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All Journal International Journal of Evaluation and Research in Education (IJERE) JUPITER (Jurnal Pendidikan Teknik Elektro) Indonesian Journal of Applied Informatics Industri Inovatif : Jurnal Teknik Industri Jurnal Mnemonic JATI (Jurnal Mahasiswa Teknik Informatika) JISA (Jurnal Informatika dan Sains) Jurnal Informatika Teknologi dan Sains (Jinteks) JUSIFOR : Jurnal Sistem Informasi dan Informatika International Journal of Educational Best Practices Journal of Computer Science Contributions (Jucosco) Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Febriana Santi Wahyuni
Institut Teknologi Nasional Malang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Journal : Indonesian Journal of Applied Informatics

 1 
Implementasi Convolutional Neural Network (CNN) untuk Face Recognition pada Sistem Presensi Kehadiran Moch Arif Rochmanullah; Nurlaily Vendyansyah; Febriana Santi Wahyuni
IJAI (Indonesian Journal of Applied Informatics) Vol 9, No 2 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v9i2.95563

Abstract

Abstrak : Sistem presensi merupakan elemen penting dalam memastikan kehadiran, terutama di lingkungan pendidikan dan pekerjaan. Penelitian ini bertujuan mengembangkan sistem presensi berbasis face recognition menggunakan metode Convolutional Neural Network (CNN) untuk mengatasi kelemahan presensi manual yang rentan terhadap kecurangan, seperti di Prodi Teknik Informatika ITN Malang. Model CNN dilatih dengan deep learning menggunakan dataset wajah mahasiswa untuk mengenali pola unik fitur wajah. Hasilnya, model mencapai training accuracy sebesar 97%, validation accuracy sebesar 90%, dan pengujian mencapai accuracy 93%. Sistem ini meningkatkan efisiensi absensi dan akurasi identifikasi hingga 93%, sekaligus mengurangi potensi kecurangan.CNN terbukti andal dalam mendukung presensi berbasis teknologi dengan pengelolaan lebih praktis. Kendati demikian, performa model masih dapat ditingkatkan melalui pengayaan dataset dan optimasi model. Sistem ini berpotensi besar meningkatkan keandalan dan keamanan proses presensi, menjadi solusi inovatif dalam pengelolaan kehadiran di era digital.=====================================================Abstract :The attendance system is a crucial element in ensuring presence, especially in educational and workplace settings. This study aims to develop a face recognition-based attendance system using the Convolutional Neural Network (CNN) method to address the weaknesses of manual attendance prone to fraud, as observed in the Informatics Engineering Study Program at ITN Malang. The CNN model was trained using deep learning techniques with a student face dataset to recognize unique facial features. The results show the model achieved a training accuracy of 97%, validation accuracy of 90%, and testing accuracy of 93%. This system improves attendance efficiency and identification accuracy by 93%, while reducing the potential for fraud. CNN has proven reliable in supporting technology-based attendance with more practical management. However, the model’s performance can still be improved through dataset enrichment and optimization. This system holds significant potential to enhance the reliability and security of attendance processes, providing an innovative solution for managing attendance in the digital era.
Aplikasi Presensi Siswa Berbasis Location Based Services (LBS) Dengan Haversine Formula Di SMK Islam Al-Futuhiyyah Mohammad Harifin; Nurlaily Vendyansyah; Febriana Santi Wahyuni
IJAI (Indonesian Journal of Applied Informatics) Vol 9, No 2 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/ijai.v9i2.95566

Abstract

Abstrak : Perkembangan teknologi informasi membawa dampak signifikan di bidang pendidikan, termasuk dalam sistem presensi siswa. Penelitian ini bertujuan untuk mengembangkan aplikasi presensi siswa berbasis Android dengan menggunakan metode Location Based Services (LBS) di SMK Islam Al-Futuhiyyah. Metode yang digunakan adalah Research and Development (R&D) dengan model pengembangan perangkat lunak Waterfall, meliputi analisis kebutuhan, desain, implementasi, pengujian, dan evaluasi. Aplikasi ini menggunakan metode Haversine untuk mengukur jarak antara lokasi siswa dan lokasi sekolah, sehingga memastikan presensi dilakukan di area yang telah ditentukan. Hasil pengujian menunjukkan bahwa aplikasi ini berhasil memvalidasi presensi dengan akurasi tinggi, di mana Haversine Formula menghasilkan akurasi presensi hingga 100%. Pengujian Black Box memastikan semua fungsi aplikasi berjalan sesuai spesifikasi, sedangkan pengujian LBS membuktikan keakuratan dalam mendeteksi lokasi siswa. Selain itu, berdasarkan User Acceptance Testing (UAT) yang melibatkan siswa dan guru, aplikasi ini memperoleh skor kepuasan 81,7%. Aplikasi ini juga mempermudah siswa dalam melakukan presensi, sekaligus membantu guru dan operator sekolah dalam memantau dan mengelola data presensi. Implementasi aplikasi ini memberikan solusi efektif dan efisien untuk menggantikan metode presensi manual yang kurang praktis. Penelitian ini diharapkan dapat meningkatkan kualitas layanan pendidikan di SMK Islam Al-Futuhiyyah dan menjadi referensi bagi pengembangan sistem presensi berbasis teknologi di lembaga pendidikan lainnya===================================================Abstract : The development of information technology has a significant impact on the field of education, including in the student attendance system. This study aims to develop an Android-based student attendance application using the Location Based Services (LBS) method at SMK Islam Al-Futuhiyyah. The method used is Research and Development (R&D) with the Waterfall software development model, including needs analysis, design, implementation, testing, and evaluation. This application uses the Haversine method to measure the distance between the student's location and the school location, thus ensuring that attendance is carried out in a predetermined area. The test results show that this application has successfully validated attendance with high accuracy, where the Haversine Formula produces attendance accuracy of up to 100%. Black Box testing ensures that all application functions run according to specifications, while LBS testing proves accuracy in detecting student locations. In addition, based on User Acceptance Testing (UAT) involving students and teachers, this application received a satisfaction score of 81,7% This application also makes it easier for students to take attendance, while helping teachers and school operators to monitor and manage attendance data. The implementation of this application provides an effective and efficient solution to replace the less practical manual attendance method. This research is expected to improve the quality of educational services at Al-Futuhiyyah Islamic Vocational School and become a reference for the development of technology-based attendance systems in other educational institutions.
Co-Authors Abdul Wahid Adi Pratama, Sena Adtya Baskara, Galih Agung Panji Sasmito AHMAD FAISOL Ahmad Ridwan Akbar Setiawan, Farhan Ali Mahmudi Ali Mashudi, Rafiu Andrianto, Erfanda Ari Ramadhan, Muhammad Ariobimo Wijaya, Dhiemas Ariwibisono, F.X Arniyanto, Muhammad Dwi Arya Lutfi, Muhammad Asyam Naufal, Kasih Benjamin Maahury, David Budi Fathony Deddy Rudhistiar Desmile, Janico Dhori Novanda Azza Diouf Ghiffary, Fiqih Dwi Yulianto, Afri Dzulfikar, Ahmad Eksanti Saragih, Dewi Fahrudi Setiawan, Ahmad Firstiano, Ivo Furqon, Moch Nurul Ghani Muttaqin, Abdul Ghozy, Ahmad Hani Zulfia Zahro Hasfa, Firmansyah Hidayati, Nofia Holifah, Musdholi Indriastuti, Ira Inzanul Huda, Muhammad Irmalia Suryani Faradisa Jalu Kinayun, Surya Janeananto Sanjaya, Andrew Karina Auliasari Kevin Merico Setiawan Kurniawan, Moch. Rizal Lakzmi, Prita Patricia Like Titi Sanjaya, Jecky Manuela, Devina Dorkas Mega Aliesa WP, Pramesty Mira Orisa Moch Arif Rochmanullah Mohammad Harifin Muhammad Rizal Pahlawan, Rifki Nayottama, Nayaka Apta Nugroho Syahputro, Fadhil Nurlaily Vendyansyah Prismaswara Prasetya , Renaldi Pristiani, Tenti Purwanti, Prasiska Dwi Ra'uf, Abdur Rafi, Mochammad Rega Firmansyah, Dicky Renaldi Primaswara Prasetya Revano Budiansyah, Moch Rhomadon, Rifal Rifqi Rizki, Fakhrizal Rizky Aditya Juniantoro, Mochammad rosada, uyun Roudhotul Rohmah, Iva Sabilur Rosyad, Hilal Sakrani, Fikriadi Sandy Nataly Mantja Sandy Nataly Mantja, Sandy Nataly Saputra, Dwi Adi Satrio, Imam Sentot Achmadi Sidik Noertjahjono Suryo Adi Wibowo Taralandu, Deriatno Vendiansyah, Nurlaily Wibowo, Nungki Widhi Nugraha, Brilliananda Willyam Saputra, Leonardo Xaverius Ariwibisono, Franciscus Xaverius Ariwibisono, Fransiskus Yosep Agus Pranoto Zidan Rusminto, Muhammad Zufar Ardana, Fadel Zulfia Zahro’, Hani Zulfia, Hani