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INDONESIA
JURNAL MEDIA INFORMATIKA BUDIDARMA
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Budi Darma
ISSN : 26145278     EISSN : 25488368     DOI : http://dx.doi.org/10.30865/mib.v3i1.1060
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
Decission Support System, Expert System, Informatics tecnique, Information System, Cryptography, Networking, Security, Computer Science, Image Processing, Artificial Inteligence, Steganography etc (related to informatics and computer science)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,182 Documents
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Identification of Regional Origin Based on Dialec Using the Perceptron Evolving Multilayer Method Okvi Nugroho; Opim Salim Sitompul; Suherman Suherman
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6301

Abstract

Voice detection is very important for the world of information technology that can be used for voice processing, biometrics, human computer interfaces. Voice identification carried out in this study is based on speech or dialect using a prototype that has been designed using the Raspiberry Pi device and other supporting devices. In its application, the regional identification prototype uses sound feature extraction, namely Mel Frequency Cepstral Coefficients (MFCC) and uses an artificial neural network method with a multilayer perceptron (secos) developing algorithm. The purpose of this study is to identify regional origins based on dialect or speech using the Mel Frequency Cepstral Coefficients (MFCC) extraction technique and the Evolving Multilayer Perceptron method. The results of the regional recognition test produce a good level of accuracy, with testing as an example of the Aceh area with test data of 10 voice samples, the results obtained by the prototype can identify voices with a success rat of being able to recognize 7 voices out of 10 samples tested in the Aceh region. From all the tests on the areas of Aceh, Karo, Nias, Simalungun, the accuracy was 88%
Sistem Optimalisasi Pengadaan Alat Kesehatan Menggunakan Metode Fuzzy Time Series Febrina Sari; Soni Fajar Mahmud; Rudi Faisal
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6405

Abstract

Controlling the procurement of Medical Devices is an important matter for the Pharmacy industry to pay attention to in order to win highly competitive competition, therefore an appropriate model and strategy is needed so that the number of sales can increase, the right solution is to maintain optimal stock availability. this is in line with the Regulation of the Minister of Health of the Republic of Indonesia Number 35 of 2014, concerning pharmaceutical service standards at pharmacies for pharmaceutical preparations, medical devices and consumables which includes procurement and control. The purpose of this study is to assist pharmacies in optimizing the procurement of medical devices by applying the fuzzy time series Chen model, so that they can overcome stock emptiness and over stock, besides that the pharmacy has a system that can predict the optimal number of medical device product purchases for the next period. which has an impact on the ability to control stock. The results showed that the fuzzy time series method of the Chen model has very good performance. This can be seen from the value of the accuracy of the forecasting results which is calculated using the AFER (Average Forecasting Error Rate) formula with a value of 4%. The number of medical devices that will be provided for the January 2023 period is 15 pieces.
Penerapan Klasifikasi Algoritma C4.5 Dan Algoritma C5.0 Untuk Mengetahui Tingkat Kepuasan Mahasiswa Terhadap Website Sistem Informasi Terpadu Layanan Program Studi (SIPLO) Nurfitrayani Nurfitrayani; Islamiyah Islamiyah; Amin Padmo Azam Masa
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6433

Abstract

Integrated Information System for Study Program Services (SIPLO) is a website-based information system for academic services at the study program level, specifically designed for the Information Systems Study Program at Mulawarman University. Despite containing information that supports lectures, SIPLO's features and information have not met students' satisfaction, as indicated by data collected through interviews. Therefore, the objective of this study was to determine the level of student satisfaction with the SIPLO website.This study employed a data mining technique using the classification methods of the C4.5 algorithm and the C5.0 algorithm. The PIECES indicators, which include performance, information, economy, control, efficiency, and service, were used as attributes in the data mining application. The data utilized in the study consisted of questionnaires distributed to 182 students from the Information Systems Study Program at Mulawarman University in 2019, 2020, and 2021. The data was divided into a 80% training data and a 20% test data ratio. The research findings using the C4.5 algorithm revealed that the variables influencing student satisfaction are performance, control, information, efficiency, and service. Meanwhile, the C5.0 algorithm identified control, performance, efficiency, information, and service as the influential variables. Both algorithms yielded an accuracy value of 91.89%, precision value of 93.75%, recall value of 96.77%, F1-Score value of 95.24%, and an AUC value of 0.8172. These results indicate a good classification performance. 
Analisis Data Mining dalam Komparasi Average Linkage AHC dan K-Means Clustering untuk Dataset Facebook Live Sellers Jhiro Faran; Rima Tamara Aldisa
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6892

Abstract

Facebook Live is a social media platform owned by Facebook that allows users to broadcast videos directly or live stream via the internet. Users can share moments in real-time with friends, followers, or members of certain groups. The platform allows anyone with a Facebook account to create live video broadcasts from a mobile device or computer equipped with a webcam. Many Micro, Small and Medium Enterprises (MSMEs) use Facebook Live as a tool to sell products or services directly to their audience. This strategy is increasingly popular in direct marketing on social media, especially in countries such as China and Thailand. Sellers on Facebook Live, known as Facebook Live Sellers, broadcast live on the platform to introduce products or services. They explain all the features offered, answer questions from viewers, and encourage them to make a purchase immediately. To increase buyer interest, they often offer special offers or discounts. Facebook Live Sellers can also be considered a form of influencer marketing, where individuals or businesses build a loyal following and use their influence to promote products and services. Despite the potential benefits, Facebook Live Sellers also face challenges. They interact directly with potential buyers, who may sometimes be dissatisfied with the product offered or the way the seller promotes it. Therefore, evaluations such as comments, reactions (such as like, unlike, angry), and other interactions during broadcasts are important. This research aims to group potential buyers' reactions during Facebook Live broadcasts as a strategy to overcome several problems in direct sales via this platform. In addition, grouping by the number of likes and comments can help sellers identify the most active groups of buyers and have the potential to become loyal customers. The number of data samples was determined using the Solvin method so that the dataset that became the data sample was 341 data. The methods used for grouping are K-Means and AHC (Average linkage) with the final results showing that the amount of data grouped into three clusters by both methods is the same, with most of the data being in Cluster 0, namely 98.5% of the total data sample. . Cluster 1 has a small amount of data, namely 0.6%, while Cluster 2 has 0.9% of the data sample.
Evaluasi Performa Algoritma Naïve Bayes Dalam Mengklasifikasi Penerima Bantuan Pangan Non Tunai Mohammad Mastur Alfitri; Nurahman Nurahman; Minarni Minarni; Depi Rusda
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6151

Abstract

The improvement of the standard of living of the community in Bapinang Hulu Village is carried out through various social assistance programs. However, the realization of the implementation of social assistance programs did not go smoothly. Social jealousy often occurs among the community during the distribution of social assistance. The distribution of assistance is carried out based on the assessment of the village officials and the Village Consultative Body, which is then validated by the heads of RT and RW. The quota provided by the government is often not in accordance with the actual number of eligible recipients in the village. Another difficulty is determining the criteria or attributes used for the selection of Non-Cash Food Assistance recipients. This study aims to obtain a classification model from which the classification pattern can be applied to the population data of Bapinang Hulu Village for the selection of social assistance recipients. To solve this problem, the classification method is applied using the Naive Bayes Algorithm. The research results show that the performance of the Naive Bayes algorithm model before feature selection had the highest accuracy in the 8th test with an accuracy of 89.80%. Meanwhile, after feature selection, the highest accuracy was found in the 3rd test with an accuracy of 88.37%. The feature selection using the Information Gain algorithm reduced the number of attributes from 16 to 6. Therefore, it is known that the highest accuracy is obtained before feature selection, but in selecting social assistance recipients, more criteria need to be applied, which is time-consuming. Meanwhile, after feature selection, only 6 criteria are used to determine social assistance recipients.
Sistem Pendukung Keputusan Penerapan Metode MOOSRA dan Pembobotan ROC dalam Penilaian Kinerja Laboran Kimia Deby Lorensyah Rambe; Ali Akbar Ritonga; Elysa Rohayani Hasibuan; Iwan Purnama
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6381

Abstract

Laboran is a designation for technical personnel who operate in a laboratory environment or a place related to scientific, research or testing activities. A chemical worker is a technical worker who has specific knowledge and skills in the chemical field. In schools, chemical workers have a role as workers who supervise and manage chemical laboratories. His main duties include sampling, material testing, data processing and maintenance of laboratory equipment. The school needs to know the performance of each chemical worker, so an assessment of the performance of each chemical worker is needed so that the school knows the best performance of the chemical worker, an additional salary will be added. The performance assessment includes several criteria namely Technical Expertise, Professional Ethics, Problem Solving, Punctuality, Safety and Health, Maintenance of tools and materials, Report Quality, Self-Development, Accuracy, Teamwork and Communication. To simplify the evaluation system for the performance of chemical workers and find out who is the best, a decision-making system is needed, namely a decision support system (DSS). SPK is a system designed to assist decision makers in solving problems or choosing the best option from various available alternatives. In this study the authors used the MOOSRA (Multi-Objective Optimization on the Basis of Simple Analysis) method and ROC (Rank Order Centroid) weighting. The MOOSRA method is a stable, consistent, and reliable multi-criteria comparison method that can provide an accurate assessment of chemical workforce performance. From the application of the ROC and MOOSRA methods, it was obtained an assessment of the performance of the chemical workforce with the chemical workforce alternative with the highest performance, namely the LK07 alternative on behalf of Gueen with a value of 207.95261.
Pengenalan Potensi Racun dan Peningkatan Keamanan Pangan Dalam Jamur Menggunakan Convolutional Neural Network Ilham Rafiedhia Pramutighna; Arief Hermawan
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6372

Abstract

One promising advancement in the field of food agriculture is the cultivation of mushrooms. Mushrooms can be broadly classified into two groups: edible mushrooms and non-edible mushrooms. Edible mushrooms serve various purposes, including as food, medicine, and other applications, while non-edible ones can lead to poisoning. However, distinguishing between edible and non-edible mushrooms is a complex task. Even a slight error in selecting suitable mushrooms for consumption can have health repercussions for consumers. The progress in science and technology, particularly in digital image processing, aids in the classification of mushrooms. Image classification using Convolutional Neural Networks (CNNs) presents an alternative to address this issue. This research primarily focuses on identifying potential toxins in mushrooms using CNNs, aiming to contribute to a more efficient and accurate approach in classifying mushrooms fit for consumption. The results demonstrate that the model trained with data augmentation achieved the highest accuracy, with 96.53% for training data and 93.22% for validation data, accompanied by lower loss rates. This underscores that CNNs are an efficient and accurate approach in classifying mushrooms based on their genus. Furthermore, this study also discovered that parameters such as the number of epochs, batch size, optimizer, image size, and image augmentation influence the model training process.
Perbandingan Matriks Loss Pada Model Deep Learning Resnet50 dan Xception dalam Deteksi Objek Herimanto Herimanto
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 4 (2023): Oktober 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i4.6849

Abstract

The implementation of deep learning has expanded into various fields, not confined solely to the field of education, particularly in computer science. It has also integrated technology into various other domains, including geospatial, remote sensing, and even the medical field. This development has made a significant contribution to reshaping the way humans understand and tackle challenges across different sectors. In this context, deep learning is employed for object detection and classification. Despite the considerable progress facilitated by the application of deep learning, object detection remains a challenge that is not entirely resolved. Constraints such as variations in lighting conditions, angles of view, and object diversity make achieving high-accuracy object detection a difficult task. Therefore, further research is required to comprehend and compare the performance of various deep learning models in addressing this issue. This research focuses on the comparison of two deep learning models, namely ResNet50 and Xception, in terms of loss metrics when detecting an object, in this case, a chair. The models are provided with input images of chairs and predict whether the chairs are empty or occupied. The results obtained from this research indicate that the ResNet50 model has a lower total loss value of 0.19422098, while the Xception model has a total loss value of 1.1822930. The lower the loss value, the better the model's performance. Based on the comparison results, the author has developed a web application simulator using Flask, utilizing the model with the lowest loss, which is the ResNet50 model.
Optimisasi Biaya Distribusi Furniture dengan Metode Tocm-Sum Approach dan Lowest Supply Lowest Cost Elpita Sari Hasibuan; Rina Filia Sari
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6440

Abstract

PT. Jipta Rimba Djaja is a company engaged in the manufacture of furniture, one of which is the manufacture of plywood. The key to the success of a company can be determined from how the company's marketing, so as to get maximum profit. In order to achieve this goal, the program that must be carried out for the company is to distribute goods or services produced to consumers. In solving transportation problems, there are two solutions, namely the initial solution and the optimal solution. Initial settlement is a solution to find an allocation of goods/products from one source to several destinations. There are many methods that can be used to determine the initial solution, including the Lowest Supply Lowest Cost (LSLC) method and the Total Oppurtunity Cost Matrix-SUM (TOCM-SUM) Approach method. Which is used to determine the most effective allocation of goods and aims to find out the results of optimizing transportation costs from sources to certain destinations with the minimum possible cost. Based on calculations using the TOCM-SUM APPROACH method and the Lowest Supply Lowest Cost (LSLC) method on the transportation costs of distributing furniture (plywood) at PT. Tjipta Rimba Djaja in January 2023 of Rp. 2,507,898,000, - and in February 2023 the optimal cost of distribution is the same, namely Rp. 1,457,324,000. Where the difference between the two is that the calculation steps of the Lowest Supply Lowest Cost (LSLC) method are not as many as those of the TOCM-SUM APPROACH method. So that the completion is faster than the TOCM-SUM APPROACH method.
Metode Naive Bayes Classifier dan Forward Selection Untuk Deteksi Berita Hoaks Bahasa Indonesia Danang Bagus Chandra Prasetiyo; Pulung Nurtantio Andono; Catur Supriyanto
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6459

Abstract

Presently, hoaxes or fake news have become a serious threat to human life. Hoax news can not only cause material harm and chaos in society, but now fake news can also affect a person's psychology by causing fear and terror, and at worst, it can break national sovereignty. To process the classification, data miming is used so that it can be seen whether a news item is hoax or genuine news. In this study, researchers used naïve Bayes as a classification method. Then the researcher also uses the forward selection function used in the Naïve-Bayes method. Forward selection is the best regression model formation method based on an approach by selecting variables by including the independent variables that have the largest correlation values. While the naïve Bayes algorithm works conditionally independent between predictions. Based on the tests that have been carried out on the classification of Indonesian hoaxes using Naïve Bayes and Forward Selection to obtain an accuracy of 84%, and a recall of 63.72% while the precision increases to 91.19% with an increase in accuracy of 8.8% and a recall of 8.19% and precision increased by 20.98%. It is hoped that the level of accuracy in the classification of Indonesian hoax news using the naïve Bayes method using forward selection can be increased.

Page 91 of 119 | Total Record : 1182

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