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p-Index From 2021 - 2026
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All Journal Engineering, Mathematics and Computer Science Journal (EMACS) International Journal of Computer Science and Humanitarian AI
Henry Lucky
Bina Nusantara University
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics

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Pengembangan Smart Air Condition Control Menggunakan Platform Blynk Berbasis Mikrokontroler ESP8266 dan Sensor DHT11 Ade Putera Kemala; Muhammad Edo Syahputra; Henry Lucky; Said Achmad
Engineering, MAthematics and Computer Science (EMACS) Journal Vol. 4 No. 1 (2022): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v4i1.8072

Abstract

Air Conditioners (AC) are increasingly used to get the room temperature as desired, starting from home use to keep the room cool and enjoyable, to specific room like server rooms or ATM which are focused on keeping the room cool in order to keep the equipment cool. The role of AC is quite important to maintain room temperature, and its increasing use has led to the growing need for users to control the AC. The Internet of Things allows users to remotely control air conditioners using the gadgets used and get real time room temperature information. The AC control system based on Internet of Things (IoT) utilizes an internet connection to monitor room temperature and control AC remotely. The devices used are DHT11 as a temperature sensor to get room temperature, Infrared Receiver to read the code sent by the remote AC, Infrared Transmitter to send commands to the AC in the room, and ESP8266 as a microcontroller and a link to the internet. The IoT platform used is Blynk which has the ability to access the microcontroller from the user's gadget. The tests are running on room air conditioners such as the Panasonic CS-PC18PKP series, the Panasonic CS-YN18TKP series and the Samsung AR09TGHQASINSE series. The test results showed that the room air conditioner was successfully controlled, and the room temperature was read in real time via an android smartphone.
Analyzing Public Sentiment Toward the Makan Bergizi Gratis (MBG) Program on TikTok Using SVM and IndoBERT Alfredo Winston; Nicholas Darren; Henry Lucky; Rilo Pradana; Noviyanti Sagala
International Journal of Computer Science and Humanitarian AI Vol. 3 No. 1 (2026): IJCSHAI
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/ijcshai.v3i1.15184

Abstract

Social media has become a major platform for the public to express opinions toward government programs. This study analyzes public sentiment toward Indonesia’s Makan Bergizi Gratis (MBG) program using a text mining approach. A total of 11,730 TikTok comments related to the MBG program were collected and classified into positive, negative, and neutral sentiments. Two classification models were compared: a traditional Support Vector Machine (SVM) using TF-IDF features and a transformer-based model, IndoBERT. Experimental results show that IndoBERT outperforms the tuned SVM model, achieving an accuracy of 0.78 and a weighted F1-score of 0.78, compared to 0.73 accuracy and 0.73 F1-score obtained by the SVM. IndoBERT demonstrates better performance in handling neutral and context-dependent sentiments, indicating its effectiveness for analyzing Indonesian social media data related to public policy evaluation. This study contributes to the growing body of research on Indonesian sentiment analysis by providing an empirical comparison between classical machine learning and transformer-based models for analyzing public responses to government policies using social media data. The findings also highlight the importance of advanced language models in capturing linguistic nuances, informal expressions, and contextual meanings commonly found in online discussions, particularly on rapidly evolving social media platforms widely used by Indonesian users across different demographic and social backgrounds.
Co-Authors Ade Putera Kemala Alfredo Winston Muhammad Edo Syahputra Nicholas Darren Noviyanti Sagala Rilo Pradana Said Achmad