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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) TEKMAPRO Journal of Industrial Engineering and Management CESS (Journal of Computer Engineering, System and Science) Briliant: Jurnal Riset dan Konseptual JOIV : International Journal on Informatics Visualization JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Kaizen : Management Systems and Industrial Engineering Journal IJID (International Journal on Informatics for Development) Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Jurnal Sistem Komputer dan Informatika (JSON) Journal of Advanced in Information and Industrial Technology (JAIIT) Journal of Industrial Engineering and Operation Management (JIEOM) Jurnal Pengabdian Kepada Masyarakat Reputasi: Jurnal Rekayasa Perangkat Lunak Go-Integratif : Jurnal Teknik Sistem dan Industri Prosiding Konferensi Nasional PKM-CSR Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence Jurnal Manajemen NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Scientific Journal of Informatics
Fauzi, Muhammad Dzulfikar
Institut Teknologi Telkom
Arts Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Nursing Public Health Social Sciences Veterinary Other

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Kombinasi Timestamp Nonce dan Nilai Salt pada Autentikasi Single Sign-On Maulana, Rizky Fenaldo; Wicaksono, Ardian Yusuf; Pertiwi, Kharisma Monika Dian; Fauzi, Muhammad Dzulfikar
BRILIANT: Jurnal Riset dan Konseptual Vol 8 No 4 (2023): Volume 8 Nomor 4, November 2023
Publisher : Universitas Nahdlatul Ulama Blitar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/briliant.v8i4.1389

Abstract

Single Sign-On atau SSO merupakan metode autentikasi tunggal dimana pengguna cukup melakukan autentikasi sekali untuk mengakses beberapa sistem atau aplikasi yang terdaftar. Proses autentikasi yang digunakan pada SSO menggunakan metode autentikasi klasik. Penyerang dapat mencuri data pengguna pada proses komunikasi autentikasi antara pengguna dan server, serangan ini disebut dengan Man In The Middle Attack (MITM). Nonce adalah tindakan untuk melindungi informasi pribadi dan rahasia serta nilai unik yang tidak akan diulang. Pada makalah ini mengusulkan metode autentikasi pada SSO dengan kombinasi algoritma timestamp nonce dan nilai salt. Kombinasi dari kedua algoritma tersebut akan menghasilkan sebuah nilai acak yang bersifat unik. Nilai unik yang dihasilkan tersebut akan digunakan untuk mengenkripsi nama pengguna dan kata sandi pada tahap autentikasi. Sehingga diharapkan dengan metode tersebut dapat mengamankan data pengguna dari pencurian data dan serangan MITM. Penerapan kombinasi algoritma Timestamp Nonce dan nilai salt dapat dijadikan salah satu alternatif pengamanan autentikasi pada sistem SSO. Selain itu, peneliti juga melakukan uji coba serangan MITM dengan melakukan pembacaan setiap paket data yang bertujuan mendapatkan nama pengguna dan kata sandi. Hasilnya adalah variabel nama pengguna dan kata sandi bersifat unik dan tidak bisa di dekripsi.
Simulasi Pengiriman Air Mineral Galon dengan Multi Depot Menggunakan Hill Climbing dan Algoritma A* Fauzi, Muhammad Dzulfikar; Hajar, Granita; Nur Rachmaniar, Desita; Hamim Zajuli al Faroby, Mohammad
Jurnal Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence) Vol 5 No 2 (2025): Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence)
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakaai.v5i2.1170

Abstract

Air mineral sangat penting bagi kesehatan manusia karena berperan dalam hidrasi tubuh, menjaga keseimbangan cairan, dan mendukung fungsi organ serta sistem tubuh. Untuk memenuhi kebutuhan sehari-hari, distribusi dari depo air ke pelanggan harus mempertimbangkan rute tercepat agar biaya pengiriman efisien. Mencari rute terpendek dengan alokasi depo terbaik dengan tetap mempertimbangkan keterbatasan kapasitas masing-masing depo dan kendaraan merupakan tujuan dari penelitian ini. Algoritma Hill Climbing merupakan metode yang efektif untuk menentukan rute terdekat antar titik pengiriman. Selain itu, algoritma A* dapat digunakan untuk mencari rute optimal dengan menggunakan informasi tambahan (heuristik) yang mengarahkan pencarian ke jalur yang paling efisien. Berdasarkan hasil penelitian, 450,41 merupakan rute terjauh dengan menggunakan moda transportasi penjemputan dengan satu depo. Sedangkan untuk moda transportasi penjemputan dengan dua depo, jalur terpendek adalah 257,62; sedangkan untuk menggunakan sepeda motor atau kereta api, jalur terpendek adalah 271,75.
A Combination of Transfer Learning and Support Vector Machine for Robust Classification on Small Weed and Potato Datasets Adhinata, Faisal Dharma; Ramadhan, Nur Ghaniaviyanto; Fauzi, Muhammad Dzulfikar; Tanjung, Nia Annisa Ferani
JOIV : International Journal on Informatics Visualization Vol 7, No 2 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.2.1164

Abstract

Agriculture is the primary sector in Indonesia for meeting people's daily food demands. One of the agricultural commodities that replace rice is potatoes. Potato growth needs to be protected from weeds that compete for nutrients. Spraying using pesticides can cause environmental pollution, affecting cultivated plants. Currently, agricultural technology is being developed using an Artificial Intelligence (AI) approach to classifying crops. The classification process using AI depends on the number of datasets obtained. The number of datasets obtained in this research is not too large, so it requires a particular approach regarding the AI method used. This research aims to use a combination of feature extraction methods with local and deep feature approaches with supervised machine learning to classify of small datasets. The local feature method used in this research is Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG), while the deep feature method used is MobileNet and MobileNetV2. The famous Support Vector Machine (SVM) uses the classification method to separate two data classes. The experimental results showed that the local feature HOG method was the fastest in the training process. However, the most accurate result was using the MobileNetV2 deep feature method with an accuracy of 98%. Deep features produced the best accuracy because the feature extraction process went through many neural network layers. This research can provide insight on how to analyze a small number of datasets by combining several strategies
ADAPTIVE AL-QUR’AN MEMORIZATION RECOMMENDATION SYSTEM BASED ON FUZZY LOGIC COGNITIVE MEMORY AND PROFILE MATCHING Dhiya'ulhaq, Afifah Fikriyah; Fauzi, Muhammad Dzulfikar; Safitri, Pima Hani
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 3 (2026): JITK Issue February 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i3.8048

Abstract

Memorizing mutasyabihat verses in the Qur’an is particularly challenging due to similarities in structure, linguistic patterns, and semantic density that place a heavy load on short-term memory. Conventional memorization approaches do not account for individual cognitive differences when dealing with verse complexity. This study proposes an adaptive recommender system based on cognitive modeling to align verse group selection with the user’s memory profile.The system models memory capacity as a multidimensional profile using fuzzy inference derived from three quantitative indicators: continuous memory score, total correct recall, and average response time. This profile is matched with verse group feature vectors through a profile matching approach and a weighted Euclidean distance similarity measure within a Multi-Attribute Decision Making (MADM) framework. Four verse characteristics are considered: thematic (35%), semantic (25%), linguistic (25%), and pattern (15%).An adaptive calibration phase combines 20% of the initial cognitive profile with 80% of actual memorization performance, reflecting the dominance of behavioral evidence over initial assessment. System evaluation employs the Top-N Accuracy method commonly used in recommender systems.Testing with 29 participants resulted in a Top-3 success rate of 66% and an overall Top-N accuracy of 62.07%. These results indicate that cognitive profile–based multidimensional similarity can adaptively match verse complexity to individual memory capacity. This study demonstrates that fuzzy cognitive modeling and profile matching can be effectively implemented in adaptive personalized learning systems to optimize memorization of mutasyabihat verses
Co-Authors Abdul Kholik Agfianto Eko Putra Agung Fatwanto Agung Fatwanto Ahmad Wali Satria Bahari Johan Aprilliyanto, Tofik Arda Erico Yuda Arda Erico Yuda Ardian Yusuf Wicaksono Arifin, Hendra Dea Arliyanti Nurdin Arliyanti Nurdin , S.T., M.T Asyhab, Naufal Aulia Faqih Rifa’i Bambang Sugiantoro Bunga Pasha Maulidina Chasandra Puspitasari Desita Nur Rachmaniar Dhiya'ulhaq, Afifah Fikriyah Faisal Dharma Adhinata Granita Hajar Haq, Azizi Khoirul Hendra Dea Arifin Heni Hapsari Heri Setiawan Ida Ayu Putu Sri Widnyani Islami, Mega Cattleya P.A Kasliono Kasliono Khurin 'ien Mukhoyyaroh Laksono Kurnianggoro Maria Ulfah Siregar Matteo Ibastian Maulana, Rizky Fenaldo Mohammad Hamim Zajuli Al Faroby Montolalu, Billy Muhammad Akid Musyafa Muhammad Alfian Jauhari Muhammad Mustakim, Muhammad Muhammad Taufiq Nuruzzaman Musyafa, Muhammad Akid Nia Annisa Ferani Tanjung Nicko Nur Rakhmaddian, Nicko Nur Nisa Isrofi Nur Ghaniaviyanto Ramadhan Nur Rachmaniar, Desita Oktavianita, Annisa Dwi Pertiwi, Kharisma Monika Dian Rachmadi, Andry Rahmaani, Amalia Ratna Rahmawati, Feri Rizky Fenaldo Maulana Rizky Novera Harnaningrum Safitri, Pima Hani Shofwatul ‘Uyun son, Sumarsono Sri Lestari Sunu Pinasthika Fajar Suryana Wijaya T. Rasmana , Susijanto Wahyono Wahyono Wahyu Andy Prastyabudi Wahyu Sri Mulyani Yulianto, Ilham