Automatic Screen Reader Using JITBIT for Sending Message on WhatsApp Messenger

The current sales trend uses more online transaction concepts. The use of digitalization in online transactions and marketing is very important for businesses in increasing sales results to the maximum and on target. One way to increase this is by promoting on social media such as WhatsApp. Limited consumer contact makes it difficult for business actors to carry out promotions, so a database of consumer contacts is needed that can be maximized. In addition, problems in the process of sending manual messages can be overcome by using automatic message-sending actions so that promotions can be carried out automatically and quickly. The sending process is assisted by an "IF-THEN" statement and a screen that can recognize color conditions so that the automatic action can be operated on other services. The main objective of this research is to create a service that can accommodate consumer contacts by sharing contacts between business actors and being able to send messages automatically on WhatsApp by utilizing JITBIT. The results of this study prove that using JITBIT can send messages automatically on WhatsApp and can be operated on other services such as web-based applications. The results of the tests that have been carried out show that the accuracy level of JITBIT can send messages 100% with a delivery speed of 12 – 12.39 seconds/messag

IMPLEMENTASI ALGORITMA NAIVE BAYES PADA KLASIFIKASI TWEET UNTUK MENGETAHUI TINGKAT KEMALASAN SISWA

Twitter merupakan salah satu media sosial yang banyak digunakan oleh masyarakat saat ini. Salah satu pengguna twitter yang aktif adalah masyarakat usia sekolah. Twitter menjadi tempat siswa untuk meluapkan isi hatinya. Kondisi malas dalam belajar yang dialami siswa juga turut diungkapkan melalui tweets. Tujuan penelitian ini untuk menerapkan algoritma naïve bayes dalam klasifikasi tweet terkait kemalasan siswa. Masing-masing faktor yang mempengaruhi kemalasan tersebut dihitung. Data tweet yang digunakan dalam perhitungan sebanyak 773.225. Parameter yang digunakan dalam perhitungan: ulangan, guru, kurikulum, tugas, fullday. Hasil penelitian diketahui bahwa “full day” merupakan parameter dengan nilai tertinggi yang berhubungan dengan kemalasan