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All Journal Jurnal Ilmu Komputer dan Informasi Jurnal Ilmiah Kursor TEKNOLOGI INFORMASI Jurnal Teknologi Informasi dan Ilmu Komputer SMARTICS Journal INOVTEK Polbeng - Seri Informatika Applied Information System and Management SENTIA 2016 SENTIA 2015 Antivirus : Jurnal Ilmiah Teknik Informatika Jurnal Teknologi Informasi dan Terapan (J-TIT) Abdi Dosen : Jurnal Pengabdian Pada Masyarakat Indonesian Journal of Electrical Engineering and Computer Science Abdimasku : Jurnal Pengabdian Masyarakat Best : Journal of Applied Electrical, Science and Technology BHAKTI PERSADA Jurnal Aplikasi IPTEKS (Journal of Applied Sciences and Technology) MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Jurnal INFOTEL Jurnal Informatika Polinema (JIP) International Journal of Integrated Science and Technology Jurnal Pengabdian Kepada Masyarakat Journal of Evrimata: Engineering and Physics
Cahya Rahmad
Politeknik Negeri Malang
Religion Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Transportation Other

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Classification of human scabies skin disease using ConvNeXt Mochammad Zaky Zamroni; Muhammad Afif Hendrawan; Agwin Fahmi Fahanani; Dhelya Widasmara; Cahya Rahmad
Jurnal Ilmiah Kursor Vol. 13 No. 3 (2026)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v13i3.490

Abstract

Scabies is a contagious skin disease caused by Sarcoptes scabiei and remains a health issue in many countries, including Indonesia. Clinical diagnosis is often difficult due to symptom similarities with other skin conditions. This study evaluates the ConvNeXt architecture for scabies classification from skin images to support automated diagnostic systems. The dataset consisted of 273 images (86 scabies and 187 non-scabies), expanded through cropping to 819 images, divided into 488 scabies and 331 non-scabies images. ConvNeXt was trained with fine-tuning at stage 3, implemented using PyTorch on an A100 GPU with the AdamW optimizer. Evaluation used 70:15:15, 80:10:10, and 5-Fold Cross Validation schemes with accuracy, precision, recall, and F1-score metrics. The best configuration (learning rate 0.0001, batch size 32) achieved 95.97% testing accuracy. Overall, ConvNeXt reached 97.75% average accuracy and an F1-score near 0.98, demonstrating highly competitive performance that slightly exceeds established baselines like ResNet-50 (97.69% accuracy). This shows its potential as an accurate and practical solution for automated scabies diagnosis in resource limited healthcare settings.Key words: Automated Diagnosis, ConvNeXt, Deep Learning, Image Classification, Scabies.
Ensuring Data Integrity in Healthcare Records through Hybrid Storage and Blockchain-Backed Audit Trails Azmiansyah Azmiansyah; Yan Watequlis Syaifudin; Cahya Rahmad; Josafat Pratama Susilo; Triana Fatmawati; Yuri Ariyanto; Pramana Yoga Saputra; Indrazno Siradjuddin; Chandrasena Setiadi
Journal of Evrímata: Engineering and Physics Vol. 04 No. 01, 2026
Publisher : PT. ELSHAD TECHNOLOGY INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70822/journalofevrmata.vi.140

Abstract

Ensuring the integrity and auditability of Electronic Health Records (EHRs) is critical for patient safety, regulatory compliance, and trust in digital healthcare. Conventional audit mechanisms such as database logs, are inherently mutable and vulnerable to insider tampering, failing to meet stringent requirements for tamper-proof, independently verifiable data provenance. To address this, this paper proposes and implements a hybrid EHR integrity system that combines PostgreSQL for sensitive clinical data storage with a private Hyperledger Fabric blockchain for immutable audit logging. Only lightweight metadata and SHA-256 hashes of records (not full EHRs) are written to the blockchain, preserving privacy while enabling cryptographic verification. Deployed on modest, heterogeneous hardware and featuring a user-friendly web interface with batched audit workflows, the system achieves 100% tamper detection accuracy, 210 ms average write latency, and 45 TPS throughput that demonstrates feasibility for real-world, resource-constrained clinical environments. Our approach delivers strong, scalable data integrity without prohibitive overhead, bridging the gap between regulatory demands and practical healthcare IT deployment.
Automated drone-assisted detection system for rice leaf pathologies a deep learning approach Erfan Rohadi; Cahya Rahmad; Septian Enggar Sukmana; Aida Sartimbul; Kismet Anak Hong Ping; Dimas Rosiawan; Ahmad Afifuddin Zakki
Indonesian Journal of Electrical Engineering and Computer Science Vol 43, No 1: July 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v43.i1.pp148-156

Abstract

Early and accurate detection of plant diseases is vital for maintaining agricultural productivity. This study investigates an automated disease identification system specifically designed for the IR64 rice cultivar. By combining drone-captured aerial imagery (UAV) taken during the plant's vegetative stage with public datasets, we established a comprehensive training dataset. The study evaluates and compares four convolutional neural network (CNN) architectures, InceptionV3, ResNet50, EfficientNetV2S, and MobileNetV2, assessing their predictive accuracy and real-world computational efficiency. Our 10-fold cross-validation results indicate varying levels of inference speed and accuracy among the models. InceptionV3 and MobileNetV2 displayed the highest stability and minimal misclassification rates across multiple disease types. In contrast, the performance of ResNet50 and EfficientNetV2S fluctuated significantly depending on the detected pathogen. In conclusion, coupling UAV imagery with fine-tuned deep learning models provides a fast, scalable solution for continuous crop monitoring and precision agriculture.
PowerPoint slideshow navigation control with hand gestures using Hidden Markov Model method Cahya Rahmad; Arief Prasetyo; Riza Awwalul Baqy
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 12 No. 1 (2022): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v12i1.7-18

Abstract

Gesture is the easiest and most expressive way of communication between humans and computers, especially gestures that focus on hand and facial movements. Users can use simple gestures to communicate their ideas with a computer without interacting physically. One form of communication between users and machines is in the teaching and learning process in college. One of them is the way the speakers deliver material in the classroom. Most speakers nowadays make use of projectors that project PowerPoint slides from a connected laptop. In running the presentation, the speaker needs to move a slide from one slide to the next or to the previous slide. Therefore, a hand gesture recognition system is needed so it can implement the above interactions. In this study, a PowerPoint navigation control system was built. Digital imaging techniques use a combination of methods. The YCbCr threshold method is used to detect skin color. Furthermore, the morphological method is used to refine the detection results. Then the background subtraction method is used to detect moving objects. The classification method uses the Hidden Markov Model (HMM). With 526 hand images, the result shows that the accuracy of the confusion matrix is 74.5% and the sensitivity is 76.47%. From the accuracy and sensitivity values, it can be concluded that the Hidden Markov Model method can detect gestures quite well as a PowerPoint slide navigation control.
Mask Detection App Uses Haar Cascade and Convolutional Neural Network to Alert Comply with Health Protocols Cahya Rahmad; Nurfaidah Nurfaidah; Supriatna Adhisuwignjo; Mamluatul Hani’ah
Applied Information System and Management (AISM) Vol. 6 No. 2 (2023): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v6i2.31396

Abstract

This study aims to identify the face of a person whether wearing a mask or not wearing a mask accompanied by an appeal to the importance of wearing a mask. The contribution of this paper to science is to provide an overview of the results of accuracy, precision, recall used by the method used with data that can be accessed by many people, so that it can be developed further or can be compared. This system uses two techniques, namely the classification of whether a person is wearing a mask or not using the Convolutional Neural Network (CNN) model. The architecture used is DenseNet-12 to detect human face objects. The data used has a total of 2332 data sets, 200 of which were retrieved manually as research objects, and the rest were obtained from Kaggle. All data is evaluated using the camera in real-time. The test results show that testing scenario one has the highest score with an accuracy of 85% while testing scenario two gets results of 80%, the precision value in testing scenario one gets results of 75%, and testing scenario two has results of 88%. Scenarios 1 and 2 also have the same recall value of 100%. Based on the data analysis, it can be concluded that the use of the Haar Cascade approach and the Convolutional Neural Network with the DenseNet-121 architecture produces good performance in the case of real-time detection of masked and non-masked facial objects.
Penerapan Sistem Informasi Administratif Desa Ngijo Kabupaten Malang menggunakan OpenSID Cahya Rahmad; Arwin Datumaya Wahyudi Sumari; Annisa Puspa Kirana; Moch Zawaruddin Abdullah; Septian Enggar Sukmana
Bhakti Persada Vol. 8 No. 1 (2022): Bhakti Persada Jurnal Aplikasi IPTEKS
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/bp.v8i1.1-8

Abstract

Administrasi kependudukan merupakan rangkaian kegiatan penataan dan penertiban dokumen dan data kependudukan serta pendayagunaan hasilnya untuk pelayanan publik dan pembangunan sektor lain. Desa Ngijo adalah salah satu desa unggulan yang ada di Kabupaten Malang. Kantor Desa Ngijo yang berada di Kabupaten Malang merupakan salah satu instansi pemerintah yang bergerak di bidang pelayanan masyarakat, namun dalam kinerja pelayanan masyarakat Balai Desa ini memiliki kendala dan permasalahan yaitu belum adanya ketersedian sistem informasi yang dapat menangani administrasi kependudukan. Desa Ngijo sebagai salah satu instansi pemerinatahan, memiliki peran yang penting yaitu sebagai pengelola data kependudukan di tingkat desa. Pengelolaan data kependudukan di Desa Ngijo saat ini masih belum memaksimalkan penggunaan teknologi informasi untuk pengelolaannya, sehingga masih terdapat beberapa kekurangan dan kendala yang dihadapi. Seperti masih terdapat kerangkapan data kependudukan, kesulitan dalam pencarian data, serta pembuatan laporan kependudukan. Sehingga pelayanan kepada masyarakat serta kerja dari perangkat desa menjadi kurang efektif dan efisien. Oleh karena itu dibutuhkan sebuah sistem informasi terkomputerisasi yang dapat digunakan untuk mengelola data tersebut. Metode yang digunakan untuk perancangan sistem administrasi kependudukan yaitu dengan metode prototyping. Dengan adanya sistem informasi administrasi kependudukan yang berbasiskan website ini, dapat memudahkan pengelolaan data kependudukan. Hal ini terwujud dalam persepsi dari 98% peserta pelatihan yang menyatakan bahwa sistem ini akan menjadi komponen layanan yang sangat bermanfaat bagi warga desa.
Co-Authors A. Shabrina Afrah Ade Putra Lesmana Adhisuwignjo, Supriatna Afrah, A. Shabrina Agwin Fahmi Fahanani Ahmad Afifuddin Zakki Ahmadi Yuli Ananta Ahya, Anugrah Vito Aida Sartimbul Alan Rizky Wardana Alfian, Ahmad Alfian Alviando Wisang , Muhammad Amanda Patria Putra Amelia Marshanda Andriani Parastiwi Anik N. Handayani Annisa Puspa Kirana Anugrah Nur Rahmanto Anugrah Vito Ahya Ariadi Retno Tri Ariadi Retno Tri Hayati Ririd Arie Rachmad Syulistyo Arief Prasetyo Arwin Datumaya Wahyudi Sumari Asrori Asrori Azmiansyah Azmiansyah Bagas Satya Dian Nugraha Banni Satria Andoko Bayu Hari Saputro Ba’ar Wasil Razzaq Budi Harijanto Cahyono, Lulus Okta Candra Bella Vista Chandrasena Setiadi Deddy Kusbianto Devi Zettyara Dewandaru, Fajar Dhelya Widasmara Dika Rizky Yunianto Dimas Rosiawan Dimas Rossiawan Hendra Putra Dimas Wahyu Wibowo Dodo Zulkarnain Dwi Puspitasari Dwi Puspitasari DWI PUSPITASARI Eka Larasati Amalia Eko Hendri S Eko Yudiyanto Ekojono Ekojono Erfan Rohadi Erlangga Adha Widyatama Faisal Rahutomo Fajar Dewandaru Febriyanto, Nugroho Frangky Tupamahu Hapsari, Indri Tri Haryono Haryono Hendra Pradibta Ika Oktavia Pristisari Imam Fahrur Rozi Indrazno Siradjuddin Indri Tri Hapsari Inta Widiastuti Josafat Pratama Susilo Kismet Anak Hong Ping Kris Witono Laras Palupi P Lesmana, Ade Putra Luqman Affandi M Hasyim Ratsanjani Mamluatul Hani’ah Marcelina Alifia Rahmawati Martin Nugroho Parapat Maula, Ahmad Zaky Moch Zawaruddin Abdullah Moch. Febry Ramadhani Mochammad Zaky Zamroni Muhammad Afif Hendrawan Muhammad Bisri Musthafa Mungki Astiningrum Musthafa, Muhammad Bisri Nabila Rasyidah Ngatmari Ngatmari Ngatmari, Ngatmari Ni’ma Shoumi, Milyun Noor Hidayat, Mohamad Nugroho Febriyanto Nur Afifi, Yunis Fiatin Nurfaidah Nurfaidah Nurudin Santoso Palupi P, Laras Parapat, Martin Nugroho Pramana Yoga Saputra Pramana Yoga Saputra Pristisari, Ika Oktavia Putra, Amanda Patria Putra, Yudistira Eka Rahmat Satrio Wibowo Ramadhani, Moch. Febry Razzaq, Ba’ar Wasil Riza Awwalul Baqy Rosa A. Asmara Rosa Andrie Asmara Rudy Ariyanto Santoso, Nurudin Saputro, Bayu Hari Satworo Adiwidodo Septian Enggar Sukmana Septian Enggar Sukmana Subhan Indra Prayoga surya Wijaya, Wldan Tri, Ariadi Retno Triana Fatmawati Ulla Delfana Rosiani Vandry Eko Haris Setiyanto Vivin Ayu Lestari Widiastuti, Inta Yan Watequlis Syaifudin Yudistira Eka Putra Yuninanto, Dika Rizky Yuri Ariyanto Zulkarnain, Dodo