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ILKOM Jurnal Ilmiah
Published by Universitas Muslim Indonesia
ISSN : 20871716     EISSN : 25487779     DOI : -
Core Subject : Science,
Computer Science & IT
ILKOM Jurnal Ilmiah is an Indonesian scientific journal published by the Department of Information Technology, Faculty of Computer Science, Universitas Muslim Indonesia. ILKOM Jurnal Ilmiah covers all aspects of the latest outstanding research and developments in the field of Computer science, including Artificial intelligence, Computer architecture and engineering, Computer performance analysis, Computer graphics and visualization, Computer security and cryptography, Computational science, Computer networks, Concurrent, parallel and distributed systems, Databases, Human-computer interaction, Embedded system, and Software engineering.
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Articles 18 Documents
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Search results for , issue "Vol 13, No 1 (2021)" : 18 Documents clear
Forensic storage framework development using composite logic method Helmi Rachman; Bambang Sugiantoro; Yudi Prayudi
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i1.811.58-66

Abstract

Increasing number of information technology users allows possibility for crimes to take advantage of information technology to continue increasing either directly and indirectly. Criminals often use computer devices to commit crimes. This is a major concern so that the need for handling digital evidences becomes significantly urgent. Therefore, a forensic storage framework is required for managing digital evidences. This framework is designed by applying the composite logic method to determine role model of each variable or the initial pattern of the stages to be collaborated. Composite logic produces a role model that is to generate patterns in order to achieve the same goal. This method collaborates framework for handling the pre-existing hdd, ssd, and vmware to be in turn combined into a forensic storage framework. Based on the results of the test, this study proposes a new framework called forensic storage framework which comprises of four main stages, namely preparation, collection, analysis and report. The advantage of this framework is that it can be used to handle digital evidences in four storages which are SSD, HDD, VmWare, and cloud.
The comparison of k-means and k-medoids algorithms for clustering the spread of the covid-19 outbreak in Indonesia Wargijono Utomo
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i1.763.31-35

Abstract

The coronavirus spreads quickly through human-to-human transmission via close contact and respiratory droplets such as coughing or sneezing. Various studies have been carried out to deal with Covid-19. However, the cure for this virus has not been found until now. Based on data from the covid19.go.id page retrieved on January 1st, 2021, which was updated by the Ministry of Health, the overall number of confirmed cases was 1,078,314 active cases reaching 175,095 or 16.2% of confirmed cases, recovered 873,221 or 81.0% of confirmed cases, and death 29,998 or 2.8% of the confirmed cases. This study compares the two algorithms of data groups to analyze clustering patterns to determine the best data processing method. The data in this study sourced from the Ministry of Health, contained 4 attributes, including confirmed cases, treatment, recovery, and death cases. In this study, only 2 attributes were used: the confirmed and death cases. From the data analysis and processing results through a comparison between the K-Means method and the K-Medoids for clustering the spread of the coronavirus in Indonesia, a conclusion is derived. With the Davies Boulden index value from K2 to K9 values, it turns out that the K-Means method gets the smallest value at the K-5 of 0.064, while K-Medoids at the k-2 value of 0.411. Thus, from the two methods used, it can be concluded that the best method for clustering the spread of the coronavirus outbreaks in Indonesia is the K-Means method.
Steganographic techniques using modified least significant bit and modification reshape transposition methods Guntoro Barovih; Fadhila Tangguh Admojo; Yoda Hersaputra
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i1.848.67-77

Abstract

A message is a form of conveying information. Various ways are used to secure the information conveyed in the form of messages either in encrypted form or in the form of applying a password in the message. Messages can also be encrypted and embedded in other media such as images (steganography). This research aimed to insert a message into the form of an image by combining the Modified Least Significant Bit (MLSB) method in encrypting messages and reshape modification technique to determine at which position the message encryption will be embedded in the image. Tests were carried out to obtain the quality of the encryption process using the parameters of Fidelity, mean square error, peak signal to noise ratio, testing on file type, robustness, and comparison of message contents. The results of the tests showed that the files that can be used are files with the image file type in the lossless compression category, the rotation can be done at 90, 180, 270 without destroying the message in it, and changing the pixel in the image file will destroy the message inside
Implementation of knowledge management system in cattle farming Edi Kusnadi; Yessy Yanitasari; Supriyadi Supriyadi
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i1.785.36-44

Abstract

Cattle are the livestock of the Bovinae family and subfamily Bovidae. They have been raised for beef and dairy products. Nowadays, beef production does not meet national needs. This is influenced by several factors. One of them is the farming pattern. However, knowledge about cattle farming is still scattered and unstructured. Knowledge Management System (KMS) offers a knowledge system that can be used to create, collect, store, maintain and disseminate knowledge. In this study, KMS for cattle farming has been implemented using the Knowledge Management System Life Cycle (KMSLC) method. The research results are web-based applications regarding cattle farming management that have been tested by experts and users, with the average test results declared good. The features possessed by this KMS application are knowledge capture, knowledge sharing, and knowledge application systems so that they can share knowledge between one user and another. In addition, this application is equipped with a discussion forum that can serve as a place to interact with fellow users or with experts.
Object motion detection in home security system using the binary-image comparison method based on robot operating system 2 and Raspberry Pi Abdul Jalil; Matalangi Matalangi
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i1.686.1-8

Abstract

This study aims is to build a home security system based on object motion detection using the Robot Operating System 2 (ROS2) and the Raspberry Pi. ROS2 in this study was used to read and process the camera data and to control the buzzer sound. At the same time, the Raspberry Pi hardware functioned to run  ROS2 using the Linux Ubuntu 18.04 operating system. The camera function to read the image and video data could be developed for the input device to control the home security systems based on object motion detection. The method used to detect an object motion was Binary-Image Comparison (BIC). This method works by comparing the value of the binary image object with the binary master and using it as a decision-making algorithm when the camera detected the object movement based on the object colors. The object colors that were detected in this study were red, yellow, green, and blue. Each object color was processed using the OpenCV library in the ROS2 node service. After that, all of the nodes communicated through topics to communicating and exchanging the message data. This study has successfully developed a prototype that can generate a buzzer sound warning to the user when the camera detected the object motion based on the object color.
Evaluation of lambung mangkurat university student academic portal using user experience questionnaire (UEQ) Yuslena Sari; Novitasari Novitasari; Hani Pratiwi
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i1.787.45-50

Abstract

The student academic portal is one of the Academic Information Systems at The University of Lambung Mangkurat (ULM). The ULM student academic portal can only be accessed by the ULM students. It can be used for academic guidance, managing student study plans, printing test cards, filling out questionnaires, and viewing exam results (assessment). However, since its release in 2016, there has been no publication regarding evaluations on the website-based ULM student academic portal. Evaluation is one of the stages in the Software Development Life Cycle (SDLC). This stage allows the user to assess the system. This study aims to evaluate the academic portal of the ULM students. Evaluation is carried out to determine the user's evaluation of the existing system. The evaluation method used is the User Experience Questionnaire (UEQ). With this method, users can assess the ULM Student Academic Portal from various aspects: Novelty, Stimulation, Dependability, Efficiency, Perspicuity, and Attractiveness. The results of this study indicate that the Perspicuity aspect gets a high score while Novelty gets a low score.
Compute functional analysis leveraging the IAAS private cloud computing service model in packstack development Mohamad Iqbal Suriansyah; Iyan Mulyana; Junaidy Budi Sanger; Sandi Winata
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i1.693.9-17

Abstract

Analyzing compute functions by utilizing the IAAS model for private cloud computing services in packstack development is one of the large-scale data storage solutions. Problems that often occur when implementing various applications are the increased need for server resources, the monitoring process, performance efficiency, time constraints in building servers and upgrading hardware. These problems have an impact on long server downtime. The development of private cloud computing technology could become a solution to the problem. This research employed Openstack and Packstack by applying one server controller node and two servers compute nodes. Server administration with IAAS and self-service approaches made scalability testing simpler and time-efficient. The resizing of the virtual server (instance) that has been carried out in a running condition shows that the measurement of the overhead value in private cloud computing is more optimal with a downtime of 16 seconds.
Clustering the potential bandwidth upgrade of FTTH broadband subscribers Sasa Ani Arnomo; Yulia Yulia
ILKOM Jurnal Ilmiah Vol 13, No 1 (2021)
Publisher : Teknik Informatika Fakultas Ilmu Komputer Univeristas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v13i1.805.51-57

Abstract

A company needs to consider determining the customers’ potential before deciding to upgrade their bandwidth. It is important because, previously, determination was conducted randomly. Therefore, potential determination is necessary by grouping customers who have similar characteristics based on their data and attributes. This study employs data mining techniques using clustering method with K-means algorithm on broadband users’ group of 263 FTTH. The determination was determined based on end centroid point in the grouping. The results were divided into 5 clusters consisting of 34 highly potential users (12.92%), 29 potential users (11.02%), 56 fairly potential users (21.3%), 54 less potential users (20.53%), and the remaining 90 not potential users (34.22%). The comparison of the validity of the Davies-Bouldin Index for the 5 (five) clusters is 0.538 for K-Means and 0.819 for K-Medois. This indicates that K-Means results better score. This method is useful for efficient bandwidth sharing.

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