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All Journal Jurnal Riset Informatika INTI Nusa Mandiri
Riyadi , Andri Agung
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Computer Science & IT

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RANCANG BANGUN SISTEM INFORMASI MANAJEMEN DISTRIBUSI QURBAN Ruhyana, Nanang; Sari, Ani Oktarini; Mardiana, Tati; Bayhaqy, Achmad; Riyadi , Andri Agung; Setiaji, Setiaji
INTI Nusa Mandiri Vol. 20 No. 1 (2025): INTI Periode Agustus 2025
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v20i1.6945

Abstract

One of the most important aspects of Eid al-Adha celebrations is the distribution of sacrificial meat. However, the process of distributing sacrificial meat often faces various challenges, such as inaccurate data collection, difficulty in tracking the amount of sacrificial meat, and a lack of transparency and efficiency. The objective of this study is to design and develop an application that can enhance efficiency, accuracy, and accountability in the distribution of sacrificial meat through the systematic use of information technology. This study employs the waterfall method, which involves several sequential stages: needs analysis, system design, implementation, and testing. This system was developed to support the performance of the sacrificial committee in managing data on sacrificial animals, information on recipients, the distribution process of meat, and the documentation of all activities in a digital and real-time manner. In the user interface (front end), the Next.js/React.js framework is combined with Tailwind CSS to produce a responsive and user-friendly interface. Meanwhile, the server side (back end) was developed using Laravel as a reliable and efficient PHP framework, and MySQL as a database to store all information related to distribution. The result of this research is a web-based application prototype featuring animal sacrifice data collection, beneficiary data recording, and distribution report generation. It is hoped that this application will facilitate more organized and effective distribution of sacrificial meat
COMPARATIVE ANALYSIS OF THE K-NEAREST NEIGHBOR ALGORITHM ON VARIOUS INTRUSION DETECTION DATASETS Riyadi , Andri Agung; Amsury , Fachri; Pattiasina , Tiska; Jupriyanto, Jupriyanto
Jurnal Riset Informatika Vol. 4 No. 1 (2021): December 2021
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v4i1.147

Abstract

Because we have flaws in developing security rules, inadequate computer system settings, or software defects, security in computer networks can be vulnerable. Intrusion detection is a computer network security method that detects, prevents, and blocks unauthorized access to confidential information. The IDS method is intended to defend the system and minimize the harm caused by any attack on a computer network that violates computer security policies such as availability, confidentiality, and integrity. Data mining techniques were utilized to extract relevant information from IDS databases. The following are some of the most widely utilized IDS datasets NSL-KDD, 10% KDD, Full KDD, Corrected KDD99, UNSW-NB15, ADFA Windows, Caida, dan UNM have been used to get the accuracy rate using the k-Nearest Neighbors algorithm (k-NN). The latest IDS dataset provided by the Canadian Institute of Cybersecurity contains most of the latest attack scenarios named the CICIDS2017 dataset. Preliminary experiment shows that the approach using the k-NN method on the CICIDS2017 dataset successfully produces the highest average value of intrusion detection accuracy than other IDS datasets.
Co-Authors Amsury , Fachri ANI OKTARINI SARI, ANI OKTARINI Bayhaqy, Achmad Jupriyanto . Pattiasina , Tiska ruhyana, nanang Setiaji Setiaji, Setiaji Tati Mardiana, Tati