IoT-Based Guppy Aquaculture Monitoring System Using C 4.5 Method on Thingspeak Platform

(1) * aa zezen zaenal abidin Mail (Universitas Mandiri, Indonesia)
(2) Yuli Murdianingsih Mail (Universitas Mandiri, Indonesia)
(3) Ilham Ruhiyat Mail (Universitas Mandiri, Indonesia)
(4) Usep Tatang Suryadi Mail (Universitas Mandiri, Indonesia)
(5) Mohd. Fairuz Iskandar Othman Mail (Universiti Teknikal Malaysia Melaka, Malaysia)
(6) Muhammad Faizal Mail (Universitas Mandiri, Indonesia)
*corresponding author


Monitoring water media in Guppy fish farming is a major problem that must be solved. monitoring is carried out to obtain a decision whether the media is suitable or not suitable for getting good guppy fish.This study aims to extract knowledge in order to make decisions on the quality of Guppy fish water media through data obtained from the IoT system.The main contribution of this research is the effort to obtain new knowledge from data collected through IoT systems. New knowledge is obtained from water quality parameter data acquired by sensors of temperature, water level and pH. data from the sensor is sent to the Thingspeak cloud application via the microcontroller module. Data from the cloud is extracted into new knowledge in the form of decision-making rules for the quality of Guppy fish water media. To validate the method used, an analysis was performed using a confusion matrix in the rapidminer application. tested for the C 4.5 method and the Naive Bayes method

The results obtained the same high accuracy of 100 percent. It is possible that this IoT system can be applied in a larger scope, for example monitoring the aquariums of various Guppy fish farming communities in a city, so that real time data on the quality of Guppy fish is obtained within the scope of Smart City.


Internet of Things, Decision Three, C 4.5 Algorithm, Guppy, ESP8266



Article metrics

10.29099/ijair.v6i2.387 Abstract views : 157 | PDF views : 50




Full Text



DKP-LIPI, “DKP-LIPI Kembangkan Ikan Hias DKP-LIPI, 2008,” Ber. online LIPI, no. September 2008, p. 2008, 2008, [Online]. Available:

Kompas, “Ikan Guppy Air Tawar Hidup di Kepulauan Terisolasi, Dari Mana Asalnya?,” Media online kompas, no. 29 Maret 2018, 2018, [Online]. Available:

Y. K. PANJAITAN, S. SUCAHYO, and F. S. RONDONUWU, “Guppy fish (Poecilia reticulata Peters) population structure in Gajah Putih River, Surakarta, Central Java,” Bonorowo Wetl., vol. 6, no. 2, pp. 103–109, 2016, doi: 10.13057/bonorowo/w060204.

Aini, “Perjalanan Gupi Hingga ke Indonesia Gupi , si Million Fish Tidak Hanya di Indonesia , Gupi Populer di Seluruh Dunia,” media online boombastis, 2017.

B. Kiswanto, “SIFT19, Indonesia Sebagai Barometer Produksi Ikan Guppy Dunia,” 2019.

R. . Matondang, A.H, Basuki, F., dan Nugroho, “Pengaruh Lama Perendaman Induk Betina Dalam Ekstrak Purwoceng (Pimpinela Alpina) Terhadap Maskulinisasi Ikan Guppy (Poecilia Reticulata),” J. Aquac. Manag. Technol., vol. 6, no. 1, pp. 10–17, 2018.

M. Ambari, “Sudah Tahu Permasalahan yang Hambat Perkembangan Ikan Hias di Indonesia ?,” no. November, 2016.

K. Heineman, “Kendala Budidaya guppy,” 2017.


A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari, and M. Ayyash, “Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications,” IEEE Commun. Surv. Tutorials, vol. 17, no. 4, pp. 2347–2376, 2015, doi: 10.1109/COMST.2015.2444095.

P. Asghari, A. M. Rahmani, and H. H. S. Javadi, “Internet of Things applications: A systematic review,” Comput. Networks, vol. 148, pp. 241–261, 2019, doi: 10.1016/j.comnet.2018.12.008.

V. Mohammadi, A. M. Rahmani, A. M. Darwesh, and A. Sahafi, “Trust-based recommendation systems in Internet of Things: a systematic literature review,” Human-centric Comput. Inf. Sci., vol. 9, no. 1, 2019, doi: 10.1186/s13673-019-0183-8.

K. Pardini, J. J. P. C. Rodrigues, S. A. Kozlov, N. Kumar, and V. Furtado, “IoT-based solid waste management solutions: A survey,” J. Sens. Actuator Networks, vol. 8, no. 1, 2019, doi: 10.3390/jsan8010005.

J. Souifi, Y. Bouslimani, M. Ghribi, A. Kaddouri, T. Boutot, and H. H. Abdallah, “Smart Home Architecture based on LoRa Wireless Connectivity and LoRaWAN® Networking Protocol,” pp. 95–99, 2020, doi: 10.1109/ccssp49278.2020.9151815.

F. Budiman, M. Rivai, and M. A. Nugroho, “Monitoring and Control System for Ammonia and pH Levels for Fish Cultivation Implemented on Raspberry Pi 3B,” Proc. - 2019 Int. Semin. Intell. Technol. Its Appl. ISITIA 2019, pp. 68–73, 2019, doi: 10.1109/ISITIA.2019.8937217.

M. Cordova-Rozas, J. Aucapuri-Lecarnaque, and P. Shiguihara-Juarez, “A Cloud Monitoring System for Aquaculture using IoT,” SHIRCON 2019 - 2019 IEEE Sci. Humanit. Int. Res. Conf., pp. 2–5, 2019, doi: 10.1109/SHIRCON48091.2019.9024849.

S. Gong, A. Angani, and K. J. Shin, “Realization of fluid flow control system for vertical recycling aquatic system (VRAS),” Proc. - 2018 Int. Symp. Comput. Consum. Control. IS3C 2018, pp. 185–188, 2019, doi: 10.1109/IS3C.2018.00054.

Z. Jiangbin, C. Rui, Z. Hao, Z. Lei, and M. Chunyan, “Intelligent fish tank control system based on internet of things cloud computing platform,” ACM Int. Conf. Proceeding Ser., 2018, doi: 10.1145/3284557.3284737.

Y. Kim, N. Lee, B. Kim, and K. Shin, “Realization of IoT based fish farm control using mobile app,” Proc. - 2018 Int. Symp. Comput. Consum. Control. IS3C 2018, pp. 189–192, 2019, doi: 10.1109/IS3C.2018.00055.

C. Buratti, A. Conti, D. Dardari, and R. Verdone, “An overview on wireless sensor networks technology and evolution,” Sensors, vol. 9, no. 9, pp. 6869–6896, 2009, doi: 10.3390/s90906869.

Y. B. Lin and H. C. Tseng, “FishTalk: An IoT-Based Mini Aquarium System,” IEEE Access, vol. 7, no. c, pp. 35457–35469, 2019, doi: 10.1109/ACCESS.2019.2905017.

Periyadi, G. I. Hapsari, Z. Wakid, and S. Mudopar, “IoT-based guppy fish farming monitoring and controlling system,” Telkomnika (Telecommunication Comput. Electron. Control., vol. 18, no. 3, pp. 1538–1545, 2020, doi: 10.12928/TELKOMNIKA.v18i3.14850.

A. Z. Z. Abidin and N. A. A. Saragih, “SISTEM MONITORING KANDANG BURUNG PUYUH BERBASIS INTERNET OF THINGS PADA PLATFORM NODE-RED MENGGUNAKAN METODE NAIVE BAYES,” J. Teknol. Inf. dan Komun., vol. 2507, no. February, pp. 1–9, 2020, [Online]. Available:

A. Z. Z. Abidin, “Implementasi Algoritma C 4.5 Untuk Menentukan Tingkat Bahaya Tsunami,” Semin. Nas. Inform. 2011 (semnasIF 2011), vol. 2011, no. semnasIF, pp. 29–36, 2011, [Online]. Available:

A. Ramadhanu, S. Defit, and S. W. Kareem, “Hybrid Data Mining with the Combination of K-Means Algorithm and C4.5 to Predict Student Achievement,” Int. J. Artif. Intell. Res., vol. 5, no. 2, pp. 180–189, 2021, doi: 10.29099/ijair.v6i1.225.

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


International Journal Of Artificial Intelligence Research

Organized by: Departemen Teknik Informatika STMIK Dharma Wacana
Published by: STMIK Dharma Wacana
Jl. Kenanga No.03 Mulyojati 16C Metro Barat Kota Metro Lampung
phone. +62725-7850671
Fax. +62725-7850671
Email: |

View IJAIR Statcounter

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.