Skip to content

Instantly share code, notes, and snippets.

View ferdhika31's full-sized avatar
:octocat:
Home

Ferdhika Yudira ferdhika31

:octocat:
Home
View GitHub Profile
@ferdhika31
ferdhika31 / sertifikasi_training.txt
Created October 16, 2022 07:37
Sertifikasi / Training
- Penggunaan Agile dan Scrum untuk Development Project [Skill Academy by Ruang Guru - https://skillacademy.com/sertifikat/8FMVOC4DANTLBX]
- Web Application Developer Associate Skill Development [Inform IT - https://drive.google.com/file/d/1ODXne-qrLNwvhpyEegf2zL0z8Ds-M7o-/view?usp=sharing]
- Belajar Prinsip Pemrograman SOLID [Dicoding Indonesia - https://www.dicoding.com/certificates/GRX5G1KWYX0M]
- Cloud Practitioner Essentials (Belajar Dasar AWS Cloud) [Dicoding Indonesia - https://www.dicoding.com/certificates/L4PQMLJ0OZO1]
- Belajar Membuat Aplikasi Android untuk Pemula [Dicoding Indonesia - https://www.dicoding.com/certificates/98XW6G6MWXM3]
- React (Basic) [HackerRank - https://www.hackerrank.com/certificates/6dc557a6fc62]
- Rest API (Intermediate) [HackerRank - https://www.hackerrank.com/certificates/df10073fa935]
@ferdhika31
ferdhika31 / content.html
Created July 22, 2022 09:03
wkhtmltopdf sample
<!DOCTYPE html>
<body>
<b>This is your body</b>
</body>
</html>
@ferdhika31
ferdhika31 / scrap.py
Last active January 28, 2021 07:52
Scrap Data Keur s Omen
import requests
import csv
from bs4 import BeautifulSoup
def scrap(page=1):
url = "http://sekolah.data.kemdikbud.go.id/chome/pagingpencarian"
hearders = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.163 Safari/537.36',
'Referer': 'http://sekolah.data.kemdikbud.go.id/chome/pagingpencarian'
}
@ferdhika31
ferdhika31 / GitCommitEmoji.md
Created December 21, 2020 08:09 — forked from parmentf/GitCommitEmoji.md
Git Commit message Emoji
@ferdhika31
ferdhika31 / Response.php
Created December 1, 2020 08:24 — forked from jeffochoa/Response.php
Laravel HTTP status code
<?php
// This can be found in the Symfony\Component\HttpFoundation\Response class
const HTTP_CONTINUE = 100;
const HTTP_SWITCHING_PROTOCOLS = 101;
const HTTP_PROCESSING = 102; // RFC2518
const HTTP_OK = 200;
const HTTP_CREATED = 201;
const HTTP_ACCEPTED = 202;
var kelipatan = 500
var angka = 12600
var hasil = Math.round(angka / kelipatan) * kelipatan;
if(hasil < angka){
hasil += kelipatan;
}
alert(hasil);
@ferdhika31
ferdhika31 / main.py
Created July 19, 2019 14:18
Simple NER metode machine learning naive bayes
from mnb import MNB
nb = MNB()
nb.learn('Santika Supriadi Supriadi', 'person')
# nb.learn('Supriadi', 'person')
# nb.learn('Supriadi Cahyadi', 'person')
nb.learn('Santika Santika Merapi', 'organisasi')
nb.learn('Merapi Merapi Bali Supriadi', 'lokasi')
@ferdhika31
ferdhika31 / preprocess.py
Created May 4, 2019 12:27
Preprocessing
import pandas as pd
from nltk.tokenize import RegexpTokenizer
from nltk.corpus import stopwords
from nltk.stem import PorterStemmer
'''
Return array of word
'''
def preprocess(teks):
# lowercase
@ferdhika31
ferdhika31 / gist:537a385b1c589e1ddfe9858612903186
Created February 26, 2019 15:33 — forked from ttezel/gist:4138642
Natural Language Processing Notes

#A Collection of NLP notes

##N-grams

###Calculating unigram probabilities:

P( wi ) = count ( wi ) ) / count ( total number of words )

In english..