Prediction of Crop, Fertilizer and Disease Detection for Precision Agriculture

2021 ◽  
Vol 9 (10) ◽  
pp. 26-30
Author(s):  
Bharathi C
Keyword(s):  
Data Mining ◽  
Pest Control ◽  
Precision Agriculture ◽  
Recommendation System ◽  
Infected Leaf ◽  
Crop Choice ◽  
Fertilizer Recommendation ◽  
Modern Technique ◽  
Using Data ◽  
The Right

Abstract: The main walk of life of our Country is Agriculture. More than 70 % of the population’s lives depend upon agriculture. It is also a great source of country’s economy. In order to make this filed more profitable for farmers proper crops have to be grown in their fields. The prevalent problem among the farmers is Crop choice depending upon the soil in their farmlands. Another challenge faced by farmers is choosing the right fertilisers for their crops, which plays a very important role in getting a good and profitable yield. There is another major problem which they have to give more attention is the pest control or the diseases to which the plants may limit their growth. The above listed problems may solved using the advanced techniques of Precision Agriculture and data mining. Precision Agriculture is modern technique which can be used for farming. The main objective of is to solve above problems using data mining techniques and build a decision system which would help farmers to choose right crops for their farm , fertiliser recommendation for the crops grown and also to help the farmers in detecting the diseases by using the infected leaf images.. Keywords: Precision Agriculture, Data Mining, Crop, fertilizer recommendation system, ML Algorithms

scholarly journals Online Fertilizer Recommendation System (OFRS): A Step Towards Precision Agriculture And Optimized Fertilizer Usage By Smallholder Farmers In Bangladesh

2020 ◽  
Vol 1 (4) ◽  
Author(s):  
M. A. Hossain ◽  
M. N. A. Siddique
Keyword(s):  
Precision Agriculture ◽  
Recommendation System ◽  
Smallholder Farmers ◽  
Fertilizer Application ◽  
Soil Test ◽  
Total Production ◽  
Soil Database ◽  
Fertilizer Recommendation ◽  
Fertilizer Recommendations ◽  
Input Cost

The recent progression and Green Revolution (approx. between the 1990s-2010s) in agriculture of Bangladesh resulted in an increase of total production despite yield-gap to ensure food security. But agriculture in Bangladesh is still backed-up by higher use of inputs (agrochemicals-fertilizers, pesticides; modern varieties, irrigation etc.) and inversion tillage. This conventional agrochemical-based smallholder agriculture may lead to soil and environmental degradation, soil acidification, and a decline in soil fertility. Therefore, it is significant to optimize input application in intensive agriculture, especially fertilizers. This paper introduces the potential online facilities of generating online fertilizer recommendations for smallholder farmers in Bangladesh to ensure proper usage of fertilizers and enable sustainable agricultural production. We also highlighted how the usage of fertilizers increased with an increase in total production over time. But the sustainability of production in the years to come still remain challenging. With the aim of sustainable crop production, reduction in the misuse of fertilizers and reduction of input cost by optimizing the present pattern of excessive fertilizer application, the Soil Resource Development Institute (SRDI) provides location-specific fertilizer recommendation through both the manual and soil test based interpretation of plant nutrients: soil database in Upzazila Nirdeshika and static laboratory soil analysis. Recently, SRDI developed web-based software named Online Fertilizer Recommendation System (OFRS). The system is capable of generating location-specific fertilizer recommendations for selected crops by analyzing the national soil database developed by this governmental institute. The software requires farmer field location, respective soil and land type, and crop type and variety information to generate crop-specific instant fertilizer recommendation. It was observed that by using fertilizer according to the recommended dose calculated on the basis of soil test values, farmers could harvest approx. 7-22% higher yield of different crops over usual farmers practice. If this system can be popularized and disseminated by effective agricultural extension, this would immensely contribute to the promotion of precision agriculture, input cost reduction and it would certainly enable us to optimize fertilizer application by the smallholder farmers in Bangladesh.

Human Talent Forecasting using Data Mining Classification Techniques

2012 ◽  
pp. 261-274
Author(s):  
Hamidah Jantan ◽  
Abdul Ali Hamdan ◽  
Zulaiha Othman
Keyword(s):  
Data Mining ◽  
Human Resource ◽  
Talent Management ◽  
Past Experience ◽  
Classification Task ◽  
Close Attention ◽  
Classification Techniques ◽  
Useful Knowledge ◽  
Using Data ◽  
The Right

Talent management is a very crucial task and demands close attention from human resource (HR) professionals. Recently, among the challenges for HR professionals is how to manage organization’s talents, particularly to ensure the right job for the right person at the right time. Some employee’s talent patterns can be identified through existing knowledge in HR databases, which data mining can be applied to handle this issue. The hidden and useful knowledge that exists in databases can be discovered through classification task and has been widely used in many fields. However, this approach has not successfully attracted people in HR especially in talent management. In this regard, the authors attempt to present an overview of talent management problems that can be solved by using this approach. This paper uses that approach for one of the talent management tasks, i.e., predicting potential talent using previous existing knowledge. Future employee’s performances can be predicted based on past experience knowledge discovered from existing databases by using classification techniques. Finally, this study proposes a framework for talent forecasting using the potential Data Mining classification techniques.

Human Talent Forecasting using Data Mining Classification Techniques

2012 ◽  
pp. 486-499
Author(s):  
Hamidah Jantan ◽  
Abdul Razak Hamdan ◽  
Zulaiha Ali Othman
Keyword(s):  
Data Mining ◽  
Human Resource ◽  
Talent Management ◽  
Past Experience ◽  
Classification Task ◽  
Close Attention ◽  
Classification Techniques ◽  
Useful Knowledge ◽  
Using Data ◽  
The Right

Talent management is a very crucial task and demands close attention from human resource (HR) professionals. Recently, among the challenges for HR professionals is how to manage organization’s talents, particularly to ensure the right job for the right person at the right time. Some employee’s talent patterns can be identified through existing knowledge in HR databases, which data mining can be applied to handle this issue. The hidden and useful knowledge that exists in databases can be discovered through classification task and has been widely used in many fields. However, this approach has not successfully attracted people in HR especially in talent management. In this regard, the authors attempt to present an overview of talent management problems that can be solved by using this approach. This paper uses that approach for one of the talent management tasks, i.e., predicting potential talent using previous existing knowledge. Future employee’s performances can be predicted based on past experience knowledge discovered from existing databases by using classification techniques. Finally, this study proposes a framework for talent forecasting using the potential Data Mining classification techniques.

scholarly journals Effectively Optimizing the Patterns with Dynamic Behaviors of the Transactions by using Data Mining Tool

2019 ◽  
Vol 8 (12) ◽  
pp. 2312-2316
Keyword(s):  
Data Mining ◽  
Reaction Time ◽  
Market Basket ◽  
Data Mining Tool ◽  
Testing Issue ◽  
Mining Tool ◽  
Test Investigation ◽  
Using Data ◽  
The Right ◽  
Time Information

Basic management and understanding the conducted of the client has turned out to be indispensable and testing issue for associations to continue their situation in the focused markets. Mechanical advancements have cleared leap forward in quicker handling of questions and sub-second reaction time. Information mining devices have turned out to be surest weapon for breaking down colossal measure of information and leap forward in settling on right choices. The target of this paper is to break down the colossal measure of information subsequently abusing the buyer conduct and settle on the right choice prompting aggressive edge over adversaries. Test investigation has been done utilizing affiliation principles utilizing Market Basket examination toward demonstrate its value more the regular systems.

scholarly journals Determining and Clustering Potential Legislative Candidate in West Java District Using K-Nearest Neighbors Algorithm

2017 ◽  
Vol 2 (4) ◽  
pp. 35
Author(s):  
Faiza Renaldi ◽  
Alfin Dhuhawan Bagja ◽  
Gunawan Abdillah
Keyword(s):  
Data Mining ◽  
Party System ◽  
Nearest Neighbors ◽  
General Election ◽  
West Java ◽  
K Nearest Neighbors ◽  
Members Of Parliament ◽  
Public Figures ◽  
Using Data ◽  
The Right

Indonesia held its first general election in 1955 to elect legislatures from all provinces. The latest was held in 2014, which elected 560 members to the People's Representative Council (Dewan Perwakilan Rakyat, DPR) and 128 to the Regional Representative Council (Dewan Perwakilan Daerah, DPD). The PRC was elected by proportional representation from multi-candidate constituencies/districts. Currently, there are 77 constituencies in Indonesia, each of which returns 3-10 Members of Parliament based on population. Under Indonesia's new multi-party system, no party has been able to secure an outright victory; hence, selecting the right candidate for the right constituencies has been a major effort for all participating parties. Many combinations have been tried; popularities, intelligence, public figures, ‘putera daerah’ are all variables that can only show a fraction of winning pattern where no general conclusion can be drawn. This research used data mining techniques to create an unfound pattern, and to suggest which particular legislative candidate is most suitable for which constituency. Using 11 West Java constituencies (11 clusters), K-Nearest Neighbors (K-NN) algorithms, we found out that an 83.33% accuracy using data from 2014 general election.

Customer Relationship Management Using Data Mining Model

2019 ◽  
Vol 118 (7) ◽  
pp. 95-100
Author(s):  
S. Balamurugan ◽  
Dr.M. Selvalakshmi
Keyword(s):  
Data Mining ◽  
Customer Behavior ◽  
Customer Relationship ◽  
Customer Profitability ◽  
Different Types ◽  
Classification Prediction ◽  
Using Data ◽  
The Right ◽  
Mining Model ◽  
Common User

The paper describes marketing insights from Data Mining about new promotions to create, focus on profitability and emphasis on the most profitable promotion that could be sent. The paper shows about the development of predictive modeling, from data mining which provides insights into future customer behavior and customer profitability. Data Mining provides a blueprint and how to define and use customer profile. It shows how to acquire new customers in the most profitable way possible and retain profitable customers. Data mining is an effective method to target at risk-customers with the right marketing promotion and services to keep them loyal. The paper discusses the number of data mining techniques with reference to customer retention for mobile phones (CART, Rule inductions, Ann etc) with a common user interface that the tool can support, an ability to support a number of different types of analysis including classification, prediction, and association detection.

scholarly journals Using data mining to identify factors that influence the degree of leg injuries in broilers

2012 ◽  
Vol 32 (4) ◽  
pp. 642-649 ◽  
Author(s):  
Alexandra F. da S. Cordeiro ◽  
Marta dos S. Baracho ◽  
Irenilza de A. Nääs ◽  
Guilherme R. do Nascimento
Keyword(s):  
Data Mining ◽  
Vitamin D ◽  
Control Group ◽  
Data Set ◽  
Leg Injuries ◽  
Leg Weakness ◽  
Gait Score ◽  
The Asymmetry ◽  
Using Data ◽  
The Right

Locomotor problems prevent the bird to move freely, jeopardizing the welfare and productivity, besides generating injuries on the legs of chickens. The objective of this study was to evaluate the influence of age, use of vitamin D, the asymmetry of limbs and gait score, the degree of leg injuries in broilers, using data mining. The analysis was performed on a data set obtained from a field experiment in which it was used two groups of birds with 30 birds each, a control group and one treated with vitamin D. It was evaluated the gait score, the asymmetry between the right and left toes, and the degree of leg injuries. The Weka ® software was used in data mining. In particular, C4.5 algorithm (also known as J48 in Weka environment) was used for the generation of a decision tree. The results showed that age is the factor that most influences the degree of leg injuries and that the data from assessments of gait score were not reliable to estimate leg weakness in broilers.

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