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All Journal Jurnal PkM MIFTEK Journal of Intelligent Systems Technology and Informatics
Putra, Andika Eka Sastya
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Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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PENCEGAHAN STUNTING DI DESA DAYEUHMANGGUNG Rezeki, Pamella M Sri; Fadhilah, Rizal Ahmad; Shiddiq, Muhammad Jafar; Rahmawati, Siti Saadah; Cahya, Meisya Aura; Fatra, Salman Dial; Sidqi, Iqbal; Sahid, Ahmad Nur; Ramadhan, Muhammad Renaldy Taufiq; Putra, Andika Eka Sastya; Hafitri, Agisni Maulani; Nurdin, Ihsan; Taufik, Muhammad Irwan; Putri, Fujiyanti Rifani; Mukhlis, Ade; Pamungkas, Lutfi Berlian Putra; Prasetyo, Nurcholis Ade; Putra, Gelar Satria; Anisa, Hani Nur; Furkon, Furkon; Mubarok, Ahmad Hilal
Jurnal PkM MIFTEK Vol 5 No 2 (2024): Jurnal PkM MIFTEK
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/miftek/v.5-2.1907

Abstract

Prevention of Stunting in Dayeuh Manggung VillageStunting is a health issue that is often experienced by children in Dayeuhmanggung Village. This is due to a lack of access to balanced nutrition and adequate sanitation. The issue can be addressed through community service activities in the form of seminars that have been conducted with the aim of raising awareness and knowledge among the public regarding the importance of balanced nutrition, good eating habits, and hygiene to prevent infections. The method used in this service is the Work Breakdown Structure (WBS) scheme, which breaks down the work process into smaller parts to facilitate planning and coordination. The results of the seminar activities indicate an increase in public understanding of stunting and its prevention measures, as well as the participants' ability to apply the knowledge gained in their daily lives. Support from the government, health organizations, and active community participation also strengthens the positive impact of this activity. A systematic and collaborative approach is expected to address the stunting cases in Dayeuhmanggung Village.
Gender Identification from Facial Images Using Custom Convolutional Neural Network Architecture Amiludin, Ikbal; Putra, Andika Eka Sastya
Journal of Intelligent Systems Technology and Informatics Vol 1 No 1 (2025): JISTICS, March 2025
Publisher : Aliansi Peneliti Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64878/jistics.v1i1.27

Abstract

Gender classification from facial images has become increasingly important in biometric applications. This study introduces a deep learning approach utilizing a custom convolutional neural network (CNN) model trained on 8,908 labeled facial images obtained from Kaggle, comprising 4,169 female and 4,739 male samples. Each image underwent preprocessing, including grayscale conversion, face alignment, cropping, resizing to 100×100 pixels, and pixel normalization. The CNN architecture consists of three convolutional layers with ReLU activation, max-pooling layers, a flatten layer, and two dense layers, ending with a sigmoid activation function for binary classification. The model was implemented using TensorFlow and trained for 70 epochs on Google Colab with GPU acceleration. Evaluation metrics include classification accuracy, confusion matrix, and area under the curve (AUC) from the ROC curve. The proposed system achieved 90.79% accuracy and 0.97 AUC, indicating robust performance. However, the confusion matrix revealed slightly higher precision for male predictions, suggesting the need for class balance refinement. The method demonstrates strong potential for integration into real-world facial analysis systems, such as identity verification, access control, and intelligent surveillance platforms.
Co-Authors Amiludin, Ikbal Anisa, Hani Nur Cahya, Meisya Aura Fadhilah, Rizal Ahmad Fatra, Salman Dial Furkon, Furkon Hafitri, Agisni Maulani Mubarok, Ahmad Hilal Mukhlis, Ade Nurdin, Ihsan Pamungkas, Lutfi Berlian Putra Prasetyo, Nurcholis Ade Putra, Gelar Satria Putri, Fujiyanti Rifani Rahmawati, Siti Saadah Ramadhan, Muhammad Renaldy Taufiq Rezeki, Pamella M Sri Sahid, Ahmad Nur Shiddiq, Muhammad Jafar Sidqi, Iqbal Taufik, Muhammad Irwan