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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) SOROT: Jurnal Pengabdian Kepada Masyarakat Smatika Jurnal : STIKI Informatika Jurnal
Fadhil Rozi Hendrawan
Telkom University
Civil Engineering, Building, Construction & Architecture Computer Science & IT Engineering Mechanical Engineering Other

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Cybersecurity Awareness and Community Response to Phishing Threats: An Indonesian Social Behavior Analysis Fadhil Rozi Hendrawan; Arif Rahman Hakim; Dewi Marini Umi Atmaja; Zaidan Mufaddhal
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 02 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i02.2332

Abstract

This research discusses the increased levels of connectivity and digital engagement experienced by the people of Indonesia due to the development of digital technology as well as the risks associated with the growing prevalence of phishing cyber crimes in the country despite having the third-highest population of internet users globally. Although the level of digital literacy varies across different regions in the country, younger users in Indonesia appear to be the most vulnerable to phishing attacks. In view of the above, this paper seeks to identify and explore the behavioral dimensions that determine vulnerability to phishing amongst young internet users in Indonesia through a qualitative exploration of behavioral exposure towards such cyber crime. The research employs a quantitative cross-sectional survey method using structured questionnaires provided to 53 participants in their teens who were frequently involved in using digital platforms for purposes such as engaging on social media, making purchases from e-commerce sites, and executing payments via digital platforms, all chosen using a purposive sample method. Validity and reliability were measured using the Principal Component Analysis, the Kaiser-Meyer-Olkin validity test, Bartlett's Test of Sphericity and Cronbach's Alpha test respectively. Validity tests produced a KMO measure of 0.587 with a statistically significant Bartlett test result (χ²=71.940, df=10, p<0.001). Using PCA, two factors contributing 70.997% cumulative variance were identified with Eigenvalue values of 2.299(45.98%) and 1.251(25.02%). The first factor measures active reception of links via digital platforms and the second measures exposure to bypassing attempts via OTP channels. The four-item scale had a Cronbach Alpha of 0.743 implying acceptable internal consistency.
Pelatihan Kemampuan Non-Teknis Mengetahui Potensi Diri dan Manajemen Waktu Menggunakan Aplikasi Trello Deki Satria; Fadhil Rozi Hendrawan; Adrian Faturohman; Hesmi Aria Yanti; Desi Nurnaningsih; Fayiz Apriwansyah Nugraha; Quinnsha Thara Diva; Nada Devi Meilani; Aliya Fayyaza Raisandrina
SOROT : Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 1 (2026): Januari
Publisher : Fakultas Teknik dan Ilmu Komputer (FASTIKOM) UNSIQ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32699/bafq2950

Abstract

  Vocational High School is one kind of high school in Indonesia. The alumni of this school are intended as a ready-to-work workforce. Therefore, the curriculum of said school mainly focused on hard skills. Unfortunately, the job market nowadays also requires the applicant to have the ability in soft skills, such as time and task management. Therefore, in these public service programs, the soft skills have become the main priority. In this public service program, two themes were presented to the audience, the first is about how student can know their potential, and the second theme is about time management using Trello. These two themes are presented using discussion and lecture methodology. Using discussion as the methodology, the audience contribution can be achieved. From the feedback questionnaire given to the audience, the programs are considered a success since the average results are more than four on a five-point Likert scale for all ten questions.   Abstrak Sekolah menengah kejuruan merupakan salah satu bentuk sekolah menengah yang ada di Indonesia. Perbedaan utama jenis sekolah ini dan sekolah menengah lainnya adalah pada lulusan. Lulusan dari sekolah menengah kejuruan diharapkan dapat menjadi tenaga siap kerja setelah lulus dari pendidikan. Oleh karena itu dalam kurikulumnya sering kali lebih berfokus pada kemampuan teknis dibandingkan dengan kemampuan non-teknis. Sayangnya, banyak sekali pemberi kerja yang juga mengharapkan tenaga kerja ini memiliki kemampuan non-teknis seperti manajemen waktu. Oleh karena itu dalam kegiatan pengabdian masyarakat ini dilaksanakan kegiatan pelatihan terkait dengan manajemen waktu dan mengetahui potensi diri. Kegiatan pengabdian masyarakat ini dilakukan dalam bentuk diskusi dan ceramah. Penggunaan metode diskusi dapat meningkatkan antusiasme dari peserta. Kegiatan ini dianggap sukses dilaksanakan berdasarkan hasil evaluasi yang dilaksanakan. Dimana dari sepuluh pertanyaan yang diberikan, semua pertanyaan mendapatkan nilai diatas 4 dari 5 skala Likert.
Pelatihan Computational Thinking Berbasis Media Interaktif Untuk Meningkatkan Skill STEM Siswa SMA Islam Darul Hasan Aries Saifudin; Zuki Pristiantoro; Yulianti; Fadhil Rozi Hendrawan; M. Aziz Kurniawano; Az-Zahra Putri Amelia; Channy; Dhea Febrianti Surdeva
SOROT : Jurnal Pengabdian Kepada Masyarakat Vol. 5 No. 2 (2026): Juli
Publisher : Fakultas Teknik dan Ilmu Komputer (FASTIKOM) UNSIQ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32699/enj4zk05

Abstract

Perkembangan era digital yang pesat menuntut generasi muda untuk memiliki kemampuan berpikir komputasional (computational thinking) sebagai fondasi literasi abad ke-21. Namun, pembelajaran berbasis STEM di tingkat sekolah menengah atas masih seringkali bersifat konvensional dan belum mampu mendorong pemikiran algoritmik siswa secara optimal. Pengabdian masyarakat ini bertujuan untuk meningkatkan skill STEM siswa SMA Islam Darul Hasan melalui pelatihan computational thinking berbasis media interaktif. Metode pelaksanaan mencakup pelatihan terstruktur menggunakan media interaktif berbasis visual dan gamifikasi, workshop pemecahan masalah berbasis algoritma, serta pendampingan langsung dalam penerapan konsep STEM. Tahapan pelaksanaan diawali dengan asesmen awal, dilanjutkan sesi pelatihan intensif yang mengintegrasikan empat pilar computational thinking  dekomposisi, pengenalan pola, abstraksi, dan perancangan algoritma ke dalam konteks pembelajaran STEM. Hasil evaluasi dari 22 responden menunjukkan 88,18% peserta memberikan penilaian Setuju dan Sangat Setuju terhadap efektivitas pelatihan. Aspek pelayanan panitia memperoleh apresiasi tertinggi (95,5%), diikuti harapan keberlanjutan program (90,9%). Pelatihan ini berhasil meningkatkan kemampuan berpikir logis, analitis, dan sistematis siswa dalam menghadapi persoalan berbasis STEM melalui pendekatan media interaktif yang inovatif.
Early detection of vascular streak dieback (VSD) disease in cocoa plants using deep learning Dewi Marini Umi Atmaja; Arif Rahman Hakim; Fadhil Rozi Hendrawan; Komang Diah Devi Pramesty; Naufal Fadhilah Fitrah; Faiz Rochmatullah Widhaputra
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 15, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v15i3.pp1087-1096

Abstract

Vascular streak dieback (VSD), caused by Ceratobasidium theobromae, poses a significant threat to cocoa (Theobroma cacao) production, leading to substantial yield losses and plant mortality. Early detection is critical to mitigate disease spread and reduce economic impact. While convolutional neural network (CNN) architectures like VGG-16 and ResNet-50 excel in leaf disease detection, no prior studies address stem-based VSD symptomatology where the disease originates in vascular tissues. This study presents the first CNN specifically developed for cocoa stem VSD detection, achieving 99.16% test accuracy with a lightweight architecture that outperforms VGG16/ResNet50 in both accuracy and mobile inference speed. A novel dataset of 215 cocoa stem images was curated and augmented for robustness. Additional evaluation metrics, including precision, recall, specificity, and F1-score, further confirm the reliability of the model. The model was successfully converted into TensorFlow Lite (TFLite) format, enabling deployment on mobile devices for real-time disease detection. This study highlights the potential of integrating deep learning into mobile and drone-based agricultural systems to support precision farming and early intervention strategies.
Co-Authors Adrian Faturohman Aliya Fayyaza Raisandrina Aries Saifudin Arif Rahman Hakim Az-Zahra Putri Amelia Channy Deki Satria Dewi Marini Umi Atmaja Dhea Febrianti Surdeva Faiz Rochmatullah Widhaputra Fayiz Apriwansyah Nugraha Hesmi Aria Yanti Komang Diah Devi Pramesty M. Aziz Kurniawano Nada Devi Meilani Naufal Fadhilah Fitrah nurnaningsih, Desi Quinnsha Thara Diva Yulianti Zaidan Mufaddhal Zuki Pristiantoro