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All Journal Jurnal Media Infotama International Journal of Artificial Intelligence Research JMM (Jurnal Masyarakat Mandiri) JUTIM (Jurnal Teknik Informatika Musirawas) Jurnal Dehasen Untuk Negeri Jurnal Media Computer Science Jurnal Dehasen Mengabdi Jurnal Komputer, Informasi dan Teknologi
Juju Jumadi
Universitas Dehasen Bengkulu
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Implementasi Metode K-Means Clustering Pada Segmentasi Citra Digital Efran Fernando Ade Pratama; Khairil Khairil; Juju Jumadi
Jurnal Media Infotama Vol 18 No 2 (2022): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v18i2.2899

Abstract

ABSTRACT:Image segmentation is the process of placing a label for each pixel in an image therefore pixels with the same label share certain visual characteristics. One of the algorithms that can be applied in accelerating the segmentation process is K-Means Clustering. K-means is a non-hierarchical clustering method that tries to partition existing data into one or more clusters. This method partitions data into clusters so that data with the same characteristics are grouped into the same cluster and data with different characteristics are grouped into other clusters. The implementation of the system uses the Visual Basic 2010 programming language and the method used in this research is the waterfall method. The results of the analysis carried out show that the similarity of the identified images based on the proximity of the color values ​​and the accuracy produced is quite good, especially for objects that have special colors or colors that have become characteristics of the object. Keywords: Digital Image, Segmentation, Clustering, K-Means
Sistem Pakar Untuk Mendiagnosa Penyakit Bronkho Pneumonia Menggunakan Metode Certainty Factor Pada Klinik Assifa Bengkulu Shintia Cantika; Indra Kanedi; Juju Jumadi
Jurnal Media Infotama Vol 19 No 2 (2023): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v19i2.4239

Abstract

Abstract_Broncho pneumonia can occur at any age caused by pneumococcal bacteria. Usually the symptoms of bacterial pneumonia are preceded by a mild respiratory infection a week earlier. Implementation of expert systems in the field of health and medicine in the form of initial diagnosis, treatment of the results of the diagnosis, determination of visible clinical symptoms. As-Shifa Bengkulu Clinic is one of the health clinics in the city of Bengkulu. In its service, this clinic serves all those related to disease from children to adults. One of them is Broncho Pneumonia. The lack of expert doctors in handling every problem in this clinic is one of the problems that occur. So that this can cause patients to wait a long time or not be able to consult directly with a doctor. Of course this takes time and will be in vain if the doctor concerned is not available. Therefore an expert system is designed to diagnose Broncho Pneumonia with the Certainty Factor method. This expert system is designed using the PHP Programming Language and MySQL database. The expert system created can make it easy for users to consult online about Broncho Pneumonia.
Citra Digital Identifikasi Kematangan Buah Sawit Berdasarkan Warna RGB dan HSV Menggunakan Metode Self Organizing Map (SOM) Rahmat Pidi Putra; Juju Jumadi; Deri Lianda
Jurnal Media Infotama Vol 20 No 1 (2024): April 2024
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i1.5354

Abstract

Palm oil is one of the largest export commodities in Indonesia. Accuracy in determining the level of maturity of oil palm fruit determines the quality of this plant's harvest. This research uses digital image processing to identify the maturity level of oil palm fruit based on RGB (Red, Green, Blue) and HSV (Hue, Saturation, Value) colors. Images in the form of photos of oil palm fruit taken with a digital camera were processed with MATLAB software and then analyzed using the Self Organizing Map (SOM) method to obtain a comparison of the RGB and HSV feature extraction results. The results of the research succeeded in distinguishing the level of maturity, namely very ripe, ripe, almost ripe and unripe, the color of the oil palm fruit was red, black orange, yellow and black. The accuracy of the results using the performance evaluation matrix method of the SOM method, namely Quantization Error, Silhouette Score and Topographic Error. Quantization Error RGB (0.004737) is lower than HSV (0.073178) which shows RGB's ability is good in representing data in SOM, Silhouette Score HSV (0.704204) is higher than RGB (0.599846) indicating HSV's ability is slightly better in grouping objects and both have no problems on Topographic Error mapping (0.000000). In the RGB image similarity approach, it is better than HSV.
Implementasi Machine Learning Untuk Prediksi Penjualan Oli Shell Pada CV. Harapan Karya Mandiri Bengkulu Dellya Septari; Indra Kanedi; Juju Jumadi
Jurnal Media Infotama Vol 20 No 2 (2024): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i2.6513

Abstract

Prediction is an activity of guessing or estimating something that will happen in the future by utilizing historical data through a scientific method. CV. Harapan Karya Mandiri in predicting oil sales is still in a conventional way. The weaknesses of conventional systems are in addition to human error in doing calculations and writing and can also be lost when doing recapitulation. For this reason, a machine learning technique is needed that is able to predict sales. One of the algorithms included in Machine Learning is K-Nearest Neighbor. The system implementation uses the PHP programming language with the MySql database and the method used in this research is the Waterfall method. The waterfall method is able to analyze the needs used to find out from the weaknesses of the old system, then make a design of the design and continue with the design of the new system. The conclusion from the results of this study explains that the sales prediction process with the K-Nearest Neighbor method first goes through a training process. The prediction results are also strongly influenced by the amount of data being trained and the value of "k" in this method.
Implementasi Metode Complex Proportional Assessment Untuk Pemilihan Reseller Terbaik Pada CV. Harapan Karya Mandiri Bengkulu Olvi Mariani; Juju Jumadi; Abdussalam Al Akbar
Jurnal Media Infotama Vol 21 No 2 (2025): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v21i2.9237

Abstract

A reseller is someone who resells products from a supplier to consumers using the reseller's price. The role of resellers cannot be separated from business competition. Resellers are one of the sales methods used by sellers to sell products to customers. For CV. HKM Bengkulu, it is certainly not an easy task to evaluate the performance of resellers achieved by each reseller for the company. Therefore, a computerized decision-making system is needed to assist and simplify the selection of the best reseller. Decision Support System (DSS) research method used in this study is the waterfall method. COPRAS method analysis that will be carried out in this research will describe the stages needed to implement COPRAS in selecting the best reseller at CV. Harapan Karya Mandiri Bengkulu. To perform the calculation process using COPRAS method, the determination of alternatives (An) and criteria, as well as the weights of each criterion, will be conducted. The criteria used are payment type, transaction volume, total spending, quantity of purchases, and subscription duration. The conclusion of this research explains the results of the calculation using COPRAS method, where the reseller with the highest value will occupy the highest ranking followed by the reseller with the lowest value.
Implementasi Kombinasi Hill Cipher Dan Steganografi Least Signifiaction Bit Untuk Evaluasi Kualitas Citra Digital Redo Osi Putra; Juju Jumadi; Ockhy Jey Fhiter. W
Jurnal Media Infotama Vol 22 No 1 (2026): April 2026
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v22i1.9914

Abstract

This study implements a combination of Hill Cipher and Least Significant Bit (LSB) steganography to improve data security and evaluate digital image quality. The Hill Cipher is used to encrypt text with 2×2 key matrix, while LSB inserts the encrypted message into the least significant bits of BMP image. The research method used is applied research with stages of analysis, design, implementation, and testing. The test results show that the integration of these two methods maintains image quality with a low Mean Square Error (MSE) value (0.0001–2.9424) and high Peak Signal-to-Noise Ratio (PSNR) (83.6554–103.4438 dB), indicating visually undetectable changes. The simulations prove the effectiveness of the system in securing data without significant image degradation. The conclusion of this study is that the combination of Hill Cipher and LSB steganography is effective in securing data without significantly compromising image quality. This study also provides an alternative solution for data security by utilizing hybrid cryptography and steganography techniques.
Perancangan Dan Implementasi Sistem Keamanan Jaringan Menggunakan Alienvault Pada SMK N 4 Kota Bengkulu Gita Dahlia Lestari; Juju Jumadi; Ahmad Asyhari
Jurnal Media Infotama Vol 22 No 1 (2026): April 2026
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v22i1.10958

Abstract

This study aims to design and implement a network security system using AlienVault OSSIM at SMK N 4 Kota Bengkulu. The method used in this research is the Network Development Life Cycle (NDLC), which consists of analysis, design, simulation, implementation, monitoring, and management stages. AlienVault is implemented as a standalone operating system running on a virtual machine using VMware and is utilized to perform centralized network monitoring, threat detection, and security management. System testing is conducted using the black box method by simulating attacks such as port scanning and ping flooding. The test results show that AlienVault is capable of detecting network activities, identifying connected devices, and providing alerts for suspicious activities. With the implementation of this system, network security at SMK N 4 Kota Bengkulu becomes more controlled, secure, and supportive of teaching and learning activities.
Co-Authors Abdussalam Al Akbar Ahmad Asyhari Annisa Putri Pratiwi Defri Wiranata Dellya Septari Devi Sartika Dewi Suranti Efran Fernando Ade Pratama Fredricka, Jhoanne Gita Dahlia Lestari Gustian Febri Syah Putra Hengki Jon Saputra Herlina Latipa Sari Ila Yati Beti Intan Diba Aulia Sari Jusuf Wahyudi Kanedi, Indra Kanedi Khairil Khairil Lena Elfianty Lianda, Deri M Dicky Imansyah Mesterjon Mesterjon Nofi Qurniati Ockhy Jey Fhiter. W Olvi Mariani Rahmat Pidi Putra Redo Osi Putra Reno Supardi Ridho Rahman Kurnianto Ronaldi Aprilianto Sallaby, Achmad Fikri Shintia Cantika