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All Journal Techno.Com: Jurnal Teknologi Informasi Journal of Applied Geospatial Information Jurnal Informatika dan Multimedia Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control INOVTEK Polbeng - Seri Informatika Jurnal ABDINUS : Jurnal Pengabdian Nusantara Prosiding Conference on Research and Community Services Community Empowerment Jurnal Minfo Polgan (JMP) Jurnal Pengabdian pada Masyarakat Ilmu Pengetahuan dan Teknologi Terintegrasi MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Jurnal Informatika dan Multimedia International Journal of Entrepreneurship, Business, and Creative Economy Jurnal Teknik Ilmu dan Aplikasi Prosiding Seminar Hasil Penelitian dan Pengabdian Kepada Masyarakat Jurnal Informatika Polinema (JIP) Journal of Information Technology and Cyber Security Jurnal Pengabdian Kepada Masyarakat KOPEMAS
Rinanza Zulmy Alhamri, Rinanza Zulmy
PSDKU Politeknik Negeri Malang Kediri, D3 Manajemen Informatika
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Optimasi Hyperparameter Convolutional Neural Network untuk Klasifikasi Citra Makanan Selingan Kunti Eliyen; Abidatul Izzah; Toga Aldila Cinderatama; Rinanza Zulmy Alhamri
Jurnal Minfo Polgan Vol. 15 No. 2 (2026): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v15i2.16523

Abstract

Optimasi hyperparameter adalah langkah mendasar dalam meningkatkan kinerja model Convolutional Neural Network (CNN). Penelitian ini bertujuan untuk mengoptimalkan hyperparameter dalam arsitektur EfficientNetB0 menggunakan Genetic Algorithm (GA) untuk meningkatkan akurasi klasifikasi gambar snack. Dataset citra makanan selingan terdiri dari 250 citra yang diklasifikasikan dalam 10 kelas, dengan 80% dialokasikan untuk data pelatihan dan 20% untuk data validasi. Proses optimasi dilakukan dengan menentukan nilai terbaik dari learning rate, dropout rate, dan batch size. Metode GA diterapkan untuk menemukan kombinasi optimal melalui proses seleksi, crossover, dan mutasi selama beberapa generasi. Hasilnya menunjukkan bahwa penggunaan GA dapat menentukan kombinasi hyperparameter yang meningkatkan akurasi model dibandingkan dengan seleksi manual. Kombinasi hyperparameter terbaik yang diperoleh adalah learning rate 0,000670, dropout rate 0,34, dan freeze ratio 0,73. Untuk mencegah overfitting, selama pelatihan diterapkan penghentian dini dan pengurangan tingkat training. Model ini dilatih untuk 40 epoh dan memperoleh 92% akurasi validasi. Hasil ini menunjukkan efektivitas GA dalam mempercepat proses menemukan hiperparameter optimal di CNN berbasis EfficientNetB0, terutama untuk kumpulan data citra makanan skala kecil yang rentan terhadap overfitting.
Application for data collection and monitoring of COVID-19 patients in Sukorame Community Health Center Toga Aldila Cinderatama; Rinanza Zulmy Alhamri; Fery Sofian Efendi; Kunti Eliyen; Benni Agung Nugroho
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.v12i1.19-30

Abstract

The significant increase in COVID-19 cases in Indonesia in May-July 2021 overwhelmed health workers. One of the efforts to monitor the spread of COViD-19 disease is collecting data on patients and proper monitoring. For example, the Sukorame Community Health Center, Mojoroto Kediri, does not yet have an application to record and monitor COVID-19 patients. Data collection is currently done manually by writing in books and excel. This study designed and built a data collection and monitoring application for COVID-19 patients to help Puskesmas staff obtain more accurate patient data and monitor the related patient data. This study implements the waterfall method, including system requirements, design, implementation, verification, and maintenance. The results of this study are the applications that can help and facilitate Community Health Center in collecting data on COVID-19 as a form of effort in overcoming and preventing the spread of COVID-19 in the work area of Sukorame Community Health Center, Kediri City. Based on the user satisfaction questionnaire results, 75% of users consisting of staff and heads of community health centers were helped by this application.
IoT-based environmental monitoring and hazard notification system for traditional blacksmith workshops Alhamri, Rinanza Zulmy; Zayn, Afta Ramadhan
Community Empowerment Vol. 11 No. 1 (2026)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/ce.15432

Abstract

Production processes in traditional blacksmith workshops often neglect Occupational Health and Safety (OHS) due to unmonitored exposure to smoke, dust, and extreme temperatures. This program aims to enhance workplace safety at Dapur Setiawan, Tulungagung, through the development of an Internet of Things (IoT)-based environmental monitoring system. The system is designed to monitor dust concentration, smoke levels, room temperature, and furnace temperature in real-time via an Android application. The development methodology included hardware design using integrated sensors, Firebase database synchronization, and functional testing. Evaluation results showed that all sensors operated accurately, with responsive danger notification systems and buzzers. Field evaluations revealed that while temperature and smoke levels remained normal, dust concentrations during production hours reached "unhealthy" levels. The implementation of this technology allows partners to monitor working conditions precisely and rapidly, providing a data-driven basis for improving ventilation systems to minimize workplace accidents and occupational diseases.
Co-Authors Abidatul Izzah Agustono Heriadi Agustono Heriadi Agustono Heriadi Agustono Heriadi, Agustono Andika Kurnia Adi Pradana Ari Susanto, Bagus Arif Syamsudin Ashafidz Fauzan Dianta Ashafidz Fauzan Dianta Ashafidz Fauzan Dianta Ashafidz Fauzan Dianta, Ashafidz Fauzan Ashafidz Fauzan, Ashafidz Atik Tri Andari Benni Agung Nugroho Benni Agung Nugroho Benni Agung Nugroho Benni Agung Nugroho, Benni Agung Candra Bella Vista Devianti, Meryta Elfarozi, Danang Eliyen, Kunti Ellya Nurfarida Erma Puspitasari, Dian Fadelis Sukya Fadelis Sukya Fadelis Sukya, Fadelis Fery Sofian Efendi Fery Sofian Efendi Fery Sofian Effendi Fery Sofian Effendi Fitria Nur Hamidah, Fitria Nur Gunawan Budiprasetyo Hamdani Arif Hendrawan, Muhammad Afif Irfin Sandra Asti Kunti Eliyen Kunti Eliyen Kusuma, Selvia Ferdiana Maskur, M Moch Zawaruddin Abdullah Mujahid Wahyu Ratna Widyastuti Ratna Widyastuti, Ratna Riswanda Al Farisi Selvia Ferdiana Kusuma Setianingsih, Novie Astuti Shofi Romal ‘Izzul ‘Ula Syamsudin, Arif Toga Aldila Cinderatama Trisha Alfandi Yanuarmawan, Dion Yoppy Yunhasnawa Zayn, Afta Ramadhan