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All Journal Medika Teknika : Jurnal Teknik Elektromedik Indonesia Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Yona Ramadika
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Computer Science & IT Electrical & Electronics Engineering

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Monitoring Urine Bag Berbasis Internet Of Things Romi Mulyadi; Albirruni Sirregar; Abu Bakar; Yona Ramadika; Vicky Firmansyah
Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Vol. 3 No. 2 (2025): Juni: Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/uranus.v3i2.902

Abstract

During this process of monitoring the contents (volume) of the patient's urinary catheter manually, the nurse must go around one by one to the patient's inpatient room to ensure the contents (volume) of the patient's urinary catheter. This process takes quite a long time while patients who use urinary catheters at the hospital are not small. In addition, if the patient's urinary catheter monitoring process is still done manually, sometimes the medical team or nurses often miss or forget, that the urine bag (catheter) is full. The purpose of this study is to design an Internet Of Things Based Urine Bag Monitoring. The research method used in this study was experimental. The population in this study was 65 TREM study program students with a sample of 40 respondents. Based on the average score table of the Simplicity, Interactivity and Usability surveys. The results of the score calculation using the Likert scale from the Simplicity, Interactivity and Usability factors of urine bag monitoring testing that has been carried out using questionnaires to respondents have shown a high score that is almost close to the value of 5 based on calculations carried out using the Likert scale which indicates that this urine bag monitoring tool can be well received by respondents. It is expected to be developed as material for further research related to monitoring urine bags using applications that can usealarms on users' smartphones and can also use batteries on urine bag monitoring tools
Sistem Deteksi Bentuk Rokok Menggunakan Faster Regional Convolutional Neural Network Yona Ramadika; Romi Mulyadi
Medika Teknika : Jurnal Teknik Elektromedik Indonesia Vol. 7 No. 1 (2025): October
Publisher : Universitas Muhammadiyah Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/mt.v7i1.26901

Abstract

Merokok adalah masalah adiksi berbahaya yang telah lama berakar di masyarakat Indonesia. Konsumsi produk tembakau menyebabkan 7,2 juta kematian, dan sebagian besar terjadi di negara berkembang, termasuk Indonesia. Fakta ini mendorong upaya pengendalian konsumsi tembakau melalui kebijakan Kawasan Tanpa Rokok (KTR) untuk melindungi masyarakat dari paparan asap rokok. Efektivitas peraturan ini seringkali terhambat oleh ketidakpatuhan sebagian masyarakat. Oleh karena itu, diperlukan penelitian untuk mengembangkan sistem monitoring yang mampu mendeteksi keberadaan rokok secara real-time. Penelitian ini bertujuan untuk merancang dan membangun sistem deteksi keberadaan rokok secara real-time menggunakan algoritma Faster R-CNN, serta menguji tingkat akurasi sistem tersebut pada implementasi di dalam dan luar ruangan pada jarak tertentu. Tingkat akurasi sistem akan diuji dengan membandingkan jumlah objek rokok yang terdeteksi dengan jumlah sebenarnya, lalu dikalikan seratus persen. Hasil pengujian menunjukkan bahwa sistem monitoring ini memiliki akurasi pendeteksian rokok yang sangat baik, dengan rata-rata akurasi berkisar antara 50% hingga 99% pada berbagai kondisi pengujian.
Co-Authors Abu Bakar Albirruni Sirregar Romi Mulyadi Vicky Firmansyah