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Evaluasi Kinerja Model Klasifikasi Machine Learning untuk Deteksi Fraud pada Data Transaksi Tidak Seimbang
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
Private vehicles are a frequently used mode of transportation because they are considered more practical. However, using private vehicles carries several risks, such as traffic accidents due to drivers losing focus on the road due to other activities, such as making calls on smartphones, drinking, or operating the radio. Approximately 90% of accidents are caused by human error. Convolutional Neural Network (CNN) is a type of neural network commonly used on image data. CNN is often used for image...
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Model Prediksi Pelunasan Haji Berbasis XGBoost Dengan Interpretasi Shap: Studi Prediksi Pelunasan Haji dengan XGBoost dan SHAP di Provinsi Jambi
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
This study develops an interpretable machine learning model to predict the settlement status of Hajj fees in Jambi Province, Indonesia. Utilizing the XGBoost algorithm on a dataset of 4,332 prospective pilgrims from 2025, the research addresses the critical challenge of class imbalance where only 28.5% of samples are labeled "Unsettled". The baseline XGBoost model achieved a ROC-AUC of 0.7778, with a recall of 0.3482 for the minority class. SHAP (SHapley Additive exPlanations) analysis was emplo...
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Analisis Sentimen Ulasan Aplikasi CapCut Berbasis IndoBERT dengan Validasi Silang
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
This study conducts sentiment analysis of Indonesian user reviews of the CapCut application using IndoBERT and compares two evaluation schemes: a single 80/20 train–test split and stratified 5-fold cross-validation (k=5). A total of 1,048,575 reviews were collected from the Google Play Store through web scraping and labeled into three sentiment classes based on rating: negative (1–2), neutral (3), and positive (4–5). After preprocessing—cleaning, case folding, banned-word removal, normalization—...
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Optimasi Prediksi Hipertensi Menggunakan Logistic Regression Berbasis Borderline SMOTE dan Penjelasan Model dengan SHAP
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
Hypertension is a major global health risk that requires accurate early detection, yet conventional methods struggle with complex and imbalanced health datasets. This study aims to optimize hypertension prediction using a Logistic Regression model integrated with Borderline-SMOTE to enhance recall and provide model transparency through SHAP (Shapley Additive Explanations). The method utilizes the BRFSS dataset, applying Borderline-SMOTE to address class imbalance at the decision boundary and XAI...
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Klasifikasi Penggunaan Daya Listrik Rumah Tangga dengan Menggunakan Metode Naive Bayes
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
Data mining is a technique of several fields of science to find previously unknown relationships in the data warehouse so that it becomes an information that can be used later. The unwise use of electricity will of course have an impact on the high use of electricity, therefore it is expected that every community understands the effort to use electricity wisely. Therefore, authors perform analysis of data mining on these electrical usage data in order to know which is a small, medium and large c...
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