Publications by Dodi Taufik Hidayat UIN Maulana Malik Ibrahim Malang
analisis NLP dengan teknik sentiment analysis menggunakan paket tidytext
library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.2 ✔ readr 2.1.4 ## ✔ forcats 1.0.0 ✔ stringr 1.5.0 ## ✔ ggplot2 3.4.2 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0...
2215 sym R (1616 sym/13 pcs)
Analisis pada dataset AirPassengers dengan menambahkan beberapa langkah analisis, seperti dekomposisi musiman, tren, dan peramalan menggunakan model ARIMA.
library(forecast) ## Registered S3 method overwritten by 'quantmod': ## method from ## as.zoo.data.frame zoo library(ggplot2) decomposition <- stl(AirPassengers, s.window = "periodic") plot(decomposition) train_data <- window(AirPassengers, end = c(1958, 12)) test_data <- window(AirPassengers, start = c(1959, 1)) auto_arima <- ...
808 sym R (1186 sym/8 pcs) 2 img
analisis peramalan masa depan menggunakan dataset UKgas
library(forecast) ## Registered S3 method overwritten by 'quantmod': ## method from ## as.zoo.data.frame zoo library(ggplot2) # Memuat dataset UKgas data("UKgas") # Memisahkan data menjadi data latihan train_data <- window(UKgas, end = c(1991, 12)) ## Warning in window.default(x, ...): 'end' value not changed # Menentukan model...
870 sym R (1655 sym/8 pcs) 1 img
Analisis Klasifikasi Spesies Bunga Iris Menggunakan Random Forest
library(caret) ## Loading required package: ggplot2 ## Loading required package: lattice # Memuat dataset iris data(iris) # Memisahkan data menjadi variabel independen (x) dan variabel dependen (y) x <- iris[, 1:4] y <- iris[, 5] # Mengubah variabel dependen menjadi faktor y <- as.factor(y) # Membagi data menjadi data latih dan data uji ...
2193 sym R (1624 sym/13 pcs)
Analisis Klasifikasi Tingkat Kecerdasan Mahasiswa Menggunakan Naive Bayes pada Dataset ‘Iris’
library(e1071) library(ggplot2) library(iterators) library(timeDate) ## ## Attaching package: 'timeDate' ## The following objects are masked from 'package:e1071': ## ## kurtosis, skewness library(lifecycle) library(globals) library(pROC) ## Type 'citation("pROC")' for a citation. ## ## Attaching package: 'pROC' ## The following objec...
2052 sym R (3026 sym/17 pcs)
Mengatur Saturasi dengan Library Magick
===================================================== Nama Mahasiswa : Dodi Taufik Hidayat NIM : 220605110142 Kelas : B Mata Kuliah : Linear Algebra Dosen Pengampuh : Prof.Dr.Suhartono,M.Kom Jurusan : Teknik Informatika Universitas : UIN Maulana Malik Ibrahim Malang ===================================================== Memanggil package magick lib...
616 sym R (560 sym/8 pcs) 2 img
Memperbesar Gambar dengan library Magick
===================================================== Nama Mahasiswa : Dodi Taufik Hidayat NIM : 220605110142 Kelas : B Mata Kuliah : Linear Algebra Dosen Pengampuh : Prof.Dr.Suhartono,M.Kom Jurusan : Teknik Informatika Universitas : UIN Maulana Malik Ibrahim Malang ===================================================== Memanggil package magick libr...
734 sym R (1810 sym/14 pcs) 3 img
Mengubah Gambar dari Teks dengan OCR Tesseract
===================================================== Nama Mahasiswa : Dodi Taufik Hidayat NIM : 220605110142 Kelas : B Mata Kuliah : Linear Algebra Dosen Pengampuh : Prof.Dr.Suhartono,M.Kom Jurusan : Teknik Informatika Universitas : UIN Maulana Malik Ibrahim Malang ===================================================== Memanggil package “tesserac...
440 sym R (498 sym/6 pcs) 1 img
Tesseract
hal 107 import numpy as np A = np.matrix([[3, 0, -5], [-1, -3, 4]]) B = np.matrix([[-5, 5, 2], [1, -2, 0]]) A + B ## matrix([[-2, 5, -3], ## [ 0, -5, 4]]) A = np.matrix([[3, 0, -5], [-1, -3, 4]]) -3 * A ## matrix([[ -9, 0, 15], ## [ 3, 9, -12]]) A = np.matrix([[1, -2,3], [-3, 2, -1]]) B = np.matrix([[0, 2], [1, 1], [2, 0...
25 sym Python (526 sym/14 pcs)
Practical Applications
hal 105 library(mvtnorm) library(ggplot2) library(matlib) ##Standard deviation sigma <- matrix(c(4,2,2,3), ncol = 2, nrow = 2) ##Mean mu <- c(1,2) n <- 1000 set.seed(123) x<- rmvnorm(n=n, mean=mu, sigma=sigma) d <- data.frame(x) p2 <- ggplot(d, aes(x = X1, y = X2)) + geom_point(alpha = .5) + geom_density_2d() p2 y <- x- mu E <- eigen(...
26 sym R (581 sym/13 pcs) 2 img