WordFreq.java Analisis sentimen data twitter menggunakan K-Means Clustering.

135 } public LinkedHashMap readTweetsFromCSVString csvFile { LinkedHashMapInteger, ArrayListString map = null; ArrayListString sToken; try { create BufferedReader to read csv file BufferedReader br = new BufferedReadernew FileReadercsvFile; String line = ; StringTokenizer st = null; map = new LinkedHashMap; int lineNumber = 0; read comma separated file line by line while line = br.readLine = null { lineNumber++; use comma as token separator st = new StringTokenizerline, ,; sToken = new ArrayList; while st.hasMoreTokens { String token = st.nextToken; sToken.addtoken; } map.putlineNumber, sToken; } } catch Exception e { System.err.printlnCSV file cannot be read : + e; } 136 return map; } public void writeFreqToCSVLinkedHashMapString, Integer input, String filename throws IOException { StringBuilder builder = new StringBuilder; for IteratorMap.EntryString, Integer it = input.entrySet.iterator; it.hasNext; { Map.EntryString, Integer e = it.next; String key = e.getKey; Integer value = e.getValue; builder.appendkey; builder.append,; builder.appendvalue; builder.appendSystem.getPropertyline.separator; } String result = builder.toString; System.out.printlnresult; try Writer writer = new FileWriterfilename { writer.writeresult; writer.close; } } public LinkedHashMap readFreqFromCSVString csvFile { LinkedHashMapString, Integer map = null; ArrayListString sToken; try { create BufferedReader to read csv file BufferedReader br = new BufferedReadernew FileReadercsvFile; String line = ; StringTokenizer st = null; 137 map = new LinkedHashMap; int lineNumber = 0; read comma separated file line by line while line = br.readLine = null { lineNumber++; use comma as token separator st = new StringTokenizerline, ,; sToken = new ArrayList; while st.hasMoreTokens { String token = st.nextToken; sToken.addtoken; } map.putsToken.get0, Integer.parseIntsToken.get1; } } catch Exception e { System.err.printlnCSV file cannot be read : + e; } return map; } }

11. KmeansClustering.java

package sentimentanalysis; import java.util.; public class KmeansClustering {