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All Journal JURNAL PENDIDIKAN TAMBUSAI TIN: TERAPAN INFORMATIKA NUSANTARA Bulletin of Computer Science Research JUTECH : Journal Education and Technology Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Jurnal Inovasi Pengabdian Masyarakat AMMA : Jurnal Pengabdian Masyarakat JRIIN :Jurnal Riset Informatika dan Inovasi APPA : Jurnal Pengabdian Kepada Masyarakat Jitu: Jurnal Informatika Utama Spectrum: Multidisciplinary Journal PESHUM
Syaeful Machfud
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Klasifikasi Gender Berbasis Citra Wajah Menggunakan Clustering Dan Deep Learning Okky Prasetia; Syaeful Machfud; Rosyani, Perani; Bobi Agustian
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.581

Abstract

Gender classification based on facial images is a significant challenge in the field of computer vision, especially when dealing with unstructured data sourced from social media platforms. This study proposes an integrated approach combining facial image preprocessing, clustering methods, and deep learning to enhance the accuracy of gender classification. The dataset used was obtained from a Big Data Competition and consists of male and female face images sourced from Instagram. Preprocessing was performed using OpenCV for face detection and cropping. Subsequently, the data were clustered using K-Means and DBSCAN algorithms to reduce noise and redundancy. Gender classification was then conducted using a sequential learning model based on Inception_v3, enhanced with Agglomerative Clustering for feature refinement. The evaluation of the system demonstrated strong performance with an accuracy of 92.97%, F1-score of 0.89556, precision of 0.97727, and recall of 0.83069. These results confirm that the integration of clustering techniques and deep learning significantly improves the effectiveness of gender classification based on facial images, especially for open-source and non-curated datasets.
Implementasi Entreprises Resource Planning Berbasis Web dan Mobile Menerapkan Metode SCRUM Syahdan, Muhammad; Nanang, Nanang; Suryaningrat, Suryaningrat; Machfud, Syaeful
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.711

Abstract

Companies operating in the property sector have highly complex business processes involving multiple divisions, such as engineering, marketing, legal, and finance. However, many property companies still manage their data manually and in a fragmented manner, leading to various risks such as data entry errors, communication failures, and other inefficiencies. This study aims to implement an integrated web- and mobile-based Enterprise Resource Planning (ERP) system to support and streamline business processes in a property company, making them more efficient and effective. The development methodology used is Agile, with data collected through interviews, observation, and documentation studies. The system was developed using web and mobile technologies to provide users with flexible access. The implementation results show that the developed ERP system is capable of supporting and improving business processes in the property sector, facilitating real-time data tracking, and increasing operational efficiency. With this system, the company no longer needs to rely on manual data recording and can improve the accuracy of decision-making. This research demonstrates that a digitally based ERP system can be a strategic and effective solution for property companies in facing the challenges of the modern era.
ANALISIS DAMPAK PENERAPAN TEKNOLOGI ARTIFICIAL INTELLIGENCE TERHADAP EFEKTIFITAS PEMBELAJARAN BAGI SISWA SMK Machfud, Syaeful; Halawa, Hedwin Winata; Gea, Kurniaman; Rizky, Mochammad; Indriani, Rifdah
JUTECH : Journal Education and Technology Vol 6, No 1 (2025): JUTECH JUNI
Publisher : STKIP Persada Khatulistiwa Sintang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31932/jutech.v6i1.4362

Abstract

This study aims to analyse the application of Artificial Intelligence (AI) technology to the effectiveness of student learning at SMK Nusantara 1 Ciputat. Using a descriptive qualitative research design, the research subjects involved 30 students selected through purposive sampling. Data were collected through semi-structured interviews and observations, then analysed using thematic analysis method with data triangulation. The results showed that the application of AI technology was able to improve students' understanding of the basic concepts of AI, its types, and its practical applications. After the training, 80% of students understood the basic concepts of AI, an increase from 20% before the training. However, the main challenges faced include infrastructure limitations, such as internet connection, as well as the need for further training for teachers. Support from the school and improved infrastructure are important factors for more effective AI implementation. This research contributes to the vocational education literature in Indonesia by demonstrating the potential of AI as an interactive and adaptive learning tool, and providing recommendations to overcome implementation challenges. Further studies with a broader scope are recommended to explore the long-term impact of AI in vocational learning.
Implementasi Metode Naïve Bayes Untuk Prediksi Penjualan Catering Pada PT Negara Rasa Indonesia Gulo, Benifati; Machfud, Syaeful
Jurnal Riset Informatika dan Inovasi Vol 3 No 8 (2026): JRIIN : Jurnal Riset Informatika dan Inovasi (INPRESS)
Publisher : shofanah Media Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini membahas implementasi metode Naïve Bayes untuk memprediksi penjualan catering pada PT.Negara Rasa Indonesia. Latar belakang penelitian didasari oleh permasalahan penjualan yang belum optimal akibat tidak adanya sistem prediksi penjulan yang terstruktur. Metode Naïve Bayes dipilih karena kesederhanaan, kecepatan, serta kemampuannya dalam mengklasifikasikan data dengan tingkat akurasi yang tinggi. Data yang digunakan dalam penelitian ini adalah data historis penjualan selama dua tahun terakhir, yang telah melalui proses cleaning, labeling, dan transformasi menjadi empat kategori penjualan, yaitu sangat laris, laris, cukup laris, kurang laris. Proses pengujian dilakukan menggunakan perangkat lunak RapidMiner dengan membagi dataset menjadi data latih dan data uji pada berbagai rasio 80:20, Hasil pengujian menunjukkan tingkat akurasi yang sangat tinggi, dengan nilai tertinggi mencapai 91,41% Temuan ini membuktikan bahwa metode Naïve Bayes dapat diandalkan untuk memprediksi penjualan katering, sehingga dapat membantu pengambilan keputusan dalam pengelolaan dan perencanaan penjualan yang lebih efisien di PT. Negara Rasa Indonesia.
Co-Authors Ahmad Basith Amrillah Ibnurhus, Gigih Arfan Yusuf Bobi Agustian Cahyono, Yono Chaerunisa Dimas Satrio Wicaksono Gea, Kurniaman Gigih Amrillah Ibnurhus Gulo, Benifati Halawa, Hedwin Winata HENDRI ARDIANSYAH Herdiansah, Febi Ibnurhus, Gigih Amrillah Indriani, Rifdah Junianto, Mochamad Bagoes Satria Khairudin Khairudin Muhammad Syahdan nanang nanang Nathan Sanjaya Okky Prasetia Perani Rosyani Prasetia, Okky Putri, Khailla Yaman Rizky, Mochammad Suryaningrat, Suryaningrat