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Journal : JOINTER : Journal of Informatics Engineering

Perancangan Sistem Kontrol Suhu Ruangan Server Menggunakan Arduino Uno Di Pusat Komputer Universitas Negeri Manado Dani Orlando; Daniel Kaparang; Kristofel Santa
JOINTER : Journal of Informatics Engineering Vol 2 No 02 (2021): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v2i02.24

Abstract

Abstract—Microcontrollers are now growing rapidly and are increasingly in demand on system applications control. These days, there are many microcontrollers that already in module form. One of the microcontroller module that is widely used is Arduino. Arduino is a type of board which contains a microcontroller. Combined with the ESP8266-01 module and NodeMCU makes the microcontroller can be connected via internet network. Microcontroller board device Arduino makes it possible to process the temperature reading data from the temperature sensor for support to the display unit using an android based smartphone and controlling AC temperature using Telegram. The processing result data from this Arduino board will be transmitted using wireless media connected to internet network.
Analisis Sentimen New Normal Pada Masa Covid-19 Menggunakan Algoritma Naive Bayes Classifier Shania Kaparang; Daniel Riano Kaparang; Vivi Pegie Rantung
JOINTER : Journal of Informatics Engineering Vol 2 No 01 (2021): JOINTER : Journal of Informatics Engineering
Publisher : Program Studi Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jointer.v2i01.33

Abstract

The impact of the covid-19 pandemic is so great that the government must have policies to reduce its impact. One of the government's policies is the new normal which requires all people to wear masks, keep their distance and wash their hands. In its application, of course, there are positive and negative sentiments uploaded to Twitter. This study aims to model the analysis of public sentiment regarding the government's new normal policy during the covid-19 pandemic in Indonesia. The stages of this research are data crawling, labeling, neutral data removal, preprocessing, distribution of training data and data testing, creation of a nave Bayes classification system, system testing and visualization of research results using wordcloud. The classification system performance includes 80.37% accuracy, 87.38% precision, 82.57% recall and 84.91% f-measure. The results of this study are 5194 tweets classified as positive sentiment and 2908 tweets classified as negative sentiment, this shows that there are more positive sentiments than negative sentiments. But from the numbers it can be seen that the comparison is not too far between positive and negative sentiments, meaning that there is a lack of public response to the new normal government policies during the pandemic.