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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Nuansa Informatika Telematika JUITA : Jurnal Informatika Indonesian Journal on Computing (Indo-JC) JETT (Jurnal Elektro dan Telekomunikasi Terapan) JOIV : International Journal on Informatics Visualization Jurnal Informatika Jurnal Pilar Nusa Mandiri Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JITK (Jurnal Ilmu Pengetahuan dan Komputer) Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Mantik Jurnal Teknik Informatika C.I.T. Medicom International Journal of Advances in Data and Information Systems EKONOMI, KEUANGAN, INVESTASI DAN SYARIAH (EKUITAS) Tematik : Jurnal Teknologi Informasi Komunikasi Innovation in Research of Informatics (INNOVATICS) Jurnal Pengabdian Masyarakat Nusantara Jurnal Abdimas Kartika Wijayakusuma Journal of Dinda : Data Science, Information Technology, and Data Analytics Naratif : Jurnal Nasional Riset, Aplikasi dan Teknik Informatika AJAD : Jurnal Pengabdian kepada Masyarakat Indonesian Journal of Business Analytics (IJBA) Formosa Journal of Applied Sciences (FJAS) Jurnal Pengabdian Masyarakat Tapis Berseri SisInfo : Jurnal Sistem Informasi dan Informatika International Journal of Accounting, Management, Economics and Social Sciences (IJAMESC) Jurnal Pengabdian Tri Bhakti International Journal of Computer Technology and Science Bulletin of Intelligent Machines and Algorithms
Nur Alamsyah
Fakultas Ilmu Komputer PASIM
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Journal : bulletin of intelligent machines and algorithms

 1 
Sentiment Analysis Model for the Free Lunch Program in Indonesia on Twitter (X) Based on Machine Learning Amelia Tifany Dewi; Nur Alamsyah; Arnold Ropen Sinaga
Bulletin of Intelligent Machines and Algorithms Vol. 1 No. 3 (2026): BIMA March 2026 Issue
Publisher : Maheswari Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65780/bima.v1i3.18

Abstract

Social media has become a primary platform for the public to voice their opinions on various public policies, including the free lunch program initiated by the Indonesian government. This study aims to analyze public sentiment toward this program through the Twitter (X) platform by utilizing machine learning algorithms. Data collection was conducted from January 2025 to June 2025, with a total of 2,045 comments successfully gathered. Sentiment labeling was performed manually, and only positive and negative sentiments were considered. The data, in the form of relevant comments, were pre-processed and classified into positive and negative sentiments. Three algorithms used in this study are Support Vector Machine (SVM), Naïve Bayes, and Random Forest. Evaluation was performed using data splitting schemes of 70:30 and 80:20, along with 5-fold cross-validation. Unlike previous studies, which primarily focused on sentiment analysis of general social issues or specific topics without emphasizing public policy, this study specifically investigates the public's sentiment regarding a government policy (the free lunch program) and compares the performance of different machine learning models. The results of the study show that the Random Forest model outperformed SVM and Naïve Bayes, achieving an accuracy of 89.41% with a standard deviation of 0.0138. Meanwhile, SVM achieved an accuracy of 88.96% and Naïve Bayes 88.72%. These findings suggest that Random Forest is the most optimal and consistent model for sentiment analysis of public policies on social media.
Enhancing Breast Cancer Diagnosis with Ensemble Learning: Leveraging Convolutional Neural Networks and Pretrained Models through Averaged Predictions Elia Setiana; Reni Nursyanti; Nur Alamsyah; Nayla Nurul Azkiya
Bulletin of Intelligent Machines and Algorithms Vol. 1 No. 4 (2026): BIMA May 2026 Issue
Publisher : Maheswari Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65780/bima.v1i4.26

Abstract

Breast cancer continues to be a serious health issue at the global level, and early detection can significantly improve patient outcomes. This research uses imaging techniques to examine the design of an improved classification model in breast cancer detection. This project uses deep learning approaches through Convolutional Neural Networks (CNN) and ensemble learning models to potentially improve classification accuracy. To further enhance performance while controlling for class imbalance and overfitting, we leverage several models, such as ResNet18 and VGG16, with data augmentation and pre-trained models. Our methods included standard preprocessing of medical images, splitting datasets into training, testing and validation sets, and training each model with the Adam optimizer. Performance measurement included accuracy, precision, recall, and F1 score metrics. Overall, prototypes recently created displayed clear advantages based on finding results achieved through an ensemble method, which demonstrated improved model stability and reduced significant misclassification errors, and model accuracy reached 0.96. This research is crucial while developing strong deep-learning models to aid in breast cancer detection, ultimately allowing us to set a base for developing better diagnostic inference systems in medical-based applications. These systems may help improve early detection and overall patient care.
Co-Authors Acep Hendra Aji Gautama Putrada Alamsyah, R Yadi Rakhman AlFauzi, Ihsan Almira Nurchawilah Amelia Tifany Dewi Arnold Ropen Sinaga Arnold Ropen Sinaga Ayi Mohamad Sudrajat Budi Sulistiyo Jati Budiman Danestiara, Venia R Della Octa Irmulvani Devi Silaen Dirham Triyadi Eli Nofita Sari Elia Setiana Erpurini, Wala Fauzan, Mohamad Nurkamal Habibi, Chairul Hani Fitria Rahmani Hani Fitria Rahmani Hasan Nuraripin Hermawan, Arief Karditya Ikke Dian Oktaviani Indah Susilawati Ismi Nur Muhamad Jennifer Kaunang, Valencia Claudia Kaunang, Valencia Kaunang, Valencia Claudia Jennifer Leonandri, Dino Gustaf Mohamad Nurkamal Fauzan Mohamad Nurkamal Fauzan Mohamad Nurkamal Fauzan Muhamad Andriansyah Nurcahya Muhamad Nurkamal Fauzan Muhammad Yusup Iskandar Muhiban, Ayi Mutaqin Akbar Nayla Nurul Azkiya Nur Imam Febrianto Nursyanti, Reni PARAMA YOGA, TITAN R Yadi Rakhman Alamsyah R. Yadi Rakhman Alamsyah Reni Nursyanti Reni Nursyanti Rijwan Rijwan Rimbun Kencana RIO ANDRIYAT KRISDIAWAN Setiana, Elia Sidik Prabowo Silvana Anggraeni, Zulmeida Syafrial Fachri Pane Tiara Nurhasanah Titan Parama Titan Parama Yoga Titan Parama Yoga Tito Sugiharto Tutik Ultsa Rahmatika Valencia Claudia Jennifer Venia Restreva Danestiara Wala Erpurini Wala Erpurini Wala Erpurini Wia Handayani Yeni