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Menampilkan 1–10 dari 16 artikel
Evolusi Performa Arsitektur Deep Learning melalui Optimasi Bertahap dan Interpretabilitas Grad-CAM untuk Klasifikasi Penyakit Ikan Air Tawar
Sasa Kirana Wulandari
; Fachruddin Fachruddin
; Jasmir Jasmir
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2026)
Freshwater fish diseases significantly affect aquaculture productivity and economic sustainability, while accurate visual classification remains challenging due to interclass similarity and image variability. This study presents a comparative evaluation of three deep learning architectures—DenseNet201, ResNet50, and EfficientNetV2-S—using a stepwise optimization strategy combined with Gradient-weighted Class Activation Mapping (Grad-CAM) for freshwater fish disease classification. Models were tr...
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Perancangan Alat Deteksi Tingkat Kematangan Buah Mangga Indramayu Berdasarkan Kandungan Gas dan Pengolahan Citra Menggunakan YOLOv11
Adi Kusuma
; Jasmir Jasmir
; Willy Riyadi
; Ahmad Ahmad
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2026)
Indramayu mango is a seasonal fruit that is highly favored due to its delicious taste and high nutritional content. However, high mango production is often not supported by adequate post-harvest facilities, particularly in terms of fruit ripeness classification. Currently, mango ripeness classification is still performed manually, which tends to be subjective and inconsistent. To address this issue, this study proposes a ripeness detection system for Indramayu mangoes by integrating the TGS2602...
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Optimasi XGBoost Dengan SHAP Untuk Sistem Skrining Penyakit Jantung
Clara Zuliani Syahputri
; Jasmir Jasmir
; Fachruddin Fachruddin
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2026)
Heart disease is the leading cause of death in Indonesia and globally, necessitating an early screening system that is both accurate and clinically trustworthy. Although XGBoost demonstrates high predictive performance, its black-box nature undermines clinical trust, while low recall risks missed diagnosis an unacceptable consequence in population screening, especially in middle-income countries with limited healthcare resources. This study aims to develop a sensitive, transparent, and implement...
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Evaluasi Kinerja Machine Learning pada Klasifikasi Penyakit Jantung Menggunakan Teknik Penyeimbangan Data
Eni Rohaini
; Gunardi, Gunardi
; Nurhayati Nurhayati
; Jasmir Jasmir
; Zahra Prisdian Tiararosa
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
AImbalanced data remains a significant issue in heart disease classification using machine learning, as it tends to cause models to overestimate the majority class while ignoring minority classes with high clinical value. This can lead to a decrease in accuracy and the model's ability to accurately detect disease cases. Therefore, this study aims to assess the effectiveness of oversampling techniques, namely Random Oversampling and Synthetic Minority Oversampling Technique (SMOTE), in improving...
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Analisis Sentimen Ulasan Penggunaan Aplikasi Maxim Pada Google Play Store Menggunakan Algoritma Naive Bayes, SVM, CatBoost Berbasis NLP
Nanda Mediya Sari
; Jasmir Jasmir
; Elvi Yanti
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
Sentiment analysis is a technique in Natural Language Processing (NLP) used to identify user opinion tendencies based on textual reviews. This study analyzer user reviews of the Maxim application on the Google Play Store and compares three Machine Learning algoritmhs-Naïve Bayes, Support Vector Machine (SVM), and CatBoost-in classifying sentiment. The research stages include data collection, text preprocessing, feature extraction using TF-IDF and Chi-Square, class balancing using SMOTE, and perf...
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Implementasi Data Mining dengan Teknik Smote dan Fitur Gain Ratio Untuk Klasifikasi Kelayakan Siswa Penerima PIP di Kota Jambi
Dea Sabrina Candra
; Jasmir Jasmir
; Yanti, Elvi
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
The Indonesia Pintar Program (PIP) is an educational assistance program for students from underprivileged families, but determining the eligibility of recipients still faces obstacles in the form of subjectivity and data imbalance. This study aims to classify the eligibility of high school students receiving PIP in Jambi City using data mining methods. The SMOTE technique was applied to overcome class imbalance, and Gain Ratio feature selection was used to determine important attributes. The dat...
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Implementasi YOLOv8 dan Pengaruh Augmentasi Data dalam Sistem Deteksi Faktor Risiko Sudden Infant Death Syndrom (SIDS) pada Bayi
Rhadis Steffani Saputri
; Jasmir Jasmir
; Gunardi Gunardi
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
Sudden Infant Death Syndrome (SIDS) is a sudden and unexpected death in infants that is often associated with the prone sleeping position. This study aims to develop an automated monitoring system capable of detecting SIDS risk factors using the YOLOv8 algorithm and to analyze the effect of data augmentation on model performance. The dataset consists of two classes, baby-lying-on-back (supine) and baby-lying-on-stomach (prone), which were processed through model training and evaluation using pre...
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Penerapan NLP Menggunakan Algoritma Naive Bayes, C4.5, XGBoost untuk Analisis Sentimen Ulasan Produk Kecantikan di Tokopedia dan Shopee
Srikandi Alifya
; Jasmir Jasmir
; Elvi yanti
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
The growth of e-commerce in Indonesia has led to an increase in product reviews, including for beauty products on Tokopedia and Shopee. These reviews serve as important sources of information to assess consumer satisfaction; however, manually analyzing thousands of reviews daily is impractical. This study applies Natural Language Processing (NLP) with Naive Bayes, C4.5, XGBoost algorithms to classify sentiment in Indonesian-language reviews. The dataset used consists of 76,256 reviews labeled as...
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Perbandingan Algoritma Naïve Bayes Classifier (NBC) dengan Random Forest Untuk Klasifikasi Penyakit Ginjal Kronis (PGK)
Caterina Paras Dewi
; Jasmir Jasmir
; Willy Riyadi
; Alya Rafina
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
Chronic Kidney Disease (CKD) is a heterogeneous disorder that gradually affects the structure and function of the kidneys, is difficult to recover, and causes the body to be unable to maintain metabolism and fail to maintain fluid and electrolyte balance, leading to increased urea levels. Chronic kidney disease data was obtained from Kaggle, in this study a comparison was made between two classification algorithms, namely Naïve Bayes Classifier (NBC) and Random Forest because it is not yet known...
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Analisis Kesesuaian Teknologi ChatGPT terhadap Aktivitas Perkuliahan Mahasiswa Menggunakan Model Task–Technology Fit (TTF)
Muhammad Arief Maulana
; Kurniabudi Kurniabudi
; Jasmir Jasmir
Prosiding Seminar Nasional Ilmu Teknik
Vol 2
, No 2
(2025)
The rapid development of artificial intelligence, particularly ChatGPT, has created new opportunities to support students’ academic activities in higher education. However, its utilization needs to be evaluated in terms of the alignment between academic task characteristics and technological capabilities to ensure optimal outcomes. This study aims to examine the feasibility of using ChatGPT in students’ academic activities by applying the Task–Technology Fit (TTF) model. This research employed a...
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