SYAHPUTRA, MOH DZIKRI ROBBY (2026) RANCANG BANGUN SISTEM MONITORING CAIRAN INFUS BERBASIS IOT DENGAN METODE TYPE-2 FUZZY SUGENO. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
Delays in replacing IV fluids and manual monitoring at healthcare facilities can risk causing medical complications, such as clogged tubes or backflow in patients. This study aims to design and implement an automated IV fluid monitoring and control system based on the Internet of Things (IoT) using a Type-2 Fuzzy Sugeno algorithm. The research develops an innovation in the form of an integrated dual-IV monitoring and control system based on IoT with the implementation of an Interval Type-2 Fuzzy Sugeno algorithm to adaptively handle sensor reading uncertainties. The ESP32 microcontroller serves as the control center, connected to two HX711 load cells to measure fluid volume, two TCRT5000 sensors to count drop rates and detect blockages, and a DC peristaltic pump as the flow control actuator. Remote monitoring interface access and TPM settings are done through a public website that is securely transmitted via Ngrok tunneling and protected by HTTP Basic authentication. A Type-2 Fuzzy Sugeno algorithm with 18 inference rules is applied to handle uncertainties and sensor reading noise in real-time. Test results show that the load cell sensor has an average volume reading accuracy rate of 99.69%. Testing the drip rate settings in the 10-60 TPM range produced a control accuracy rate of 97.96% with a combined error of 2.04%. All main operational functions (Infusion 1 and 2 Active, Auto-Switch, Blockage Detection, Second Infusion Empty Warning, and Emergency Stop) were successfully performed. Overall, the integration of the IoT-based system and Type-2 Fuzzy Sugeno resulted in a combined system accuracy rate of 98.82%, proving to be reliable in minimizing manual medical interventions and improving patient safety. Keywords: Internet of Things (IoT), Infusion Fluid Monitoring, Type-2 Fuzzy Sugeno, TPM, Ngrok Tunne Keterlambatan penggantian cairan infus dan pemantauan manual pada fasilitas Kesehatan berisiko menyebabkan komplikasi medis, seperti selang tersumbat atau timbulnya aliran darah balik pada pasien. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem monitoring serta pengendalian cairan infus otomatis berbasis Internet of Things (IoT) menggunakan algoritma Type-2 Fuzzy Sugeno. Penelitian ini mengembangkan kebaruan berupa sistem monitoring dan kendali infus ganda terintegrasi berbasis IoT dengan implementasi algoritma Type-2 Fuzzy Sugeno untuk mengatasi ketidakpastian pembacaan sensor secara adaptif. Mikrokontroller ESP32 sebagai pusat kendali yang terhubung dengan dua loadcell HX711 untuk mengukur volume cairan, dua sensor TCRT5000 untuk menghitung laju tetesan dan mendeteksi sumbatan, serta peristaltic pump DC sebagai aktuator kendali aliran. Akses antarmuka monitoring jarak jauh dan pengaturan TPM dilakukan melalui website publik yang ditransmisikan secara aman via tunnelling Ngrok serta dilindungi autentikasi HTTP Basic. Algoritma Type-2 Fuzzy Sugeno dengan 18 aturan inferensi diterapkan untuk mengani ketidakpastian dan noise pembacaan sensor secara real-time. Hasil pengujian menunjukkan bahwa sensor loadcell memiliki Tingkat akurasi rata-rata pembacaan volume sebesar 99,69%. Pengujian pengaturan laju tetesan pada rentang 10-60 TPM menghasilkan tingkat akurasi kendali sebesar 97,96% dengan eror gabungan 2,04%. Seluruh fungsi operasional utama (Infus 1 dan 2 Aktif, Auto-Switch, Deteksi Penyumbatan, Peringatan Kedua Infus Habis, dan Emergency Stop) berhasil dilakukan dengan baik. Secara keseluruhan, integrasi sistem berbasi IoT dan Type2 Fuzzy Sugeno ini menghasilkan Tingkat akurasi sistem gabungan sebesar 98,82%, sehingga terbuikti handal dalam meminimalisasi intervensi manual tenaga medis dan menibgkatkan keselamatan pasien. Kata Kunci : Internet of Things (IoT), Monitoring Cairan Infus, Type-2 Fuzzy Sugeno, TPM, Tunneling Ngrok
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