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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) Tematik : Jurnal Teknologi Informasi Komunikasi Jurnal Dinamika Informatika (JDI) AMMA : Jurnal Pengabdian Masyarakat
Ahmad Rifai
STMIK IKMI Cirebon
Humanities Chemistry Computer Science & IT Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing

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SMART ATTENDANCE TRACKING SYSTEM EMPLOYING DEEP LEARNING FOR FACE ANTI-SPOOFING PROTECTION Bani Nurhakim; Ahmad Rifai; Dian Ade Kurnia; Dadang Sudrajat; Ujang Supriatna
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 3 (2025): JITK Issue February 2025
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i3.5992

Abstract

Conventional attendance systems face challenges in accuracy and efficiency, often vulnerable to spoofing and data manipulation. This study addresses these issues by developing a smart attendance system integrating Deep Learning-based facial recognition with anti-spoofing technology. The system ensures secure and reliable attendance authentication while automating and enhancing management processes. Utilizing a convolutional neural network (CNN) architecture, the system processes raw facial images directly without additional feature extraction, improving accuracy and efficiency. A novel training strategy, termed 50 Random Samples-30 Sub-epochs Count-1 Epoch, is introduced to optimize the training process. This strategy involves random sampling during each forward pass and grouping 30 passes as one epoch, enabling the use of complex CNN architectures and automatic dataset expansion. The system achieves 98.90% accuracy in identifying genuine attendance, maintaining a confidence level above 80%, significantly reducing spoofing risks and errors. This innovative solution has significant implications, particularly for educational institutions. It automates attendance tracking, minimizes manual effort, reduces errors, and supports disciplinary enforcement through accurate data. Moreover, its scalability allows for application across various environments, offering benefits to a wide range of institutions. By enhancing data accuracy and operational efficiency, this system sets a foundation for smarter, more reliable attendance management, strengthening administrative practices in education and beyond.
Peningkatan Kreativitas Karang Taruna Melalui Pelatihan Desain Grafis dan Konten Digital Ahmad Faqih; Ahmad Rifai; Mohamad Riad Solihin; Muhammad Daffa Ayyasy
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 03 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

The role of youth in village development is becoming increasingly important in the digital era, particularly in promoting local potential, social activities, and creative economic initiatives. One of the main challenges faced by youth organizations such as Karang Taruna is the limited ability to produce engaging digital content and graphic designs, despite the great potential of social media as a means of promotion and communication. This Community Service Program (PKM) aims to enhance the capacity of Karang Taruna members in creating creative content and graphic design using simple and accessible digital applications. The program was carried out in several stages: identifying participants’ needs, developing training modules, conducting in-person training sessions, and providing post-training assistance. The training materials included the basics of graphic design, understanding visual elements (color, typography, layout), simple photography and videography techniques using smartphones, and the use of design applications such as Canva, CapCut, and Pixellab. Participants also practiced creating social media content to promote village activities, local MSMEs, and social campaigns managed by Karang Taruna. The results show a significant improvement in participants' skills in designing posters, Instagram feeds, and short videos for publication purposes. Some of the participants' works have been uploaded to Karang Taruna’s official social media accounts and received positive responses from the community. This program not only enhanced technical skills but also fostered confidence, creativity, and a spirit of collaboration among members. It makes a tangible contribution to empowering village youth through digital literacy and creative media. Moving forward, this training can be developed into a sustainable program to strengthen the village’s digital identity and promote local potential through community-based efforts.
Penerapan Model LSTM Univariat dengan Walk-Forward Validation untuk Estimasi Harga Saham Nokia Ahmad Rifai; Roni Saputra; Dian Ade Kurnia; Fatihanursari Dikananda
TEMATIK Vol. 13 No. 1 (2026): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2026
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v13i1.3000

Abstract

Prediksi harga saham merupakan permasalahan yang kompleks karena karakteristik data deret waktu finansial yang bersifat non-linear, volatil, dan dinamis. Meskipun algoritma Long Short-Term Memory (LSTM) terbukti efektif dalam menangkap pola temporal, banyak penelitian sebelumnya menggunakan pendekatan multivariat yang melibatkan variabel dengan korelasi sangat tinggi sehingga berpotensi menimbulkan redundansi informasi dan meningkatkan kompleksitas model. Penelitian ini mengusulkan model LSTM univariat untuk memprediksi harga saham Nokia Corporation (NOK) dengan menggunakan harga penutupan sebagai variabel masukan tunggal. Data historis harian periode 1 Oktober 2015 hingga 24 Oktober 2025 sebanyak 2.532 observasi diperoleh dari Yahoo Finance. Sebelum proses pemodelan, dilakukan analisis korelasi terhadap variabel Open, High, Low, Close, dan Volume. Hasil analisis menunjukkan bahwa variabel harga memiliki korelasi yang sangat tinggi (r > 0,99), sedangkan variabel Volume memiliki korelasi yang sangat rendah terhadap variabel harga (−0,052 ≤ r ≤ −0,043). Berdasarkan hasil tersebut, harga penutupan dipilih sebagai fitur utama dalam pemodelan. Untuk mengevaluasi performa model pada kondisi prediksi yang realistis, diterapkan metode Walk-Forward Validation (WFV) sebanyak 30 iterasi. Hasil pengujian menunjukkan bahwa model memperoleh nilai MSE sebesar 0,0260, RMSE sebesar 0,1613, MAE sebesar 0,1086, MAPE sebesar 2,75%, dan koefisien determinasi (R²) sebesar 0,9446. Hasil tersebut menunjukkan bahwa model mampu menjelaskan 94,46% variasi harga saham dengan tingkat kesalahan prediksi yang rendah. Penelitian ini menyimpulkan bahwa model LSTM univariat yang didukung oleh proses seleksi fitur yang sistematis dan validasi temporal yang robust mampu menghasilkan prediksi harga saham yang andal dengan kompleksitas yang lebih rendah dibandingkan pendekatan multivariat konvensional.
Analisis Sentimen Ulasan by.U dengan Pelabelan Rating dan Leksikon Menggunakan Multinomial Naïve Bayes Fatihanursari Dikananda; Bani Nurhakim; Dian Ade Kurnia; Ahmad Rifai; Mugi Praseptiawan
TEMATIK Vol. 13 No. 1 (2026): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Juni 2026
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v13i1.2996

Abstract

Perkembangan layanan telekomunikasi digital mendorong bertambahnya jumlah ulasan pengguna yang digunakan sebagai bahan informasi guna mendukung pengambilan keputusan berbasis data. Penelitian ini bertujuan menganalisis sentimen ulasan aplikasi by.U menggunakan dua metode pelabelan data, yaitu rating-based labeling dan lexicon-based labeling, menggunakan algoritma Multinomial Naïve Bayes (MNB). Metode penelitian menerapkan framework Knowledge Discovery in Databases yang meliputi tahapan selection, preprocessing, transformation, data mining, dan evaluation. Dataset penelitian diperoleh dari Google Play sebanyak 8.000 ulasan berbahasa Indonesia. Tahap prapemrosesan mencakup cleaning, case folding, normalisasi, tokenisasi, stopword removal, serta stemming. Representasi fitur dilakukan menggunakan TF-IDF, sedangkan penyeimbangan data diterapkan melalui metode SMOTE. Evaluasi model dilakukan menggunakan metrik accuracy, precision, recall, dan F1-score dengan skema 10-fold cross validation. Hasil penelitian menunjukkan bahwa pendekatan lexicon-based labeling memberikan performa yang lebih baik dibandingkan rating-based labeling. Pendekatan rating-based menghasilkan accuracy sebesar 82,59%, precision 83,79%, recall 82,59%, dan F1-score 82,43%. Sementara itu, pendekatan lexicon-based memperoleh accuracy sebesar 88,96%, precision 89,69%, recall 88,96%, serta F1-score 88,91%. Temuan tersebut menunjukkan bahwa strategi pelabelan memiliki pengaruh terhadap performa klasifikasi sentimen. Pendekatan berbasis leksikon dinilai lebih efektif karena mampu memahami konteks linguistik dan ekspresi emosional pengguna secara lebih baik dibandingkan pendekatan berbasis rating.
Analisis Kualitas Jaringan Hotspot Menggunakan Metode Quality of Service (QoS) dalam Mendukung Kegiatan Belajar Mengajar Di Sekolah Menengah Kejuruan Negeri 1 Gebang Mochammad Fatha Mudzhaffar; Martanto; Arif Rinaldi Dikananda; Ahmad Rifai
Jurnal Dinamika Informatika Vol. 14 No. 1 (2025): Jurnal Dinamika Informatika Volume 14 Nomor 1
Publisher : Program Studi Informatika Universitas PGRI Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31316/jdi.v14i1.513

Abstract

Hotspot adalah jaringan nirkabel yang menyediakan akses internet kepada pengguna melalui perangkat Wi-Fi. Kualitas jaringan hotspot sangat penting dalam mendukung berbagai aktivitas, termasuk kegiatan belajar mengajar. Untuk menilai performa jaringan, metode Quality of Service (QoS) digunakan sebagai pendekatan standar dalam mengukur parameter-parameter utama jaringan, seperti throughput, packet loss, delay, dan jitter. Penelitian ini bertujuan untuk menganalisis kualitas jaringan hotspot di SMK Negeri 1 Gebang menggunakan metode QoS. Hasil penelitian menunjukkan bahwa nilai throughput berada dalam kategori "Buruk" hingga "Sangat Buruk" pada jam-jam trafik tinggi (12:00-15:00), dengan nilai berkisar antara 150-318 kbps, sehingga memerlukan optimasi jaringan. Di sisi lain, parameter packet loss tercatat 0%, yang menempatkannya dalam kategori "Sangat Baik." Nilai delay berkisar antara 10,12 ms hingga 30,01 ms, menunjukkan responsivitas jaringan yang baik dalam kategori "Sangat Baik." Sementara itu, nilai jitter berada dalam kategori "Baik" meskipun mengalami sedikit fluktuasi pada jam sibuk. Secara keseluruhan, meskipun performa jaringan dinilai baik dalam aspek packet loss, delay, dan jitter, peningkatan kualitas throughput sangat diperlukan untuk memastikan koneksi yang stabil dan berkualitas, khususnya pada jam trafik tinggi. Temuan ini memberikan dasar untuk pengembangan strategi optimasi jaringan guna mendukung kegiatan pendidikan secara lebih efektif.
Pendampingan Legalitas Usaha Dan Penguatan Profie Digital Bagi UMKM Kota Cirebon Ahmad Rifai; Nana Suarna; Difa Aulia Farradila; Muhammad Zeya Sebastian
AMMA : Jurnal Pengabdian Masyarakat Vol. 4 No. 5 : Juni (2025): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a strategic role in supporting regional economic development; however, many still face challenges related to business legality and digital business identity. These limitations restrict their access to government assistance programs, financing opportunities, business partnerships, and broader market promotion. This community service program aimed to enhance the capacity of MSMEs through business legality assistance and digital business profile development for five MSMEs in Cirebon City, namely Warung Kopi/Angkringan, Wonton, Orenz Drink, Noenk Ice, and Afiqah Banana. The program employed a participatory approach consisting of needs assessment, business legality education, assistance in obtaining the Business Identification Number (Nomor Induk Berusaha/NIB), digital business profile development, implementation support, and monitoring and evaluation. The results demonstrated that all participating MSMEs improved their understanding of the importance of business legality, organized their business administration more systematically, and developed comprehensive digital business profiles containing business identity, product information, visual documentation, contact details, and communication channels. Furthermore, the assistance enhanced participants' ability to utilize digital business profiles as effective information and promotional media, thereby strengthening their business identity and increasing consumer accessibility. The integrated mentoring model successfully combined administrative strengthening with digital transformation within a systematic empowerment framework. This program contributes to improving MSMEs' capacity to establish better business governance, enhance consumer trust, and strengthen the competitiveness of local products in a sustainable manner.
Co-Authors Ahmad Faqih Arif Rinaldi Dikananda Bani Nurhakim Dadang Sudrajat Dian Ade Kurnia Difa Aulia Farradila Fatihanursari Dikananda Martanto . Mochammad Fatha Mudzhaffar Mohamad Riad Solihin Muhammad Daffa Ayyasy Muhammad Zeya Sebastian Nana Suarna Praseptiawan, Mugi Roni Saputra Ujang Supriatna