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All Journal AMMA : Jurnal Pengabdian Masyarakat JRIIN :Jurnal Riset Informatika dan Inovasi
Abdullah Rendra Zuriansyah
Universitas Pamulang
Humanities Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing

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Peningkatan Literasi Teknologi Bagi Generasi Muda : Membangun Pemahaman Dasar - Dasar Machine Learning Rahmawati; Geraldo Sabila Firdaus; Azzani Nurfadia Rizky; Abdullah Rendra Zuriansyah; Elyananda Subroto; Jefi Eliel Tigor Tampubolon; Mia Septiana Wambrauw; Muhammad Aldhito Firlata; Ridwan Firdaus Haryono; Emison Wonda; Satria Andikah Putra
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 11 : Desember (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Increasing technological literacy is a strategic step in preparing the younger generation to face the challenges of the Industrial Revolution 4.0. This community service activity aims to build a basic understanding of machine learning (ML) technology for students of SMKN 5 Tangerang Kota. The implementation method includes basic theory delivery, interactive training, simple practice of building image classification using MIT App Inventor Personal Image Classifier, and group discussions. The results showed a significant increase in the understanding of basic Machine Learning concepts such as classification and regression, as well as the high enthusiasm of the participants in understanding the application of this technology. This programme is expected to be the first step in creating a generation that is able to actively contribute to the development of artificial intelligence-based technology.
Deteksi Dini Website Phising Berbasis Karakteristik URL Menggunakan Algoritma Random Forest sebagai Upaya Penegakan Keamanan Siber Muhammad Faqih Alharits; Hanif Maulana Ar Rasyid; Rifky Firmansyah; Abdullah Rendra Zuriansyah; Ardiansyah Maulana; Firza Aditiya Ardiansah; Rahmawati
Jurnal Riset Informatika dan Inovasi Vol 4 No 4 (2026): JRIIN : Jurnal Riset Informatika dan Inovasi (INPRESS)
Publisher : shofanah Media Berkah

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Phising merupakan salah satu ancaman keamanan siber yang paling merugikan, dengan modus menyamar sebagai website terpercaya untuk mencuri data sensitif pengguna. Penleitian ini mengembangkan sistem deteksi dini phising website berbasis karakteristik URL menggunakan algoritma Random Forest. Dataset yang digunakan terdiri dari 10.000 sampel URL (50% legitimate, 50% phising) dengan 48 fitur berbasis karakteristik URL. Model baseline Random Forest mencapai akurasi 98,55%, presisi 98,60%, recall 98,50%, F1-score 98,55%, dan AUC-ROC 99,09%. Hyperparameter tuning menggunakan RandomizedSearchCV menghasilkan model dengan performa serupa namun sedikit lebih rendah pada recall (98,20%). Analisis feature importance menunjukkan bahwa PctExtHyperlinks (20,69%), PctExtNullSelfRedirectHyperlinksRT (16,77%), dan FrequentDomainNameMismatch (7,78%) merupakan fitur paling informatif. Kajian etika profesi dilakukan terhadap implikasi false positive dan false negative, tanggung jawab profesional pengembang, serta kepatuhan terhadap regulasi Indonesia (UU ITE, UU PDP No. 27 Tahun 2022). Penelitian ini menunjukkan bahwa pendekatan machine learning berbasis Random Forest efektif untuk deteksi phishing dan dapat berkontribusi pada penegakan keamanan siber di Indonesia.
Co-Authors Ardiansyah Maulana Azzani Nurfadia Rizky Elyananda Subroto Emison Wonda Firza Aditiya Ardiansah Geraldo Sabila Firdaus Hanif Maulana Ar Rasyid Jefi Eliel Tigor Tampubolon Mia Septiana Wambrauw Muhammad Aldhito Firlata Muhammad Faqih Alharits Rahmawati Ridwan Firdaus Haryono Rifky Firmansyah Satria Andikah Putra