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All Journal JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknik Informatika (JUTIF) TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi AMMA : Jurnal Pengabdian Masyarakat
Nurhakim, Bani
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Humanities Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing

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Data Augmentation Techniques on the Accuracy of Fertile and Infertile Egg Classification Using Convolutional Neural Networks Nurhakim, Bani; Solihudin, Dodi; Amalia, Dina; Arelia, Irly
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5234

Abstract

The classification of fertile and infertile chicken eggs is crucial in the poultry industry to ensure optimal incubation efficiency and hatchability. However, the visual similarity between both egg types under candling conditions poses a significant challenge for manual inspection. This study aims to develop a convolutional neural network (CNN) model using the EfficientNetB4 architecture to automatically classify egg fertility based on image data. The dataset comprises candling images of chicken eggs, which underwent preprocessing steps such as resizing, normalization, and histogram stretching to enhance contrast. To improve model generalization, aggressive data augmentation techniques were applied, including rotation, flipping, zooming, and brightness adjustment. The model was trained in two phases—feature extraction and fine-tuning—using transfer learning and class balancing strategies. Evaluation results demonstrated high performance with an F1-score of 0.95 and balanced classification across both classes. The model's interpretability was further enhanced using Grad-CAM visualization, showing relevant activation regions. These findings indicate that the proposed method is effective in automating egg fertility classification and has potential for broader application in agricultural image diagnostics.
A Decision Tree Model with Grid Search Optimization for Scholarship Recipient Classification Suprapti, Tati; Nurhakim, Bani; Warni Ayu Hermina, Bintang; Syahputra Simbolon, Vrendi Amro
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5235

Abstract

This study aims to classify scholarship recipients using the Decision Tree algorithm implemented in RapidMiner. The dataset consists of 1.404 records with socioeconomic and academic attributes. Preprocessing was conducted using two Replace Missing Value operators, where categorical attributes such as No. BANTUAN, No. KKS, and Prestasi were filled with "Tidak Punya," while Kepemilikan Rumah was imputed using the average value. The model was built using a Decision Tree algorithm, optimized with the Optimize Parameters (Grid) operator to determine the best values for maximal depth and confidence. Evaluation was performed using 10-fold Cross Validation to ensure reliability. The results show that the optimized Decision Tree model achieved a high accuracy of 97.72%, with strong precision, recall, and F1-score values in both the "Eligible" and "Not Eligible" classes. These findings demonstrate that the Decision Tree algorithm, when properly optimized and validated, can effectively support decision-making processes in scholarship eligibility classification. The model provides an interpretable and robust tool for educational institutions to evaluate student applications based on critical socioeconomic features, This research contributes to educational data mining by offering a validated and interpretable model that enhances fairness, transparency, and efficiency in the scholarship selection process.
Co-Authors Alma’as, Aziz Apriliyani, Ela Arelia, Irly Atha Anantyo Putra, Gilang Bakhtiar Ilmi, Hikmaludin Dina Amalia Eka Permana, Sandy Gifthera Dwilestari Hery Widijanto Hoeriah, Dede Lukman Rohmat, Cep Lukmanrohmat, Cep Maulana, Arman Mulyawan, Mulyawan Ningrum, Cistia Nining Rahaningsih Nur Kirana, Anita Permana, Sandy Eka Pratama, Denni Prihartono, Willy Rizki Fauzi, Ahmad Rizki Rinaldi , Ade Rizki Rinaldi, Ade Septiani, Intan Solihudin, Dodi Syahputra Simbolon, Vrendi Amro Tati Suprapti Warni Ayu Hermina, Bintang Yoni Ardiansah, Muhamad Zidan Soleh, Kautsar