Building of Informatics, Technology and Science (BITS)
Informatics
Building of Informatics, Technology and Science (BITS) is an open access media in publishing scientific articles that contain the results of research in information technology and computers. Paper that enters this journal will be checked for plagiarism and peer-rewiew first to maintain its quality. This journal is managed by Forum Kerjasama Pendidikan Tinggi (FKPT) published 2 times a year in Juni and Desember. The existence of this journal is expected to develop research and make a real contribution in improving research resources in the field of information technology and computers.
Articles in this Journal
Studi Komparasi Kinerja Algoritma AdaBoost dan CatBoost dalam Prediksi Perilaku Pembelian Pelanggan
Customer purchase behavior is a crucial factor in the development of effective marketing strategies. By leveraging predictive analytics, businesses can personalize recommendations, optimize marketing campaigns and improve user experience, ultimately...
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Comparison of Clustering Algorithms for Analyzing the Impact of Conflict on Poverty and Inflation
Armed conflict can have significant impacts on the social and economic conditions of a region, particularly on poverty levels and inflation. This study aims to analyze the impact of conflict on key economic indicators using a Knowledge Management Sys...
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Penerapan Regresi Logistik, K-NN, dan Naïve Bayes Berbasis Pendekatan CRISP-DM dalam Memprediksi Penyakit Jantung
Heart disease remains the leading cause of mortality globally, despite having significant potential to be controlled through early detection and effective risk-factor management. To improve the accuracy and efficiency of early detection, machine lear...
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Sentiment Analysis on the Allocation of the MBG Program Budget Using Support Vector Machine
Sentiment analysis is one of the applications of artificial intelligence and machine learning used to automatically identify and classify public opinions, particularly those expressed on social media. This approach is important for understanding publ...
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Deep Learning-Based Early Detection Optimization for Rice Leaf Diseases to Support Sustainable Local Agriculture
Rice leaf diseases such as Bacterial Blight and Blast are major threats to rice productivity that directly impact food security and the sustainability of local agriculture. This study aims to develop and optimize a deep learning-based early detection...
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Hybrid Entropy and CRADIS Method Approach in Decision Support System for Selecting the Best Employees
Selecting the right employees is a key factor in improving organizational performance and productivity. However, in many organizations, the employee selection process is still conducted through manual assessments and subjective judgments, which may l...
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Hybrid DBSCAN - K-Means Clustering for Financial Loss Identification in INA-CBG Claims Based on Medical Treatment Patterns
Hospital financial deficits due to INA-CBG claim discrepancies pose a critical challenge to healthcare sustainability in Indonesia. The difference between hospital operating costs and INA-CBG rates often results in significant financial deficits, whi...
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Pemodelan Pola Temporal Action Unit untuk Pengenalan Ekspresi Wajah Berbasis Bidirectional LSTM
This study develops a facial expression recognition system based on Facial Action Units (AU) data using a Bidirectional Long Short-Term Memory (BiLSTM) model. The dataset consists of AU data obtained from a supervisor, sourced from DCAP-SWOZ (USC Ins...
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Komparasi Model Ensemble dan Algoritma Machine Learning Untuk Memprediksi Penyakit Jantung
This study compared the performance of nine machine learning algorithms in predicting heart disease using a dataset dating back to 1988 and consisting of four databases: Cleveland, Hungary, Switzerland, and Long Beach totaling 1025 data. The dataset...
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Hybrid Music Recommendation System Using K-Means Clustering and Neural Collaborative Filtering for Spotify Playlist Personalization
Personalizing music recommendations has become a significant challenge on music streaming platforms such as Spotify due to the vast number of available songs and the limitations of conventional recommendation systems in accurately capturing user pref...
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Perbandingan Naïve Bayes dan Support Vector Machine Berbasis Term Frequency−Inverse Document Frequency pada Analisis Sentimen Ulasan Produk Afiliasi Lintas Platform TikTok dan Shopee
The growth of affiliate marketing on digital platforms, particularly TikTok and Shopee, has led to a rapid increase in consumer reviews that can be leveraged as actionable insights for businesses. However, reviews across platforms exhibit different l...
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Perbandingan Kinerja Model ARIMA dan LSTM dalam Peramalan Harga Crypto Solana (SOL-USD) Berbasis Data Yahoo Finance
The extreme volatility and non-linear patterns of Solana (SOL) data, driven by its unique consensus mechanism and massive transaction volume, demand accurate forecasting methods to mitigate investment risks. This study compares the statistical method...
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Analisis Ketahanan Model ResNet-50 pada Klasifikasi Bahasa Isyarat Arab terhadap Degradasi Citra Bawah Air
Automatic sign language recognition using deep learning, particularly Convolutional Neural Networks (CNNs), has shown significant potential. The ResNet architecture, through transfer learning, is frequently reported to achieve high accuracy for Arabi...
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Optimasi Deteksi Malware Android pada Dataset Drebin Menggunakan Ensemble Learning
The increasing number and complexity of Android malware require detection systems that are accurate, efficient, and capable of handling high-dimensional data. Machine learning–based approaches have become one of the widely adopted solutions in cybers...
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Comparative Analysis of K-NN and Naïve Bayes Algorithms for Early-Stage Chronic Kidney Disease Classification
Chronic Kidney Disease (CKD) is a global health issue characterized by low early detection rates and high diagnostic costs. Artificial intelligence, particularly machine learning, offers a promising solution as a rapid and cost-effective decision sup...
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