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All Journal Jurnal Simetris Jurnal technoscientia Telematika : Jurnal Informatika dan Teknologi Informasi Seminar Nasional Informatika (SEMNASIF) Jurnal Sistem Informasi dan Bisnis Cerdas Register: Jurnal Ilmiah Teknologi Sistem Informasi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Eksplora Informatika JMM (Jurnal Masyarakat Mandiri) JurTI (JURNAL TEKNOLOGI INFORMASI) Compiler CARADDE: Jurnal Pengabdian Kepada Masyarakat Voice Of Informatics Jurnal Teknologi Sistem Informasi dan Aplikasi Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat JMAI (Jurnal Multimedia & Artificial Intelligence) JUSIM (Jurnal Sistem Informasi Musirawas) Antivirus : Jurnal Ilmiah Teknik Informatika Building of Informatics, Technology and Science Technologia: Jurnal Ilmiah Journal of Information Systems and Informatics Jurnal Sistem Informasi dan Informatika (SIMIKA) JURNAL TEKNOLOGI TECHNOSCIENTIA Journal of Information Technology Ampera Journal of Computer and Information Systems Ampera Journal of Software Engineering Ampera Charity : Jurnal Pengabdian Masyarakat Prosiding SNAST Jurnal Pengabdian Masyarakat Indonesia Jurnal Ilmiah Teknologi Informasi dan Robotika Jurnal Abdi Masyarakat Indonesia International Journal Of Computer, Network Security and Information System (IJCONSIST) Jurnal Sains dan Teknologi Jurnal Pengabdian Mitra Masyarakat (JPMM) Journal of Computer Science and Technology (JCS-TECH) Journal of Information System and Artificial Intelligence Jurnal Sistem Informasi dan Bisnis Cerdas Journal Research of Social Science, Economics, and Management SisInfo : Jurnal Sistem Informasi dan Informatika Innovative: Journal Of Social Science Research TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi SENAPAS Mohuyula : Jurnal Pengabdian Kepada Masyarakat SITEKNIK: Sistem Informasi, Teknik dan Teknologi Terapan International Journal of Artificial Intelligence and Science
Prasetyaningrum, Putri Taqwa
Universitas Mercu Buana Yogyakarta
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Workshop Literasi Digital dan Keamanan Informasi Bagi Guru dan Siswa SMA Negeri 1 Sedayu Imam Riadi; Fithriatus Shalihah; Putri Taqwa Prasetyaningrum; Bambang Robiin
Mohuyula : Jurnal Pengabdian Kepada Masyarakat Vol 4, No 2 (2025): Desember
Publisher : Universitas Muhammadiyah Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31314/mohuyula.4.2.42-50.2025

Abstract

Perkembangan teknologi digital yang pesat menuntut peningkatan literasi digital dan kesadaran akan keamanan informasi di kalangan generasi muda, khususnya di tingkat SMA. Tujuan dari kegiatan pengabdian ini adalah untuk memberikan pelatihan mengenai literasi digital dan keamanan informasi kepada guru dan siswa SMA Negeri 1 Sedayu. Metode yang digunakan dalam pelatihan ini adalah pendekatan workshop interaktif yang meliputi ceramah, diskusi, dan simulasi praktis. Materi yang disampaikan mencakup pengenalan terhadap literasi digital, ancaman siber seperti phishing dan malware, serta cara melindungi data pribadi di dunia maya. Hasil dari kegiatan ini menunjukkan peningkatan signifikan dalam pemahaman peserta mengenai cara melindungi informasi pribadi dan mengenali ancaman siber. Berdasarkan evaluasi menggunakan pre-test dan post-test, peserta mengalami peningkatan pengetahuan mengenai literasi digital dan keamanan informasi, dengan 100% peserta mampu mengidentifikasi ancaman siber setelah pelatihan. Pelatihan ini juga berhasil meningkatkan kesadaran peserta tentang bahaya kejahatan siber, seperti cyberbullying, serta langkah-langkah pencegahan yang dapat dilakukan. Kesimpulannya, pelatihan ini berhasil mencapai tujuannya dalam meningkatkan pemahaman dan keterampilan peserta dalam menghadapi tantangan dunia digital. Diharapkan pelatihan ini dapat menjadi model untuk kegiatan serupa di sekolah lain, guna menciptakan lingkungan digital yang lebih aman dan bijak di kalangan generasi muda.
ANALISIS PENINGKATAN PERFORMA CONVOLUTIONAL NEURAL NETWORK MENGGUNAKAN HYPERPARAMETER TUNING DAN ENSEMBLE LEARNING PADA KLASIFIKASI CITRA MRI TUMOR OTAK SILA MILDAWATI; Putri Taqwa Prasetyaningrum
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8341

Abstract

This study aims to improve brain tumor MRI image classification performance through selected hyperparameter combinations and ensemble learning. The publicly available dataset consists of 3,264 training images and 394 testing images categorized into four classes: glioma, meningioma, no tumor, and pituitary tumor. The preprocessing stage includes resizing images to 224 × 224 pixels, normalization, and training-data augmentation. Two pre-trained CNN architectures, VGG16 and EfficientNetV2B0, were fine-tuned using selected combinations of the Adam and SGD optimizers, learning rates of 0.0001 and 0.001, and batch sizes of 32. The best configuration was obtained using Adam, a learning rate of 0.0001, and a batch size of 32. VGG16 achieved an accuracy of 90.00%, while EfficientNetV2B0 reached 98.73%. Combining the prediction probabilities of both models using soft-voting ensemble learning increased the accuracy to 99.49%, with two misclassified images. These results indicate that an appropriate training configuration and soft-voting ensemble learning can numerically improve MRI-based brain tumor classification performance.
COMPARATIVE ANALYSIS OF CONVNEXT V2 AND VISION TRANSFORMER FOR CLASSIFICATION OF STROKE LESIONS ON MRI IMAGING Nursila Latambaga; Putri Taqwa Prasetyaningrum
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8342

Abstract

Stroke is a major cause of neurological disability, and rapid, accurate diagnostic support remains essential. Because MRI interpretation still depends heavily on radiologist expertise, automated classification models are needed to support Computer-Aided Diagnosis (CAD). This study compares ConvNeXt V2 and Vision Transformer (ViT) for classifying stroke lesions in MRI images, using 7,463 images (4,423 Stroke; 3,040 Normal) integrated from two public Kaggle datasets. The pipeline covered dataset integration, preprocessing, augmentation, transfer learning with full fine-tuning, and evaluation on a held-out 20% test set using accuracy, precision, recall, specificity, F1-score, and AUC-ROC, supported by Grad-CAM and attention-rollout saliency analysis. ConvNeXt V2 achieved 94.98% accuracy, 95.81% precision, 95.71% recall, 93.91% specificity, 95.76% F1-score, and 99.25% AUC, outperforming ViT (92.77% accuracy, 94.30% precision, 93.45% recall, 91.78% specificity, 93.87% F1-score, 98.54% AUC) across all metrics. The largest gap appeared in accuracy and recall, and a paired McNemar test confirmed the difference is statistically significant (χ² = 14.42, p < 0.001). These findings support ConvNeXt V2 as a promising architecture for MRI-based stroke CAD systems, while highlighting the continued need for external clinical validation.  
COMPARATIVE ANALYSIS OF TRANSFER LEARNING PERFORMANCE USING VGG16 AND XCEPTION ARCHITECTURES FOR BREAST CANCER HISTOPATHOLOGICAL IMAGE CLASSIFICATION raden roro christawani herawati; putri taqwa prasetyaningrum
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8344

Abstract

Breast cancer ranks among the most prevalent malignancies in women globally and demands reliable image-based diagnostic support systems for accurate clinical decision-making. This study compares two transfer learning architectures, VGG16 and Xception, for breast cancer histopathological image classification using the BreakHis dataset, partitioned into training, validation, and testing subsets through stratified splitting. The pipeline included preprocessing, data augmentation, and a two-phase training strategy (freeze then fine-tuning), with performance assessed using eight metrics: accuracy, precision, recall, specificity, F1-score, AUC-ROC, Matthews Correlation Coefficient (MCC), and Cohen Kappa. Testing on 747 images demonstrated that Xception attained an accuracy of 95.72%, F1-score of 95.72%, AUC-ROC of 0.9926, MCC of 0.9144, and Cohen Kappa of 0.9143, compared to VGG16's accuracy of 90.90%, F1-score of 90.90%, AUC-ROC of 0.9686, MCC of 0.8181, and Cohen Kappa of 0.8179. Confusion matrix analysis revealed that Xception produced only 18 false negatives in the malignant class, versus 37 for VGG16, a clinically meaningful reduction. VGG16 required fewer parameters and shorter training duration, whereas Xception delivered superior classification performance. These findings suggest that Xception is the more suitable architecture for breast cancer Computer-Aided Diagnosis (CAD) system development, particularly where diagnostic sensitivity and overall accuracy outweigh computational cost.  
Enhancing Accessibility, Engagement, and Motivation in Counseling Services for Secondary Schools through Gamified Blended Mobile and Virtual Reality Therapy Putri Taqwa Prasetyaningrum; Norshahila Ibrahim; Eka Aryani; Rully Ningsih; Ibnu Rivansyah Subagyo
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 9 No 2 (2025): August 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v9i2.24814

Abstract

Background: Secondary school counseling services often face challenges such as limited counselor availability and low student participation. Traditional counseling methods frequently fail to engage students, thus reducing both accessibility and impact. Integrating Virtual Reality (VR) and mobile-based interventions presents a promising solution to address these issues. Objective: This study aims to evaluate the effectiveness of a gamified blended mobile and VR therapy in enhancing accessibility, cognitive-emotional-behavioral engagement, and motivation within secondary school counseling services. Methods: A mixed-methods research design was employed, combining quantitative methods (pre- and post-intervention surveys, along with behavioral tracking) and qualitative methods (semi-structured interviews and thematic analysis of focus group discussions). These methods were chosen to capture both measurable impacts and participants’ perceptions of the intervention. A total of 384 students and 10 counselors participated in an 8-week intervention. Results: The intervention led to a significant improvement in the Accessibility Index (from 3.2 to 4.6). Additionally, engagement across cognitive, emotional, and behavioral dimensions showed marked improvements. Thematic analysis revealed that students appreciated the safety and realism provided by the digital counseling environment. Conclusion: The gamified blended therapy approach effectively enhanced counseling accessibility and multidimensional engagement, offering a scalable, student-centered solution for secondary school counseling services.
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN SUPPLIER BAHAN BAKU FURNITURE TERBAIK MENGGUNAKAN METODE MULTI-OBJECTIVE OPTIMIZATION BY RATIO ANALYSIS (MOORA) Heri Agus Prasetyo; Putri Taqwa Prasetyaningrum
Technologia : Jurnal Ilmiah Vol 14 No 2 (2023): Technologia (April)
Publisher : Fakultas Teknologi Informasi, Universitas Islam Kalimantan Muhammad Arsyad Al Banjari, di bawah koordinasi UPT Publikasi dan Pengelolaan Jurnal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/tji.v14i2.7838

Abstract

CV Mandiri Abadi adalah salah satu perusahaan di Jepara yang bergerak di bidang furniture. Perusahaan yang memproduksi berbagai macam furniture atau mebel dengan bahan kayu jati sebagai bahan baku utamanya. Selama ini dalam pemilihan supplier hanya berdasarkan ketersediaan barang dan harganya saja tanpa memikirkan faktor lain. Dampaknya perusahaan sering mengalami kendala dalam kegiatan operasionalnya. Maka perlunya perancangan sistem pendukung keputusan pemilihan supplier bahan baku menggunakan Metode Multi-Objective Optimization By Ratio Analysis (Moora). Dengan mengimplementasikan perhitungan metode moora ini diharapkan dapat meminimalisir resiko yang dialami perusahaan saat ini, juga diharapkan dapat membantu perusahaan untuk mengambil keputusan dalam memilih supplier bahan baku yang tepat dan sesuai kriteria yang dibutuhkan perusahaan. Karena metode moora ini mempunyai tingkat selektifitas yang akurat dalam menentukan suatu alternatif, metode yang memiliki perhitungan dengan kalkulasi yang minimum dan sederhana, dan juga metode yang mempunyai tingkat fleksibilitas dan mudah dipahami.
Co-Authors Adi Ronggo Wicaksono Affandi Putra Pradana Agung Supoyo Agustin, Isnaini Ahmad Iwan Fadli Ahmad Mukhlasin Ahsan, Moh Ajisari, Lanang Dian Albert Yakobus Chandra Albert Yakobus Chandra Alfin Ainin Ramdhani Alphi Mukti Anggie Kurniawati Anggo Luthfi Yunanto Ari Wibowo Arita Witanti Aritonang, Roselina Artika Sari Arwa Ulayya Haspriyanti Aryani, Eka Ati, Gresensia Rosadelima Azzahra, Bernica Bagus Nur Solayman Bambang Robiin Bambang Setio Purnomo Bambang Setio Purnomo Budianto, Alexius Endy Cindy Okta Melinda Dapit Virdaus Denny Jean Cross Sihombing Devi Febrianti dewi, Ine shinta Dhana Sudana Eka Aryani, Eka Erza, Muhammad Al-Ghifari Fendi Pradana Saputra Fithriatus Shalihah Fransiskus Xaverius Pere GUNARTATIK ESTHININGTYAS Hamam Nurrofiq Hasnidar Hasnidar Heri Agus Prasetyo Herin, Sofia Herlina Angraini Susanti Ibnu Rivansyah Subagyo Ibnu Rivansyah Subagyo Ibnu Rivansyah Subagyo Ibrahim, Norshahila Imam Riadi Irfan Pratama Irya Wisnubhadra Julius Bata Jumiyati Juwita Juwita Karlina, Leni Khalifah Samiih Sya'bani Sya'bani Khoirut Tamimi Kris Rahayu Kristina Andryani Larasaty, Raditha Latifah, Retno Leni Karlina Lewoema, Scholastica Larissa Zefira luky kurniawan, luky M. Anjas Leonardi M. Irfan Bahri Mita Oktafani Mu'ti, Dewi Lestari Mukti, Alphi Rinaldi Nalendra Mutaqin Akbar Nabil Fauzan Nanda, Tietan Geovanka Ningsih, Ruly Norshahila Ibrahim Nuning Rusmilawati Nur Sholehah Dian Saputri Nuri Budi Hangesti Nursila Latambaga Nurul Tiara Kadir Nurul Tiara Kadir Okta, Sri Oktafani, Mita Ozzi Suria Ozzi Suria Pipin Yuliyanto Pratama, Bagus Wahyu Ari Pratama, Irfan Puja Waldi Nadeak Puja Waldi Nadeak Puja Purwanto Purwanto Putra, Rio Aji Hadyanta raden roro christawani herawati Raditha Larasaty Rani Dwi Lestari Reny Yuniasanti Resi Dwi Febrianti Rias Ilham Agung Nugroho Rosita, Rani Rully Ningsih Rustiawan, Muhammad Rizqi Akfani saka, Hildegardis Kristina Santoso Pamungkas Sari, Artika Scholastica Larissa Zefira Lewoema Scholastica Lewoema Setiyani, Santi Setyaningsih, Putry Wahyu Sidiq Purnomo, Agus SILA MILDAWATI Simarmata, Penni Wintasari Subagyo, Ibnu Rivansyah Suharjo, Imam Suria, Ozzi Suyoto Suyoto Syalom Kristian Manurung Umi Rosyidah Viony Julianti Sipayung Wahyuningsih Wahyuningsih