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All Journal JOIN (Jurnal Online Informatika) Journal of Technopreneurship and Information System (JTIS) Jurnal Pengabdian Masyarakat Bumi Raflesia Journal of Robotics and Control (JRC) Jurnal Teknik Informatika (JUTIF) DECODE: Jurnal Pendidikan Teknologi Informasi Jurnal INFOTEL IJMST Scientific Journal of Engineering Research
Muhajir Yunus
Universitas Muhammadiyah Gorontalo
Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Other

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Journal : IJMST

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The Role of Sentiment Analysis in Election Predictions Compared to Electability Surveys Firdaus, Asno Azzawagama; Faresta, Rangga Alif; Yunus, Muhajir
Indonesian Journal of Modern Science and Technology Vol. 1 No. 1 (2025): January
Publisher : CV. Abhinaya Indo Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64021/ijmst.1.1.1-8.2025

Abstract

Indonesia has just held the voting process for the Presidential Election. This has become a discussion of various media to social media, especially Twitter. However, when making predictions based on social media it will be so difficult if there is no specific technique or method for handling it. The prediction method we found in Indonesia often uses electability surveys in elections, but this research will compare it with sentiment analysis that utilizes social media in data collection. Another novelty is the data used during candidate campaign debates using the Support Vector Machine (SVM) method in class classification. The results obtained show that there are still differences between electability and sentiment, but this is due to several factors such as the amount of data, data objects, data collection time span, and methods. Overall, the SVM method has an accuracy of more than 0.75 on all three candidate datasets, proving that this method can be applied to similar cases.
Internet of Things-Based Automatic Trash Can Prototype Using Arduino Mega 2560 Sumarno Wijaya; Ahmad Fatoni Dwi Putra; Yuan Sa'adati; Hadi San, Ahmad Syahrul; Yunus, Muhajir; Talirongan, Florence Jean B.; G. Tangaro, Diana May Glaiza; Grancho, Bernadine
Indonesian Journal of Modern Science and Technology Vol. 1 No. 2 (2025): May
Publisher : CV. Abhinaya Indo Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64021/ijmst.1.2.43-49.2025

Abstract

The development of Internet of Things (IoT) technology encourages the creation of various smart device innovations that can be applied in everyday life, one of which is an automatic waste management system. This research aims to design and implement an IoT-based automatic trash can prototype using an Arduino Mega 2560 microcontroller that is able to detect the presence of people who will throw away garbage, open and close the lid of the tub automatically, and provide notification if the trash can is full. This research uses an experimental method by combining ultrasonic sensors, servo motors, and LED indicators as the main components. The test results show that the device works well and in accordance with the researcher's expectations. Ultrasonic sensor 1 can detect the presence of objects in front of the trash can and trigger the servo motor to open and close the lid automatically. Ultrasonic sensors 2 and 3 are also able to detect the height of the garbage and activate the servo motor while the indicator LEDs also function as designed: LED 1 blinks when someone approaches to take out the trash, while LED 2 and LED 3 light up when the sensors detect that the trash has reached a certain height limit. In addition, the system is energy efficient as it only activates when an object is detected, making it suitable for households and educational institutions.
Sentiment Analysis of User Reviews of TikTok App on Google Play Store Using Naïve Bayes Algorithm Hasanah, Rakyatol; Sani SR, Sahrul; Munzir, Misbahul; Firdaus, Asno Azzawagama; Sulton, Chaerus; Yunus, Muhajir
Indonesian Journal of Modern Science and Technology Vol. 1 No. 2 (2025): May
Publisher : CV. Abhinaya Indo Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64021/ijmst.1.2.58-64.2025

Abstract

In recent years, user interaction through mobile applications has grown rapidly, making user reviews an important source of feedback for improving service quality. This study explores sentiment analysis on 5,000 user reviews of the TikTok application, collected from the Google Play Store using the google-play-scraper library. The data underwent several preprocessing steps, such as case folding, text cleaning, and selecting relevant columns like review content and rating score. Sentiment labeling was based on rating values: scores of 4 and 5 were treated as positive, while scores of 1 and 2 were considered negative. From the results, it was observed that negative reviews appeared more frequently, indicating an imbalance in the dataset. Despite this, the Naïve Bayes classification algorithm still achieved a reasonably good performance in categorizing the sentiments. These findings suggest that even with simple models, valuable insights can be gained from user-generated content. Moreover, the results provide meaningful input for TikTok developers to better understand user concerns and emphasize the potential need for applying balancing techniques in future analysis. Further studies are encouraged to explore other algorithms that may improve sentiment classification accuracy on more complex datasets.    
Co-Authors Abdul Fadlil Abdul Fadlil Abdul Fadlil Ahmad Fatoni Dwi Putra Alwas Muis Asno Azzawagama Firdaus Azminuddin I. S. Azis Daniel Santoso Faresta, Rangga Alif Fitriah Fitriah Fitriah Fitriah G. Tangaro, Diana May Glaiza Grancho, Bernadine Hadi San, Ahmad Syahrul Hasanah, Rakyatol Herman Herman Imam Riadi Imam Riadi Muhammad Kunta Biddinika Muhammad Kunta Biddinika Muhammad Kunta Biddinika Muis, Alwas Munzir, Misbahul Muzakkir Pangri Nurdin, St Suryah Indah Rusydi Umar Sani SR, Sahrul Sulton, Chaerus Sumarno Wijaya Suprihatin Suprihatin Talirongan, Florence Jean B. Yuan Sa'adati