Make Graph to Simple Linear Regression, y=laba; x=keuntungan.

linearRegressionSederhana.py

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import style
style.use("ggplot")
keuntungan = [7000000, 10000000, 7500000, 5000000, 17000000, 7000000, 14000000]
laba = [3000000, 4000000, 2000000, 1200000, 5000000, 2000000, 5000000]

def linearRegresion(data):
	'''
		indeks[0] -> response variable -> x
		indeks[1] -> predictor variable -> y
	'''
	x2=[]
	y2=[]
	xy=[]
	n = len(data[0])

	for x in data[0]:
		x2.append(x**2)

	for y in data[0]:
		y2.append(y**2)

	i=0;
	while(i<n):
		dump = data[0][i]*data[1][i]
		xy.append(dump)
		i+=1
	jmlhx = sum(data[0])
	jmlhy = sum(data[1])
	jmlhx2 = sum(x2)
	jmlhy2 = sum(y2)
	jmlhxy = sum(xy)

	a = ((jmlhy*jmlhx2)-(jmlhx*jmlhxy))/(n*jmlhx2-(jmlhx**2))
	b = ((n*jmlhxy)-(jmlhx*jmlhy))/(n*jmlhx2-(jmlhx**2))

	return(a,b)

def gambarGrafik(dataProses):
	a,b = linearRegresion(dataProses)
	print("Nilai a adalah %.4f"%(a))
	print("Nilai b adalah %.4f"%(b))
	def f1(keanggotaan,a,b):
		hit = []
		for x in keanggotaan:
			y = b*x+a
			hit.append(y)
		return(hit)
	plt.scatter(dataProses[0],dataProses[1],label='data aktual',s=10)
	plt.plot(dataProses[0],f1(dataProses[0],a,b),c='k',label='hasil regresi without',linewidth=0.5)
	plt.title("Hasil regresi Linear Sederhana")
	plt.ylabel("laba")
	plt.xlabel("keuntungan")
	plt.legend()
	fig = plt.figure(1)
	fig.canvas.set_window_title("regresi by sufyan97")
	plt.show()

gambarGrafik([keuntungan,laba])