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Testimonial

We saying thank you for your visiting in our website. Best wishes to us all, we hope we all will be successful in carrying out daily activities. This website is portfolio of developer were created as a means to introduce themselves, share sience and technology and receive software maker service. I hope you are satisfied with the services our provide.

Services

Website Maker

Serving the website maker services for personal websites, bussiness and government.

Desktop Application

Serving the application maker services for desktop based in many language programming such as VB, Java, C/C++ and etc.

Microcontroller System

Serving the microcontroller system based arduino service, such as automatic control home device using mobile device and internet.

Image

Many project in succesful finish including simple search engine prophet and messengers story project, implementation of K-Means and KNN algorithm in Java.

# Project

About Me

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Depandi Enda or better known as Depandi is one of the students of the D4 Technical Information Electronic Engineering Polytechnic Institute of Surabaya who have a hobby in the field of robotics and programming, was born in Bagansiapiapi on May 22, 1990. Starting in Vocational High School education Ujang Khalijah (2005-2008) and continuing vocational education studies at the Polytechnic Bengkalis (2011-2014). Until now still continued his studies in PENS.

Motivation : Life is full of challenges, if you are weak you will be crushed and if you powerful you will find the solution of any trials you found. Motto : business and prayer is a thing that should run parallel for reaching for the bright future.

 

Skill

  • Java / Javascript80%
  • HTML5 / CSS90%
  • PHP80%
  • C/C++70%
  • Database (MySQL/Oracle)70%

My Work

Project #1

Simple search engine prophets and messengers story in (Indonesian) is a search engine that will find keywords that are searched in a document format (.txt). This search engine is the implementation of text mining stages comprising stages (Tokenizing, Filtering, Stemming, Tagging and Anlyzing). This search engine uses Sastrawi library to stemming process and TF-IDF algorithm for assessment based on common documents with keywords. I hope you are satisfied with this simple search engines.


Simple Search Engine 25 Prophet and Messenggers Story
Text Mining Stages(Tokenizing, Filtering, Stemming, Tagging, Analyzing)
Input your keywords in (Indonesian) below this Text Field !
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References

Text Mining.pdf →


Project #2

Correlation Measurement in Data Mining (Case Study Early Diagnosis of Kidney Disease Symptoms). The project is implemented on Android mobile devices. Techniques used to measure the level of similarity between symptoms data and deases is cosine metric. This technique will provide relevant diagnosis of the symptoms being felt by the patient. The greater the level of confidence in the results of diagnosis, then greater the accuracy of the patient suffering from a particular disease...

Read More →


Project #3

Content Based Image Retrieval (CBIR) Using Colour Detect System. This Project is implementation of CBIR technical using colour extraction. This image will be retrieved by colour similiarity of image. This project using 130 bin colour detection with 1000 image sample in database. It's very simple you can choose 1 of 9 picture this below. You can get same colour of image at below this picture.

Content Based Image Retrieval (CBIR) Using Colour Feature
Please Select One Image For Samples Query !

References

Image Retrieval.pdf →


Project #4

Geographical Information System Project
Autonomous Mobile Robot Design using GPS Navigation for Disaster Area Mapping

As the development of information technology has helped many people in completing tasks and daily work. One of the fastest growing technology is robotics technology and location-based information system. In completing his duty robots are classified into three operating modes, namely, the manual robot (robot operated by human intervention), robot semi-autonomous (robot, whose work can be operated manually and automatically) and an autonomous robot (robot working alone without any interference human to operate it).

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Project #5

Machine Learning Project
K Nearest Neighbor Algorithm Implementation in java

K-Nearest Neighbour or KNN is one of the algorithms instance based learning or case-based reasoning. Case-based reasoning is another methodology for, among other things, identifying clusters of similiar events in large databases. K-nearest neighbor is a supervised learning algorithm where the results of a new instance of the categories classified by the majority of K-nearest neighbor. KNN is used in many applications of data mining, statistical pattern recognition, image processing, etc.

Guide

KNN Guide.pdf →

Java Application

KNN App.rar →

KNN Sample Dataset

KNN Dataset.rar →

References

KNN References.pdf →


Project #6

Machine Learning Project
K-Means Algorithm Implementation in java

Clustering defenition : Clustering is a method to determine which group the data based on specific criteria. K-Means clustering is a method for grouping items into k groups (where k is the number of groups desired). Group or cluster is formed by minimizing the amount of Euclidean distances) between the data center point (centroid) corresponding. Centroid is the central point of data, in this case we are assuming an average vector as a centroid.

Guide

K-Means Guide.pdf →

Java Application

K-Means App.rar →

K-Means Sample Dataset

K-Means Dataset.rar →

References

K-Means References.pdf →


Final Project

Wireless Sensor Network
Early Fire Detection System in Smart Home Monitoring Based Wireless Sensor Network

Utilization of wireless sensor network technology can improve the anticipation of the occurrence of fire hazards in the smart home, this is done by replacing the human task in monitoring the situation around the home by using multiple sensors which can directly interact with the environment. This study focuses on the early fire detection systems on smart home-based wireless sensor network monitoring. Sensors are used to detect the level of fire danger include temperature sensors, humidity, carbon monoxide and smoke. To improve the reliability and accuracy of the information provided for the system that was designed does not give any warning to users that use fuzzy logic inference systems to process the data from the four sensors...

Read More →

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