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All Journal bit-Tech
Desiyanna Lasut
Buddhi Dharma University
Computer Science & IT

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Network Security Analysis with SnortIDS Using ACID (Analysis Console for Intrusion Databases Ruruh Wuryani; Indah Fenriana; Dicky Surya Dwi Putra; Desiyanna Lasut; Susanto Hariyanto
bit-Tech Vol. 5 No. 3 (2023): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v5i3.728

Abstract

The use of Wi-Fi and Ethernet is increasing in today's computer networks due to the advancement of technology. The development of networks today is characterized by the need for low-latency and high-bandwidth technology. The technology has also introduced 5G and Wi-Fi 6 which support high-speed internet surfing. The introduction of Network File System (NFS) in this era sparked the demand for Ethernet. NFS also increased the use of UNIX in education and professional computing in the 1980s. Then, in 1982, Token Ring Topology emerged as an alternative to the internet and was only standardized in 1985. Network security is an important factor in ensuring data is not stolen or damaged. With the increasing knowledge of hacking and cracking, and the availability of tools that can be easily used to launch attacks or intrusions, it is important to investigate when an attack occurs. One network forensic method for monitoring attacks on the network is using Snort IDS and Ntop to facilitate the logging process for monitoring the network system. Based on the results obtained from designing a network security with Snort Intrusion Detection System (IDS) using ACID (Analysis Console for Intrusion Databases) with the utilization of IPTables on Ubuntu Server can stop attackers. In this research, the researcher used IPTables on Ubuntu as a firewall to anticipate attacks. To prevent port scanning attacks conducted by the attacker, the author created a firewall using IPTables where the IPTables rules aim to block the IP address of the attacker.
Application of The Haversine Method In The Android-Based Donation Search Application Daniel Daniel; Desiyanna Lasut
bit-Tech Vol. 6 No. 1 (2023): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v6i1.736

Abstract

Used goods that we no longer use will only fill the room which if we leave it will be damaged and have no use value because it consumes time. If given to someone else, the goods may still be useful and can help their lives the problem is how we find people who need our goods and vice versa. For this reason, a system is needed that can help facilitate and bring the two parties together. The effort made to make it easier for the recipient to contribute in taking the donated goods is to use the haversine method so that the recipient can consider the distance between them and the donated item. The haversine formula is an equation that uses latitude and longitude to find the distance between the two different points. By using the haversine formula, the output is the distance from the location of the party receiving the donation (current location) to the donor. Therefore, the author wants to create and design an android-based application so that it can reach many people and can make it easier for donors to donate their goods or for the recipient of donations in looking for items that have been donated.
Market Segmentation Analysis Using the K-Means Algorithm to Determine Sales Patterns Clerence Antonius; Desiyanna Lasut
bit-Tech Vol. 7 No. 1 (2024): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v7i1.1504

Abstract

This research aims to apply the K-Means method in classifying egg stock, speeding up stock searches to meet consumer demand, and efficiently analyzing the amount of egg stock for inventory at PT. Kaizen Prima Bersama. The prospect of developing laying hens is expected to be able to meet community demand, especially for use as a business to meet community production and consumption needs. As datasets grow, single CPU based approaches will lose their efficacy. This research aims to develop a parallel universal K-Means algorithm that is capable of handling larger datasets. To overcome this challenge, the K-Means Clustering algorithm is used. The application of the K-Means clustering algorithm in managing egg supplies provides advantages in recording data. This algorithm facilitates categorization of inventory levels based on specific attributes. Utilizing available information, the K-Means clustering algorithm professionally groups egg supply into daily transactions, to meet consumer needs.This research method uses data mining, namely the Knowledge Discovery Database (KDD) to obtain various patterns obtained from data. This method is expected to help company manages egg stocks more effectively. The benefits resulting from this research include the development of an information system that can speed up the data input and output process on egg stock taking, reduce the accumulation of records in paper form, and create an information system that makes work more efficient and easier to understand. With the information system implemented, it is hoped that company can improve operational performance and respond quickly to the dynamics of the egg market.
Co-Authors Clerence Antonius Daniel Daniel Dicky Surya Dwi Putra Indah Fenriana Ruruh Wuryani Susanto Hariyanto