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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Ilmiah FIFO Applied Information System and Management Holistika : Jurnal Ilmiah PGSD Jurnal Sistem Informasi dan Informatika (SIMIKA) Journal of Applied Engineering and Technological Science (JAETS) Tadarus Tarbawy : Jurnal Kajian Islam dan Pendidikan Journal of Applied Computer Science and Technology (JACOST) Journal of Renewable Energy, Electrical, and Computer Engineering Prosiding Seminar Nasional Pemberdayaan Masyarakat (SENDAMAS)
Nurbojatmiko Nurbojatmiko, Nurbojatmiko
Universitas Islam Negeri Syarif Hidayatullah Jakarta
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice

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Patterns Thematic Tracing of the Hadith of the Prophet Muhammad SAW Using the FP-Growth Algorithm and ECLAT Nurbojatmiko, Nurbojatmiko; Rustamaji, Eri; Wadud, Abdul; Mutholib, Abdul
Applied Information System and Management (AISM) Vol. 7 No. 1 (2024): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v7i1.34492

Abstract

The limited ability to memorize, understand Arabic, and access sources are obstacles to understanding Islamic knowledge, especially hadith. Searching for access to sources to obtain hadiths that are in accordance with the theme and the interrelationships between themes improves the quality of the preachers towards religious understanding. This study investigates how to automate the thematic tracking pattern of Prophet Muhammad's hadith using the FP-Growth (Frequent Pattern-Growth) and ECLAT algorithms. The research was conducted using qualitative and quantitative approaches. The next step involves creating a prototype using the dataset development framework. The result of this study is a prototype of hadith tracing using the FP-Growth algorithm with the prophet's hadith dataset based on the Bulughul Maram book. 
Design and Implementation of a Blockchain-based Shipment Tracking Proof-of-Concept for Academic Application Arsyad, Andi Arniaty; Safitri, Riri; Pradani, Winangsari; Nurbojatmiko, Nurbojatmiko; Abdullah, Abdullah
Prosiding Seminar Nasional Pemberdayaan Masyarakat (SENDAMAS) Vol 5, No 1 (2025): InPress
Publisher : UniversitasAl Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/psn.v5i1.5053

Abstract

The demand for secure, transparent shipment tracking is rising as digital logistics advances. Traditional centralized tracking systems face issues such as data delays and manipulation, which reduce trust and accuracy. This research aims to create a blockchain-based shipment-tracking system that serves as both a prototype and an educational tool for students. The system features a user interface built with Vue.js and utilizes a middleware layer with Node.js and Express.js. A smart contract in Solidity is deployed on a local Ethereum network using the Hardhat framework. This prototype allows students to engage with decentralized application development and explore interactions among front-end components, middleware, and smart contracts. Each transaction is recorded immutably, with an average gas consumption of about 175,000 units and execution times under 2 seconds, while preventing duplicate shipments. This research offers a functional shipment-tracking model that provides transparent data recording and serves as an effective framework for blockchain education, bridging theoretical concepts with practical applications in higher education.Keywords – Academic Application, Blockchain, Shipment Tracking, Smart Contract, Solidity.
Systematic Literature Review: Implementation of Machine Learning for Intrusion Detection Khilda, Amanda Amelia; Rayhan, M. Shaquille; Amaliah, Annisa Rizki; Nurbojatmiko, Nurbojatmiko
Journal of Renewable Energy, Electrical, and Computer Engineering Vol. 5 No. 2 (2025): September 2025
Publisher : Institute for Research and Community Service (LPPM), Universitas Malikussaleh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jreece.v5i2.20300

Abstract

The rapid development of information technology has an impact on the increasing threat to cyber security. One of the main threats is intrusion attacks that are increasingly complex and diverse. To solve this problem, machine learning-based Intrusion Detection System (IDS) is a promising solution due to its ability to detect threats automatically and efficiently. However, the large number of machine learning methods available poses a challenge in determining the best approach for various needs. This research aims to conduct a systematic literature review using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. This literature review identifies and categorises previous studies related to the application of machine learning in IDSs based on the problem addressed, proposed solution, research method, metric parameters, research object, and research results. The data for this research is taken from trusted sources, such as Google Scholar, IEEE, Elsevier, Springer, and MDPI. The results of this review are expected to provide a deeper understanding of the application of machine learning in IDS and provide direction for other researchers to fill the remaining research gaps.
Co-Authors Abdul Mutholib Abdul Wadud, Abdul Abdullah Abdullah Ade Arfani, Mizan Amaliah, Annisa Rizki Anisyah, Rifka Annisa Ramadhanti Arif, Zainal Arsyad, Andi Arniaty Asnadi, Nur Muhammad Eri Rustamaji Herlino Nanang Indah Kusuma Ayu Irahman, Muhammad Shidqa Karimiyah, Muhammad Sharhan Khatami Khilda, Amanda Amelia Mahbubul Wathoni Mayanda, Deara Muhammad Fitra Alfajri Nabil Cahya Wasiqi Nashikha, Ainun Natasya Aurora Yasmin Nur Aeni Hidayah Pradani, Winangsari Putri, Rizka Amalia Rabiatul Nurhasanah Raharja, Muhammad Ridwan Ali Ramadhan, Raihan Lail Rayhan, M. Shaquille Rony, Zahara Tussoleha Safitri, Riri Siti Ummi Masruroh Sulasiyah, Ismi Ana Victor Amrizal Viesah Putra Alegra Wathoni, Mahbubul Winda Wulandari, Winda Yasin Efendi Yuliwanda Anggi Kusumaatuti Yuni Kurnia Purwati Yusri, Azizah Nurfauziah Zahra Ulinnuha Zulfitria Zulfitria, Zulfitria