Penerapan Data Mining Untuk Prediksi Perkiraan Hujan dengan Menggunakan Algoritma K-Nearest Neighbor

نویسندگان

چکیده

Rain is a condition where water droplets fall from clouds to the earth. In life, presence of rain highly anticipated, can help people who have profession as farmers. that occurs on large scale will really provide obstacles for community, in addition hampering activities or especially those carried out outdoor also cause disaster community form flooding. Estimating very important, knowing whether it not make easier anticipate possibilities may occur due rain. However, process delivering forecasts, there often an uneven distribution information and delays conveying public regarding occur. The should be able independently predict Data processing done properly correctly. mining way assist data processing. this study, settlement using K-Nearest Neighbor (K-NN) algorithm. results obtained show testing decision NO. other words, algorithm problem solving

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Multidimensi Pada Data Warehouse Dengan Menggunakan Rumus Kombinasi

Multidimensional in data warehouse is a compulsion and become the most important for information delivery, without multidimensional data warehouse is incomplete. Multidimensional give the able to analyze business measurement in many different ways. Multidimensional is also synonymous with online analytical processing (OLAP).

متن کامل

Validasi data dengan menggunakan objek lookup pada borland delphi 7.0

s: Developing an application with some tables must concern the validation of input (scpecially in Table Child). In order to maximize the accuracy and input data validation. Its called lookup (took data from other dataset). There are 2 (two) ways to lookup data from Table Parent: 1) Using Objects (DBLookupComboBox & DBLookupListBox), or 2) Arranging The Properties Of Fields Data Type (shown by u...

متن کامل

k-Nearest Neighbor Classification on Spatial Data

Classification of spatial data streams is crucial, since the training dataset changes often. Building a new classifier each time can be very costly with most techniques. In this situation, k-nearest neighbor (KNN) classification is a very good choice, since no residual classifier needs to be built ahead of time. KNN is extremely simple to implement and lends itself to a wide variety of variatio...

متن کامل

K-Nearest Neighbor Classification Using Anatomized Data

This paper analyzes k nearest neighbor classification with training data anonymized using anatomy. Anatomy preserves all data values, but introduces uncertainty in the mapping between identifying and sensitive values. We first study the theoretical effect of the anatomized training data on the k nearest neighbor error rate bounds, nearest neighbor convergence rate, and Bayesian error. We then v...

متن کامل

FUZZY K-NEAREST NEIGHBOR METHOD TO CLASSIFY DATA IN A CLOSED AREA

Clustering of objects is an important area of research and application in variety of fields. In this paper we present a good technique for data clustering and application of this Technique for data clustering in a closed area. We compare this method with K-nearest neighbor and K-means.  

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Building of Informatics, Technology and Science (BITS)

سال: 2022

ISSN: ['2684-8910', '2685-3310']

DOI: https://doi.org/10.47065/bits.v4i3.2564