Smart Monitoring Agriculture Based on Internet of Things

Kurniawan, Fachrul; Nurhayati, Hani; Arif, Yunifa Miftachul; Harini, Sri; Nugroho, Supeno Mardi Susiki; Hariadi, Mochamad

doi:10.1109/eiconcit.2018.8878510

Cited by 10 publications

(7 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Artificial intelligence is also one of the elements in the Internet of Things (IoT) technology. Technology Internet of Things (IoT) is a phenomenon in which an entity has the ability to transmit data over a network without the need for human or human intervention to a device where data produced by the instruments (sensors) connected to the chosen object is generated [6]. One of the analysis methods found in data mining is classification.…”

Section: Master O F Informatics Engineering State Islamic University O F Maulana Malik Ibrahimmentioning

confidence: 99%

A Comparison of Naive Bayes Methods, Logistic Regression and KNN for Predicting Healing of Covid-19 Patients in Indonesia

Romadhon

Kurniawan

2021

2021 3rd East Indonesia Conference on Computer and Information Technology (EIConCIT)

Self Cite

View full text Add to dashboard Cite

Since it was declared a global pandemic by the World Health Organization (WHO), the number of cases of Covid-19 patients who died has continued to increase. One of the countries with the highest death rate in the world is Indonesia. On Saturday, April 4, 2020, Indonesia reached the highest death rate for Covid-19 patients, around 9.11%. This number must be suppressed so that there are no more victims. For this reason, it is necessary to know actually the factors that can reduce the risk of death and predict the chance of curing Covid-19 patients. In data mining, there are several methods that can be used to predict a patient's recovery rate by considering several variables. The variables used in this study were age and gender. Naive Bayes Method, logistic regression, and K-Nearest Neighbor (KNN) are the methods to be chosen in this study to analyze their most accurate performance. The result shows that KNN has the highest accuracy, which is 0.750 compared to logistic regression which has a value of 0.703 as well as Naive Bayes which has the same value. Meanwhile, the level of precision of the three models shows that KNN also has the highest value, namely 0.750 than logistic regression and Naive Bayes which have the same value, namely 0.700. The recall value of the three also shows that the kNN remains the highest with 0.750 compared to the two comparison models which have the same value, namely 0.708.

show abstract

Section: Master O F Informatics Engineering State Islamic University O F Maulana Malik Ibrahimmentioning

confidence: 99%

A Comparison of Naive Bayes Methods, Logistic Regression and KNN for Predicting Healing of Covid-19 Patients in Indonesia

Romadhon

Kurniawan

2021

2021 3rd East Indonesia Conference on Computer and Information Technology (EIConCIT)

Self Cite

View full text Add to dashboard Cite

show abstract

“…According to the dose [4]. Currently, the application of technology for rice fields is still being developed, however, according to direct reports from farmers in handling problems in paddy field processing using current technology, it is not yet empowered in terms of quality and quantity [5]- [11].…”

Section: Introductionmentioning

confidence: 99%

Internet of things implementation and analysis of fuzzy Tsukamoto in prototype irrigation of rice

Silalahi

Jatikusumo

Budiyanto

et al. 2022

IJECE

View full text Add to dashboard Cite

<span lang="EN-US">This research raises the topic of modern technology in the field of rice fields. The problem in this research is determining the fuzzy inference system algorithm for electronic engineering. The prototype was built by Raspberry Pi and python-based to the internet of things. The objective of this research is to design a new model for the rice field monitoring/control system and display every condition based on the internet of things. So that the hypothesis of this research can answer the phenomena that occur in rice fields, including drought problems, maintained plant conditions. The test results showed that irrigation control automatically runs optimally by scheduling, automatic irrigation control of water pH degree value detection analyzed by fuzzy Tsukamoto method at Z=3.5 defuzzification value for low and high irrigation control, and Z value=1.83 for normal irrigation control. Furthermore, the scheduling of spraying liquid fertilizer obtained the results of duration for 60 min in accordance with the needs of fertilizer dose. Lastly, for monitoring data on the website successfully accessed anywhere from the use of hosting servers and domains. Finally, it can be concluded that fuzzy Tsukamoto's algorithm is appropriate to be applied to the modern rice field system.</span>

show abstract

“…Irrigation is an effort to bring in water by designing irrigation canals to go to the fields or fields regularly and disposing of water that is no longer needed [4,5,6]. Rice fields/gardens need water flow, and water flow is obtained from river water flow or irrigation channel flow.…”

Section: Introductionmentioning

confidence: 99%

Design a Monitoring and Control in Irrigation Systems using Arduino Wemos with the Internet of Things

Silalahi

Budiyanto

Silaban

et al. 2021

JIAE

View full text Add to dashboard Cite

Irrigation door is a big issue for farmers. The factor that became a hot issue at the irrigation gate was the irresponsible attitude of the irrigation staff regarding the schedule of opening/closing the irrigation door so that it caused the rice fields to becoming dry or submerged. In this research, an automatic prototype system for irrigation system will be designed based on integrating several sensors, including water level sensors, soil moisture sensors, acidity sensors. This sensor output will be displayed on Android-based applications. The integration of communication between devices (Arduino Nano, Arduino Wemos and sensors supporting the irrigation system) is the working principle of this prototype. This device will control via an Android-based application to turn on / off the water pump, to open/close the irrigation door, check soil moisture, soil acidity in real time. The pump will automatically turn on based on the water level. This condition will be active if the water level is below 3cm above ground level. The output value will be displayed on the Android-based application screen and LCD screen. Based on the results of testing and analysis of the prototype that has been done in this research, the irrigation door will open automatically when the soil is dry. This condition occurs if the water level is less than 3 cm. The calibrated Output value, including acidity sensor, soil moisture sensor and water level sensor, will be sent to the server every 5 seconds and forwarded to an Android-based application as an output display.

show abstract

Smart Monitoring Agriculture Based on Internet of Things

Cited by 10 publications

References 10 publications

A Comparison of Naive Bayes Methods, Logistic Regression and KNN for Predicting Healing of Covid-19 Patients in Indonesia

A Comparison of Naive Bayes Methods, Logistic Regression and KNN for Predicting Healing of Covid-19 Patients in Indonesia

Internet of things implementation and analysis of fuzzy Tsukamoto in prototype irrigation of rice

Design a Monitoring and Control in Irrigation Systems using Arduino Wemos with the Internet of Things

Contact Info

Product

Resources

About