Crop Analysis and Profit Prediction using Data Mining Techniques (Id:39)

Crop Analysis and Profit Prediction using Data Mining Techniques (Id:39)

Special Issue – 2019 International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 RTESIT – 2019 Conference Proceedings Crop Analysis and Profit Prediction using Data Mining Techniques (Id:39) Akshatha Shailesh Shetty S Dept. of Computer Science & Engineering Asst. Prof. Dept of Computer Science Sahyadri College of Engineering, Sahyadri College of Engineering, Mangalore Mangalore Anet P James Athira M Saseendran Dept. of Computer Science & Engineering Dept. of Computer Science & Engineering Sahyadri College of Engineering, Sahyadri College of Engineering, Mangalore Mangalore Chaitra M Poojary Dept. of Computer Science & Engineering Sahyadri College of Engineering, Mangalore AbstractFarmers are the backbone of our country. They which can be used to solve a problem for the organizations cultivate different varieties of crops. In some cases it is difficult growth. As an instance, classification technique of ID3 for the farmers to get back the contributed amount from the algorithm approach is used for predicting the crops. ID3 is a harvest due to the market value of the yield. Farmers will not scientific calculation used to produce a decision tree from a realize the market value until they bring the crops to the market given dataset by utilizing a top down, avaricious inquiry to test which makes them to battle a great deal. These crop rates can be each quality at each hub of the tree. controlled if there is a system which helps the farmers to know about the crops planted around his location with prediction to suggest the farmers about the crops to be cultivated to maximize India’s sixty percent of the regions are arable. India is second profit. In this paper a system is been proposed which will gather guiding nation with reference to the total cultivable land, yet information about all the crops that are cultivated from different the greater part of the farmers are not getting the assessed places around the state so that the farmers can use the system to harvest yield because of a several reasons . The crop yield for know about the on growing crop details and to predict the best the most part relies upon the climate condition, area, soil type. crop that allows him to get more profit. This system uses various Crop yield figure is a huge cultivating issue. Each cultivator is criteria such as place, population, crop type, soil type, stock, worried about deliberate, how much gather he is going to current requirement, season, number of farmers cultivating the anticipate. This paper centers around investigation of rural same crop, crop duration etc to predict the crop for farmers. information utilizing data mining systems to foresee the best KeywordsDatamining, ID3, agriculture, classification harvest and whether the yield is productive or not. The remainder of the paper is sorted out as pursues: Section-2 I. INTRODUCTION exhibits the Background and Related Work, Section-3 shows Farmers and agricultural businesses need to settle on various the Methods, Section-4 displays the Results and Section-5 choices consistently in agriculture area and tangled introduces the Conclusion. complexities requires the different variables impacting them. Agriculture has been a show focus for information mining. II. BACKGROUND AND RELATED WORK Atmospheric conditions, changeability in the soil, input levels, combinations and stock expense made it even more relevant A. Classification for farmers to utilize data and get help to settle on basic Classification is an information mining capacity that relegates cultivating choices. things in an accumulation to target classifications or classes. The objective of characterization is to precisely anticipate the Data mining is defined as a process of checking large pre- objective class for each case in the information. existing datasets to produce new information. It implies that usable data is extracted from larger dataset and examined B. Related Work through applied technique. As the evolution of technology, the intense use of technology has increased which leads to interest Agriculture is an economic sector which plays an important in data mining concept tremendously. Data mining techniques role in the socio-economic fabric of India. The classification are used by organizations to evaluate their ongoing of soil into low, medium and high categories are done by functionalities. Data mining authorizes the collection of huge adopting data mining techniques in order to predict the crop data in faster manner. The most significant challenges are to yield using available dataset [1]. The improvement in yields analyze the data and provide meaningful extraction of data expectation by past agriculture data. It additionally portrays Volume 7, Issue 08 Published by, www.ijert.org 1 Special Issue – 2019 International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 RTESIT – 2019 Conference Proceedings the determination of best yield contingent upon the climate system by the farmer. The system analyses the crop circumstance and gives expected data to favour the reasonable information along with the trained dataset. This gives the season to do magnificence cultivating [2]. The soil fruitfulness output whether the crop is adaptable or not. The obtained is resolved utilizing sensor and proposes which crop must be output is analyzed using profit parameters to predict whether planted and furthermore it predicts the harvest yield. Data the crop is profitable or not. The system architecture is shown about the harvest is as graph. It likewise proposes the compost in Fig. 3.2. which must be added to the soil to build the soil richness [3]. The issue of the farmers has been tended to through accuracy farming. Exactness horticulture is a cutting edge cultivating strategy that utilizes look into information of soil attributes, soil types, crop yield information accumulation and proposes the farmers the correct harvest dependent on their site explicit parameters [4]. The stock pattern forecast utilizing regression analysis. Financial exchange forecast with the assistance of relapse examination is the most productive mix to foresee the stocks and the states of the market. The advancement of an energetic application for examining and anticipating securities exchange costs [5]. The regular issue existing among the Indian farmers are they don’t pick the correct yield dependent on their soil prerequisites. Because of this they face a genuine mishap in efficiency. This issue of the farmers has been resolved to through precision agriculture. [6]. The spotlights on expectation of rice crop yield amid monsoon season dependent on the recorded rural dataset of semi-bone-dry climatic zone. [7]. III. METHODOLOGY The system architecture consists of two phases. In the first phase the farmer needs to enter the list of crops along with the location. The system takes in account the factors like temperature, humidity, water level and soil type for that Fig. 3.2. System Architecture location and then predicts the best crops that can be grown in the area. This analysis is done using ID3 algorithm. IV. RESULTS In the second phase the best crops obtained from the phase The parameters of three regions namely Bantwal, one are further analyzed using the ongoing crop details, current Belthangady, Mangaluru are updated. Farmer enters the crop stock, population and season which tells us whether the crop is name, area of cultivation, land size and season. The updated profitable or not. Hobliwise & Grama Panchayat wise crop area details of the crop parameters could be viewed by the farmer. statistics 2015-16 is used as the dataset fr training the system. The sample outcome of the Proposed project is shown in the below figure. A. ID3 Algorithm Fig 3.1. ID3 algorithm Fig 4.1. Result showing the profitable crop B. Working The result shows that which crop can be cultivated during a The system is trained and updated by using the crop particular season. It also shows whether cultivating the parameters and profit parameters. The farmer needs to register particular crop is profitable or not for the farmer. The system in order to access the information. is very helpful so that the farmer can take a decision. Therefore farmer is authenticated each time he logins to the system. The crop name and location is given as input to the Volume 7, Issue 08 Published by, www.ijert.org 2 Special Issue – 2019 International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 RTESIT – 2019 Conference Proceedings CONCLUSION [4] S.Pudumalar, E.Ramanujam, R.Harine Rajashree, C.Kavya, T.Kiruthika, J.Nisha Crop Recommendation System for Precision Agriculture IEEE The project aids the farmers in deciding which crop to be Eighth International conference on Advanced computing on 2016. grown in a particular area during a specific period of time and [5] S Abdulsalam Sulaiman Olaniyi, Adewole, Kayode S, Jimoh R G Stock predict whether it is profitable or not. It provides the details trend prediction using Regression analysis -Data mining technique 2010-11 by stating whether the crop is profitable or not. Hence this [6] S.Pudumalar, E.Ramanujam, R.Harine Rajashree, C.Kavya, T.Kiruthika, system helps farmers to preserve their time by aiding them in J.Nisha Crop Recommendation System for Precision Agriculture decision making process. IEEE Eighth International conference on Advanced computing on 2016. [7] Niketa Gandhi, Leisa J. Armstrong, Manisha Nandawadekar REFERENCES Application of data mining techniques for predicting rice crop yield in [1] Monali Paul, Santosh K Viishwakarma, Ashok Verma Analysis of soil semi-Arid climatic zone of India IEEE International Conference on Behaviour and Prediction of Crop Yielding using Data Mining Approach Technology Innovations in ICT For Agriculture and Rural Development International conference on, 2015. on 2017. [2] R Sujatha A Study on Crop Yield Forecasting Using Classification Techniques IEEE conference on, 2016. [3] N. Hemageetha A Survey on Application of Data Mining Techniques to Analyze the Soil for Agricultural Purpose IEEE conference on, 2016. Volume 7, Issue 08 Published by, www.ijert.org 3