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All Journal KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer Angkasa: Jurnal Ilmiah Bidang Teknologi JURIKOM (Jurnal Riset Komputer) Jurnal ICT : Information Communication & Technology Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Accounting Information System (AIMS) Jurnal Riset Sistem Informasi dan Teknologi Informasi (JURSISTEKNI) Tematik : Jurnal Teknologi Informasi Komunikasi Journal of Artificial Intelligence and Engineering Applications (JAIEA) AMMA : Jurnal Pengabdian Masyarakat Akuntansi: Jurnal Riset Ilmu Akuntansi Jurnal Informatika: Jurnal Pengembangan IT Jurnal Accounting Information System (AIMS) Jurnal Ilmu Komputer Ruru Smatika Jurnal : STIKI Informatika Jurnal
Saeful Anwar
STMIK IKMI Cirebon
Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mechanical Engineering Nursing Other

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EVALUASI PENGALAMAN PENGGUNA MAHASISWA TERHADAP SISTEM INFORMASI SIASAT: PENDEKATAN DENGAN USER EXPERIENCE QUESTIONNAIRE Saeful Anwar
Jurnal Ilmu Komputer Ruru Vol. 2 No. 1 (2025): Edisi Januari
Publisher : Yayasan Grace Berkat Anugerah

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Abstract

This research aims to analyze student user experience on the Satya Wacana Information System (SIASAT) using the User Experience Questionnaire (UEQ). UEQ is a measurement method from the aspect of its use and the aspect of the experience, including a compressive impression using a questionnaire scale. The UEQ has 26 questions that must be filled out by respondents, where the questions cover 6 aspects, including attractiveness, efficiency, perspicuity, dependability, stimulation, and novelty. The UEQ questionnaire in this study used data from 54 active SWCU student respondents who understood the use of the Satya Wacana Academic Information System (SIASAT) well. The final results of the tests carried out obtained data for the scale of attractiveness, efficiency, dependability, and stimulation to get a normal evaluation category. Meanwhile, the novelty scale gets a negative evaluation category and the perspicuity scale gets a positive evaluation category. Then for the results of the benchmark evaluation, the majority got the Bad category which includes a scale of attractiveness, efficiency, dependability, stimulation, and novelty. Only one scale that gets the Above Average category (Good Enough) is perspicuity.
Edukasi Keamanan Digital dan Etika Bermedia Sosial bagi Remaja Sekolah Saeful Anwar; Tati Supra; Indah Ratna Ningsih; Kevin Salsabil Arlandy
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 04 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

In today's digital age, social media use has become an integral part of teenagers' lives. However, increased access to information and online communication also brings new challenges, especially in terms of digital safety and media etiquette. School adolescents, as active users of social media, often lack an adequate understanding of the risks that can arise from their digital activities. This study aims to provide a comprehensive understanding of the importance of digital safety and the application of ethics in social media among teenagers. The method used is a literature study combined with an educational approach based on learning and training modules. The results of the study show that most teenagers are not aware of the importance of personal data protection, password security, and the risk of spreading false information or hoaxes. In addition, the lack of ethics in communicating on social media can lead to social conflicts and privacy violations. Therefore, a systematic educational approach is needed to equip teenagers with the knowledge and skills to maintain digital security and act ethically in the digital space. This educational effort needs to involve the role of teachers, parents, and school policies that support digital literacy as a whole.
Penerapan Sistem Informasi Kearsipan Digital untuk Pemerintah Desa Ryan Hamonangan; Saeful anwar; Ibnu Hajar; Ike Suryani Dewi
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 04 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

In the digital era, an archival information system is an important requirement in supporting effective and efficient administrative governance in the village government. Many villages in Indonesia still use a manual archive recording system that is vulnerable to data loss, physical damage to documents, and the slow process of retrieving information. This service program aims to implement a digital-based archival information system in the village government to improve administrative performance and public services. The methods used include partner needs analysis, system design, software implementation, user training, and evaluation of results. The developed system enables document digitization, archive grouping, and fast data search, and is equipped with security features to maintain information integrity. The results of the implementation showed that village officials were able to understand and operate the system well after the training. The information system significantly speeds up the document search process and reduces the risk of data loss. In addition, the implementation of the system also has an impact on improving transparency, accountability and professionalism in services to the community. In conclusion, the implementation of a digital-based archival information system is an innovative and applicable solution to address the challenges of modern village archive management.
Pengembangan Sistem Informasi Learning Analytics untuk Monitoring dan Evaluasi Kompetensi Digital Pelaku UMKM pada Platform SkillUP Denni Pratama; Dian Ade Kurnia; Saeful Anwar
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.v13i1.2994

Abstract

Transformasi digital telah mendorong kebutuhan peningkatan kompetensi digital bagi pelaku Usaha Mikro, Kecil, dan Menengah (UMKM) di Indonesia. Platform microlearning SkillUP telah berhasil dikembangkan dan diterima pengguna berdasarkan Technology Acceptance Model (TAM), namun masih belum dilengkapi mekanisme monitoring dan evaluasi kompetensi digital secara komprehensif. Penelitian ini bertujuan mengembangkan Sistem Informasi Learning Analytics (SILA) untuk monitoring dan evaluasi kompetensi digital pelaku UMKM pada platform SkillUP menggunakan metode Design Science Research (DSR). Sistem yang dikembangkan mengintegrasikan data aktivitas pembelajaran ke dalam tiga lapisan pengumpulan data, mesin analitik, dan dashboard. Novelty penelitian mencakup Digital Competency Monitoring Framework dan Digital Competency Progress Index (DCPI) yang dihitung dari Learning Engagement Score (LES), Learning Completion Rate (LCR), Quiz Achievement Score (QAS), dan Competency Achievement Score (CAS). Evaluasi sistem menggunakan standar ISO/IEC 25010 dengan fokus pada Functional Suitability, Usability, dan Performance Efficiency. Hasil evaluasi menunjukkan nilai Functional Suitability sebesar 1,00 (sangat baik), Usability sebesar 87,5 (excellent berdasarkan SUS), dan rata-rata response time 1,87 detik. Sistem ini berkontribusi dalam menyediakan data berbasis bukti untuk pengambilan keputusan strategis terkait pengembangan kompetensi digital UMKM di Indonesia.
The Optimization of Learning Media Through Augmented Reality to Improve Student Learning Comprehension Saeful Anwar; Tati Suprapti; Yoga Nugraha; Arif Rinaldi Dikananda
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 18, No 2 (2026): Mei
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/angkasa.v18i2.3869

Abstract

This study presents the development and evaluation of an Augmented Reality (AR) based learning media optimized to enhance students’ comprehension of camera architecture concepts. The AR system was developed using Unity 3D integrated with Vuforia SDK, implementing a marker-based AR approach to ensure stability and compatibility with limited mobile device specifications. The system architecture consists of a mobile AR client, image-marker recognition module, 3D visualization engine, and learning interaction layer designed based on multimedia learning principles and cognitive load theory. A five-stage development framework was employed: planning, material collection, assembly, implementation, and evaluation. The AR media was applied in an undergraduate informatics course involving 30 students, using a one-group pretest–posttest design. Learning outcomes were analyzed using paired t-tests, Wilcoxon tests, normalized gain, and effect size measurements. Results show significant improvements across all cognitive dimensions (p < 0.001), with very large effect sizes (dz = 3.13) and a moderate normalized gain (g = 0.42). The findings indicate that AR provides strong practical impact on higher-order cognitive skills, particularly application and analysis, while highlighting limitations related to measurement instrument validity, absence of a control group, and limited sample generalizability, which will be addressed in future research through experimental comparison and extended system performance testing.
Perbandingan Kinerja VGG 16 dan ResNet untuk Pengenalan Ekspresi Wajah Mahasiswa Berbasis CNN pada Smart Learning Environment Dian Ade Kurnia; Fatihanursari Dikananda; Saeful Anwar; Dadang Sudrajat; Abdul Aziz
TEMATIK Vol. 12 No. 2 (2025): Tematik : Jurnal Teknologi Informasi Komunikasi (e-Journal) - Desember 2025
Publisher : LPPM POLITEKNIK LP3I BANDUNG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38204/tematik.v12i2.2590

Abstract

Perkembangan teknologi kecerdasan buatan (AI) dan visi komputer telah membuka peluang besar dalam penerapan pengenalan ekspresi wajah pada berbagai bidang. Dalam konteks pendidikan tinggi, keterlibatan mahasiswa selama proses belajar menjadi faktor penting yang masih sulit diukur secara objektif menggunakan metode konvensional. Namun pada kenyataannya, penelitian sebelumnya masih jarang menguji performa arsitektur CNN populer secara langsung di lingkungan pembelajaran nyata dengan kondisi pencahayaan dan pose yang beragam. Penelitian ini berkontribusi dengan membandingkan kinerja dua arsitektur deep learning, yaitu VGG-16 dan ResNet, dalam klasifikasi ekspresi wajah mahasiswa pada Smart Learning Environment. Penelitian dilakukan dengan pendekatan eksperimen kuantitatif melalui lima tahapan, yaitu pengumpulan data wajah mahasiswa di kelas, preprocessing berupa cropping, resizing, dan augmentasi, pengembangan model CNN, pelatihan menggunakan data split 80% training dan 20% validasi, serta evaluasi dengan metrik akurasi, presisi, recall, dan F1-score. Hasil eksperimen menunjukkan bahwa VGG-16 unggul dalam mengenali ekspresi suka dengan nilai F1-score tertinggi sebesar 85%, sedangkan ResNet relatif lebih baik pada ekspresi bosan dengan F1-score 73,2%. Sementara itu, keduanya sama-sama lemah dalam mengenali ekspresi tidak suka. Temuan ini mengimplikasikan bahwa VGG-16 lebih sesuai digunakan untuk mendukung analisis keterlibatan mahasiswa secara real-time dalam Smart Learning Environment berbasis AI.
Application of Decision Tree Algorithms to Classify the Sales Results of Kangen Kripik Sme Products Adila G Khiqmatiar Muchsin; Nining Rahaningsih; Irfan Ali; Dadang Sudrajat; Saeful Anwar
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1854

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in strengthening the national economy; however, many still face challenges in managing and analyzing sales data effectively. This study aims to classify product sales results at UMKM Kangen Kripik Mang Acep by applying the Decision Tree algorithm as a data classification method based on machine learning. A quantitative experimental approach was employed to evaluate the model’s performance using one-year sales data, including attributes such as product variants, sales volume, sales channels, and marketing regions. Data processing was conducted using RapidMiner software following the Knowledge Discovery in Databases (KDD) framework, which includes data selection, preprocessing, transformation, data mining, and model evaluation. The results indicate that the Decision Tree algorithm successfully classified sales regions (Garut, Bandung, and Sumedang) with an accuracy rate of 96.48%, identifying “Units Sold (pcs)” as the most influential attribute for distinguishing marketing areas. These findings demonstrate that the Decision Tree method is not only effective in improving data analysis efficiency but also provides valuable strategic insights for data-driven business decision-making in MSMEs
Penguatan Kapasitas Pengelolaan Media Sosial Untuk Promosi Produk UMKM Kota Cirebon Saeful Anwar; Fathurrohman; Aulia Adisty Hervianne; Indah Nur Hasanah
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 economic growth, employment generation, and community welfare. However, the use of social media as a promotional tool among MSMEs in Cirebon City remains limited due to insufficient digital literacy, low-quality promotional content, and the absence of structured social media management strategies. This community service program aimed to strengthen the capacity of MSME owners in managing social media for product promotion through practice-based training and mentoring. The implementation consisted of needs assessment, training, hands-on practice, mentoring, monitoring, and evaluation. Training materials included digital branding, promotional content creation, product photography, caption writing, content calendar development, and the optimization of Instagram, Facebook, TikTok, and WhatsApp Business. The results demonstrated significant improvements in participants' ability to manage business social media accounts, produce more engaging promotional content, organize structured publishing strategies, and enhance customer engagement. The program also produced practical outputs, including professionally managed social media accounts, content calendars, and a simple social media management guide. These findings indicate that combining training with continuous mentoring is effective in improving digital competencies and strengthening the competitiveness of MSMEs.
Pelatihan Pengolahan Dan Transformasi Data Otomatis Berbasis N8N Pada SMK Kabupaten Cirebon Saeful Anwar; Dadang Sudrajat; Muhamad Ilham Nur Faqih; Firman Yudatama
AMMA : Jurnal Pengabdian Masyarakat Vol. 5 No. 5 : Juni (2026): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

This Community Service Activity raised the theme "n8n-Based Automatic Data Processing and Transformation Training at Vocational High Schools in Cirebon Regency." The activity was held on Saturday, April 4, 2026, targeting participants from the Cirebon Regency Vocational High School environment. This program was motivated by the need for vocational schools to improve data management capabilities, utilize digital technology, and automate work processes. School activities generate a lot of data, such as student data, attendance, activity registration, grades, evaluation questionnaires, and administrative reports. This data is often managed manually, spread across various media, and requires a long time to be summarized. The solution provided was training in automatic data processing and transformation using n8n. n8n was chosen because it has a visual interface, supports the low-code concept, can connect various applications, and allows users to build automated workflows gradually. The implementation method uses a participatory, educational, practical, problem-based, and sustainable approach. The activity began with partner coordination, module development, technical preparation, workshop implementation, guided practice, case studies, evaluation, and follow-up recommendations. The results of the activity showed that participants gained an understanding of data concepts, data transformation, workflow automation, triggers, nodes, outputs, and workflow evaluation. Participants were also able to create simple workflows based on school case studies, such as activity registration recaps, attendance processing, automatic notifications, and evaluation recaps. The participant satisfaction evaluation showed an average score of 4.48, categorized as very satisfied. The training benefits and practical methods indicators received high scores, thus the training was deemed relevant to the school's needs. Overall, this activity successfully improved digital literacy, basic data automation skills, and participants' awareness of the importance of technology-based work efficiency. This program is expected to serve as a foundation for the development of data automation in vocational schools in Cirebon Regency and support the sustainable digital transformation of vocational education.
Optimization of Social Assistance Recipient Determination using Gradient Boosting Algorithm Windi Herlita Vidila; Rudi Kurniawan; Saeful Anwar
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 2 (2025): February 2025
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i2.773

Abstract

This research aims to classify social assistance recipients to ensure the accuracy of aid distribution by utilizing the Gradient Boosting algorithm on RapidMiner. The data used is data on residents who are categorized as receiving and not receiving social assistance in Cicadas village with a total dataset consisting of 670 entries with 18 attributes that will be divided equally between eligible and ineligible recipients. This research uses KDD (Knowledge Discover in Database) analysis which includes the stages of data selection, pre-processing, transformation, modeling, and interpretation of results. This research uses a quantitative approach, focusing on the distribution of datasets in a ratio of 70:30 with a stratified sampling technique for training and testing purposes. The experimental results show that the selected method is effective in classifying recipients by obtaining an accuracy of 91.67%, this accuracy result can be relied upon to support decision-making in social assistance distribution. The findings underscore the potential of machine learning in optimizing social welfare initiatives by improving target accuracy and ensuring aid reaches the rightful recipients.
Co-Authors Abdul Aziz Abdul Aziz Abdul Robi Padri Ade Irma Purnamasari Adila G Khiqmatiar Muchsin Afif Maulana Sidik Ahmad Faqih Ahmad Faqih Ali Ali Arif Rinaldi Dikananda Aulia Adisty Hervianne Basysyar, Fadhil Muhammad Cep Lukman Rohmat Chaidir Ali Dadang Sudrajat Dadang Sudrajat Denni Pratama Dian Ade Kurnia Dian Ade Kurnia Dias Bayu Saputra Dilita Pramasmawari Lita Dimas Aji Dita Rizki Amalia Edi Tohidi Fathurrohman Fatihanursari Dikananda Firman Yudatama Gifthera Dwilestari Gifthera Dwilestari Heliyanti Susana Ibnu Alfian Ibnu Hajar Iin Ike Suryani Dewi Indah Nur Hasanah Indah Ratna Ningsih Irfan Ali Kanda Muhamad Ishak Kevin Salsabil Arlandy Khamim Surya Hadi Kusuma Al Atros Kokom Komariyah Martanto Martanto . Muhamad Ilham Nur Faqih Nafhan Khairuddin Fathin Nana Suarna Nana Suarna Narasati, Riri Narasati Nining Rahaningsih Nisa Dieanwati Nuris Novia Wulandari Odi Nurdiawan Raditya Danar Dana Rahaditya Dasuki Rahmat Mauludin Revita Lestari Faujiah Risa Komala Sari Rudi Kurniawan Ruli Herdiana Ryan Hamonangan Saeful Amri Sandy Eka Permana Siti Rini Sari sri wahyuni nengsih Tati Supra Tati Suprapti Topan Hadi Tuti Hartati Windi Herlita Vidila Yoga Nugraha Yudhistira Arie Wijaya