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All Journal Jurnal Ilmiah Teknik Informatika dan Komunikasi Jurnal Pengabdian Masyarakat dan Riset Pendidikan Jurnal Intelek Dan Cendikiawan Nusantara Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi
Ferry Cahyadi
Unknown Affiliation
Humanities Computer Science & IT Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Mathematics Other

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Integrasi Teknologi IoT pada Sistem CRM untuk Meningkatkan Kepuasan dan Retensi Pelanggan Ferry Cahyadi
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 1 (2025): Februari: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i1.688

Abstract

The Internet of Things (IoT) has become one of the leading technologies in digital transformation, including in customer relationship management (CRM). This article discusses how IoT integration in CRM systems can improve customer satisfaction and retention through real-time data collection, service personalization, and data-driven decision making. With a literature study and implementation analysis, this research shows that IoT technology can provide deeper insight into customer behavior, improve operational efficiency, and create a more satisfying customer experience.
Sosialisasi Keamanan Digital dan Pencegahan Kejahatan Siber di SMAN 1 Air Joman : Pengabdian Muhammad Yasin; Seprina Aulia Putri; Adhistya Aulia DH; Syahrul; Ferry Cahyadi; Ilham Habinsaran; Fikri Vahriza
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 2 (2025): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 2 (October 202
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i2.2873

Abstract

KKN (Real Work Lecture) is a community service program in which students apply their academic knowledge in real-world contexts. One of the initiatives carried out was a digital security awareness program at SMAN 1 Air Joman, designed to improve students’ understanding, pratical skills, and awareness in dealing with cybercrime threats. This study used a descriptive method with pre-test and post-test questionnaires distributed to 40 eleventh-grade students. The results showed significant improvements in three areas. In knowledge, students’ understanding of personal data protection, types of cybercrime, and the ability to identify hoaxes increased from an average of 35-30% to 85-90%. In practice, the use of strong passwords, two-step verification, and caution toward suspicious links rase from 28-42% to 78-92%. In awareness, students intending to apply digital safety in daily life grew from 37% to 93%, and 95% found the program highly beneficial. These findings indicate that KKN-based socialization effectively prevents cybercrime and is worth continuing as a sustainable school program highly beneficial. These findings indicate that KKN-based socialization effenctively prevents cybercrime and is worth continuing as a sustainable school program
Sistem Penilaian Hasil Belajar Mahasiswa Menggunakan Logika Fuzzy Metode Mamdani Delyanti Putri Sitorus; Ferry Cahyadi; Khairul Saleh
Jurnal Intelek Dan Cendikiawan Nusantara Vol. 2 No. 6 (2025): Desember 2025 - Januari 2026
Publisher : PT. Intelek Cendikiawan Nusantara

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

Abstract

Prestasi belajar adalah hasil belajar siswa tehadap pendidikan yang dijalaninya di sekolah. Penelitian ini bertujuan mengetahui prestasi belajar siswa dengan mengaplikasikan logika fuzzy mamdani. Sistem penilaian hasil belajar siswa merupakan aspek penting dalam pendidikan tinggi untuk mencapai pencapaian akademik secara tujuan. Namun, metode penilaian konvensional sering kali tidak mampu menangani diskusi dan subjektivitas dalam nilai data. Penelitian ini mengembangkan sistem penilaian hasil belajar siswa menggunakan logika fuzzy dengan metode Mamdani (Mamdani Fuzzy Inference System) untuk mengatasi keterbatasan tersebut. Logika fuzzy adalah salah satu cabang ilmu kecerdasan buatan untuk membangun sistem cerdas. Logika fuzzy sering digunakan dalam pemecahan masalah yang menjelaskan sistem bukan melalui angka-angka, melainkan secara linguistik, atau variable-variabel yang mengandung ketakpastian/ ketidaktegasan. 
Penerapan Learning Vector Quantization (LVQ) Untuk Klasifikasi Data Citra Digital Bambang Irwansyah; Delyanti Putri Sitorus; Rezki Abdillah; Rizky Febriansyah; Harry Ardian; Syahrul Syahrul; Ferry Cahyadi; Fahri Finanda Rizki
Jurnal Ilmiah Teknik Informatika dan Komunikasi Vol. 6 No. 1 (2026): Maret : Jurnal Ilmiah Teknik Informatika dan Komunikasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juitik.v6i1.2072

Abstract

The rapid development of information technology has increased the utilization of digital images in various fields, creating a need for classification methods that are accurate and efficient. One method that can be applied to classify numerical data obtained from image feature extraction is Learning Vector Quantization (LVQ). This study aims to implement the LVQ method for digital image classification based on numerical features and to evaluate its performance in terms of accuracy. The data used in this study consist of grayscale digital images that have undergone a feature extraction process and are represented as numerical vectors. The dataset is divided into two classes, namely Class A and Class B. The research stages include data collection, grayscale conversion, feature extraction, LVQ training, and classification testing. The classification results are evaluated using a confusion matrix and accuracy measurement. The experimental results show that the LVQ method successfully classified all test data correctly, achieving an accuracy rate of 100%. These results indicate that Learning Vector Quantization is an effective method with good performance for classifying digital image data based on numerical features.
Co-Authors Adhistya Aulia DH Delyanti Putri Sitorus Fahri Finanda Rizki Fikri Vahriza Harry Ardian Ilham Habinsaran Irwansyah, Bambang Khairul Saleh Muhammad Yasin Rezki Abdillah Rizky Febriansyah Seprina Aulia Putri Syahrul Syahrul Syahrul