapan Vol 8 No 3 (2024): G-Tech, Vol. 8 No. 3 Juli 2024
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/gtech.v8i3.4327

Abstract

Pertanian memiliki peran penting dalam ekonomi Indonesia, khususnya sub-sektor hortikultura seperti produksi buah dan sayuran. Budidaya tomat (Lycopersicum esculentum Mill) menjadi salah satu komoditas unggulan, namun serangan penyakit pada daun tomat menjadi tantangan utama yang dapat mengurangi hasil panen. Berbagai penelitian telah menyoroti kebutuhan akan solusi deteksi penyakit tanaman berbasis komputer vision untuk tomat. Penelitian ini fokus pada pengembangan aplikasi deteksi penyakit pada citra daun tomat berbasis Android menggunakan metode YOLO versi 8. Evaluasi model dilakukan menggunakan confusion matrix dan metrik seperti precision, recall, dan mAP.Hasilnya menunjukkan akurasi yang tinggi dalam mengklasifikasikan berbagai penyakit pada daun tomat. Hasil menunjukkan kinerja model yang baik dalam mengklasifikasikan berbagai jenis penyakit pada daun tomat, dengan mAP sebesar 96.6%  dan recall sebesar 92.2% untuk seluruh kelas penyakit. Pengujian aplikasi dengan Black box testing menunjukkan kemampuan deteksi yang baik. Aplikasi ini berhasil dikembangkan dan dirilis sebagai "Plantify" di Apkpure.
Co-Authors Afu Ichsan Pradana Andy Ariyanto Asa Dilla Safitri Atik Sulami Bagus Erwanto Jamilatun Safitri Nurchim Nurchim