Muhammad Haykal Islam Baskoro, . (2026) IMPLEMENTASI FUZZY SUGENO TIPE-0 PADA IOT REAL-TIME UNTUK PENGENDALIAN KUALITAS AIR AKUARIUM IKAN HIAS. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.
![[img]](http://repository.upnvj.ac.id/style/images/fileicons/text.png) |
Text
ABSTRAK.pdf Download (146kB) |
|
Text
AWAL.pdf Download (748kB) |
|
Text
BAB I.pdf Restricted to Repository UPNVJ Only Download (142kB) |
|
Text
BAB II.pdf Restricted to Repository UPNVJ Only Download (1MB) |
|
Text
BAB III.pdf Restricted to Repository UPNVJ Only Download (1MB) |
|
Text
BAB IV.pdf Restricted to Repository UPNVJ Only Download (3MB) |
|
Text
BAB V.pdf Download (97kB) |
|
Text
DAFTAR PUSTAKA.pdf Download (126kB) |
|
Text
DAFTAR RIWAYAT HIDUP.pdf Restricted to Repository staff only Download (105kB) |
|
Text
LAMPIRAN.pdf Restricted to Repository UPNVJ Only Download (2MB) |
|
Text
HASIL PLAGIARISME.pdf Restricted to Repository staff only Download (38MB) |
|
Text
ARTIKEL KI.pdf Restricted to Repository staff only Download (618kB) |
Abstract
Ornamental fish keeping requires continuous water-quality monitoring because changes in temperature, pH, and turbidity can affect aquarium conditions. This study implements a real-time IoT prototype based on an ESP32 and Type-0 Sugeno Fuzzy Logic to process data from DS18B20, pH-4502C, and SEN-0175 sensors and control a heater, fan, filter pump, drain pump, and fill pump. The inference process uses three input variables, 27 rules, the minimum operator, and weighted average. Data are transmitted through MQTT to a Node.js backend, forwarded through WebSocket, stored in Supabase, and visualized on a web dashboard. Test results show that Sugeno achieved an inference time of 9.391 µs, lower than Tsukamoto at 17.871 µs and Mamdani at 1,462.504 µs. The temperature sensor produced a mean absolute error of 0.275°C, while the turbidity sensor voltage decreased from 4.5912 V to 4.1464 V with a coefficient of variation below 0.12%. Under extreme conditions, the heater, cooler, and filter reached outputs of 99–100%. Black-box testing with three users resulted in 63 successful scenarios out of 63. These results indicate that the prototype provides gradual control and supports real-time water-quality monitoring.
| Item Type: | Thesis (Skripsi) |
|---|---|
| Additional Information: | [No.Panggil: 2210511149] [Pemimbing 1: Dr. Didit Widiyanto] [Pemimbing 2: Nur Hafifah Matondang] [Penguji 1: Dr. Indra Permana Solihin] [Penguji 2: Novi Trisman Hadi] |
| Uncontrolled Keywords: | ESP32, Ornamental Fish Aquarium, Real-Time IoT, Type-0 Sugeno Fuzzy Logic, Water Quality |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software S Agriculture > SH Aquaculture. Fisheries. Angling T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Fakultas Ilmu Komputer > Program Studi Informatika (S1) |
| Depositing User: | MUHAMMAD HAYKAL ISLAM BASKORO |
| Date Deposited: | 30 Jul 2026 07:45 |
| Last Modified: | 10 Sep 2026 01:41 |
| URI: | http://repository.upnvj.ac.id/id/eprint/51720 |
Actions (login required)
 |
View Item |