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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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Perbandingan Akurasi, Recall, dan Presisi Klasifikasi pada Algoritma C4.5, Random Forest, SVM dan Naive Bayes Azhari, Mulkan; Situmorang, Zakaria; Rosnelly, Rika
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2937

Abstract

In this study aims to compare the performance of several classification algorithms namely C4.5, Random Forest, SVM, and naive bayes. Research data in the form of JISC participant data amounting to 200 data. Training data amounted to 140 (70%) and testing data amounted to 60 (30%). Classification simulation using data mining tools in the form of rapidminer. The results showed that . In the C4.5 algorithm obtained accuracy of 86.67%. Random Forest algorithm obtained accuracy of 83.33%. In SVM algorithm obtained accuracy of 95%. Naive Bayes' algorithm obtained an accuracy of 86.67%. The highest algorithm accuracy is in SVM algorithm and the smallest is in random forest algorithm
Penerapan Metode Promethee Dalam Sistem Pendukung Keputusan Penetapan Penerima Kartu Indonesia Sehat (KIS) Siregar, Reva Octaviani; Irmayani, Deci; Masrizal, Masrizal
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2948

Abstract

Health is a state of well-being of body, soul and society that enables everyone to live productively socially and economically. Therefore, health is the most important element in human life. Health is closely related to economic conditions. factors that affect human health such as healthy food and drinks, a healthy environment and healthy living habits will be fulfilled. Conversely, if a bad economy will make it difficult for individual people to meet some of these factors, if these conditions are ignored, the individual community will find it difficult to improve their health. The problem that occurred at Galang Health Center was the unsatisfactory selection of KIS (Kartu Indonesia Sehat) participants. the selection of KIS (Kartu Indonesia Sehat) participants requires a decision support system (DSS) to speed up and make it easier to make decisions. Decision support systems are used to assist decision making in an organization to facilitate decision making. Where no one knows exactly how decisions should be made. The Promethee method (Preference Ranking Organizational Method for Enrichment Evaluation) is a method used to determine priority (order) in multi-criteria analysis. With the Promethee method, the problem of choosing KIS (Kartu Indonesia Sehat) participants is feasible to use in this study, the stages of research carried out in this study are starting from data collection, problem analysis, method analysis, design and testing of applications to be built, the purpose of this research is to solve the problems of the participants. KIS (Kartu Indonesia Sehat), which have been unsatisfied in terms of the decision of KIS (Kartu Indonesia Sehat) recipients. The results showed that of the three KIS (Kartu Indonesia Sehat) participants who were tested, there were two participants who deserved KIS (Kartu Indonesia Sehat) based on the results of the assessment of the five criteria used so that the calculation results using the Promethee method showed that the net flow from each of the alternatef is -1 for alternative 1 and 0.2 for alternative 2 and 0.8 for the third alternative.
Fuzzy Neural Network (FNN) Pada Proses Identifikasi Penyakit ISPA Saputra, Dhio; Yanto, Musli; Safitri, Wifra; Mayola, Liga
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 3 (2021): Juli 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i3.3020

Abstract

ISPA is a disease that can affect anyone from children, adolescents, adults, and even the elderly. The causes experienced by sufferers of this disease are quite simple, such as fever, runny nose, and cough. The discussion in this paper describes the process of ISPA disease identification by developing a Fuzzy Neural Network (FNN) model. The process will be optimized using Fuzzy Logic to form rules for the diagnostic process, then proceed with an Artificial Neural Network (ANN). This model can maximize the performance of ANN in the identification process so that the output given is quite precise and accurate. The results provided by Fuzzy Logic can describe the clarity of the rules in diagnosis by presenting several rules (rules) that are presented from the Fuzzyfication process to the Defuzzyfication process. The output obtained from the ANN process also shows quite perfect results with an average error value based on MSE of 0.00912 and accuracy value of 91.96%. With these results, it can be stated that the FNN model can be used in the ISPA diagnosis process so that the presentation of this paper aims to provide an alternative in the identification process
Penerapan Pengenalan Wajah Untuk Aplikasi Absensi dengan Metode Viola Jones dan Algoritam LBPH Buana, I Komang Setia
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 3 (2021): Juli 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i3.3008

Abstract

The human face can be used to assess because of its uniqueness based on certain parameters. To perform facial recognition, the first thing that needs to be done is face detection. The author uses the Viola-Jones method to detect faces. The Viola-Jones method is known to have high speed and accuracy because it combines several concepts (Haar Features, Integral Image, AdaBoost, and Cascade Classifier) into the main method for handling objects. The principle of camera face recognition itself is that the captured face object will be processed and compared with all face images in the existing data set so that the identity of the face is known. One of the applications of face recognition is to do attendance with individual faces. The attendance process does not need physical contact interactions between humans and devices such as the fingerprint system so that during the current COVID-19 pandemic, the spread of the virus can reduce. In this research, a system that can be checked and a person's face is used as a leverage medium for arrival and return attendance using the Viola-Jones method and the LBPH algorithm. The language used is python with the OpenCV library. The PHP language is used for the user interface so that users perform attendance via a browser with the MySQL database to store attendance data. The result of the research is that using the Viola-Jones method and the LBPH algorithm faces are identified and the data is stored in the database used for data attendance. Distance and slope affect the results of face recognition. The distance is too close about 30 cm from the camera, the face cannot be detected. Instead of face position is too far approximately 200 cm, the face can still be detected but could not be identified. For a face tilt level of about 20o from perpendicular, it can still be recognized, but at a tilt degree of about 30o up or to the right, faces cannot be detected.
Penerapan Algoritma Crawling dalam Otomatisasi Verifikasi Pembayaran Tiket Seminar Eldy Dwi Sentosa; Iskandar Fitri; Agus Iskandar
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i1.2578

Abstract

The system for viewing student seminar payment data can be viewed through administrator controls. The seminar payment confirmation process for National University students still uses the manual system by paying the seminar organizer so it takes longer to process the seminar payment. The purpose of creating this system is to speed up the payment time of the seminar. This system uses a unique 3-digit code in each payment of seminar participants, this unique 3-digit code acts as a mark that differentiates student payments so that it does not require confirmation to the seminar organizer. Cron work will be performed on UNIX-based operating systems (Linux, Ubuntu, etc.) which function to perform tasks or scripts automatically. The content of the script is an order to execute the payment confirmation order against the participant. This level of research consists of several stages, namely needs analysis, design, writing system application code, application testing. This investigation has resulted in an application that can expedite the payment verification process by matching the number of transfer participants with those in the database. The results of testing the payment verification process are influenced by the Crawl Algorithm to help the payment process become more effective. With results that have been tested on average, it shows 4.8 seconds to confirm the participant's payment. With this seminar payment system, you can save time to process seminar payments.
IoT-Based Kobela Teaching Aid for Mathematics Learning Multiplication and Division Materials for Grade II Elementary School Students Setiawan, Muhammad Ilham; Suwastika, Novian Anggis; Prabowo, Sidik
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 3 (2021): Juli 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i3.3107

Abstract

Kotak Belajar Ajaib (Kobela) is props for elementary school math class II which can help learn to calculate multiplication and division. Based on research conducted by Sugeng Harnanto, Kobela can improve concentration, increase creativity and student learning outcomes. This tool has been tested in low-grade learning and extracurricular learning activities. The average student success in learning without using teaching aid is 54.56 (56.77%), after using teaching aid the average learning success rate reaches 90.52 (94.19%). The level of mastery learning for Basic Competencies: 3.1 Doing Multiplication of Two Numbers have increased by 37.42. In previous studies, the application of Kobela teaching aid in all learning activities was still manual-based. Potential or opportunities for development, especially for reading assessments and automatic data storage are possible to be achieved by implementing the Internet of Things (IoT). In this study, Kobela was built which implements IoT technology for reading, assessment, and recording based on learning activities. Then evaluate the system by testing the functionality of all the learning activities. From the test results, it was found that the system was running 100% by the specified function. The results of system performance testing in terms of sensor readings are on average 3 seconds with 8 Watt room lighting conditions and the average value of the assessment accuracy is 84.
Implementasi Speech Recognition Pada Aplikasi E-Prescribing Menggunakan Algoritme Convolutional Neural Network Azis, Nur; Herwanto, Herwanto; Ramadhani, Fathurrahman
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2841

Abstract

The process of manually prescribing drugs by doctors can cause several problems, including doctors not knowing what drugs are available and it takes time to find out what drugs are available in the pharmacy. Speech recognition is now widely used in various ways, which can help facilitate work. The application of speech recognition can be done in the e-prescribing application with the neural network method using the Convolutional Neural Network (CNN) algorithm, which is the basic method of deep learning. This study aims to facilitate physicians in filling out drug data in e-prescribing applications using speech recognition. The data used in this study were obtained from the open source dataset provided by Google and collected independent datasets. From the results of experiments that have been carried out, the accuracy achieved with 40 epochs and 40 direct impressions with different words is 90%. Where words are successfully recognized 36 words out of 40 words
Model Optimasi Jaringan Rantai Pasok Pada Sistem Informasi Harga Karet Rakyat Berbasis Web Irvai, Muhammad; Herdiansyah, Muhammad Izman
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2928

Abstract

The supply chain problems have traditionally resulted in inefficient distribution of the people's rubber production. The research scope is in Musi Rawas district. The purpose of this research is to optimize the people's rubber supply chain from each supply chain channel using an information system. The method of analysis used in this research is Linear Programming (LP). Conveyance capacity and labor hours serve as constraint functions, while the objective function is to maximize distribution profits from each rubber supply chain channel. From the results of testing the Quantitative Management (QM) application with a sample of farmers 1, village collectors 1 and sub-district 1 collectors in the first channel, a solution of type A products is obtained, which is 625 and a profit of X1 = 8218, then multiplied into a profit of Rp. 5,136,250. From the results of testing the Quantitative Management (QM) application with a sample of farmers and village / sub-district collectors 1 in the second channel, it was found that the product type A solution was 500 and the profit X1 = 7923, the profit was Rp. 3,961,500. From the results of testing the Quantitative Management (QM) application with a sample of farmers and UPPB 1 in the third channel, the solution for type B products is 562.5 and the profit X2 = 9897, the profit is Rp. 5,567,063. So from the results of the analysis using the QM application, the maximum benefit from the people's rubber supply chain in Musi Rawas district is in the third channel
Deep Learning dalam Mengindetifikasi Jenis Bangunan Heritage dengan Algoritma Convolutional Neural Network Winiarti, Sri; Saputro, Mochammad Yulianto Andi; Sunardi, Sunardi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 3 (2021): Juli 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i3.3058

Abstract

A heritage building is a building that has a distinctive style or tradition from a culture whose activities are carried out continuously until now and are used as a characteristic of that culture. The problems that occur in the community are the lack of knowledge to recognize the types of heritage buildings and the lack of digital documentation. Another problem that occurs in identifying heritage buildings is that there are similarities between heritage buildings and new buildings that imitate the architectural style of heritage buildings from ornaments. This can raise doubts in the information related to the original history of heritage buildings for the public or visitors. This study aims to apply the Convolutional Neural Network (CNN) to identify the types of heritage buildings. The benefits of this research can be found in the characteristics of a building based on ornaments so that it can be used to obtain information about the types of heritage buildings in Indonesia. A dataset of 7184 images of ornaments from heritage buildings were used which were taken directly at the Yogyakarta location, namely; Mataram Grand Mosque, Taqwa Wonokromo Mosque, Kalang House, Joglo KH Ahmad Dahlan and Ketandan. It is necessary to identify the heritage building because the object of the building can become extinct at any time, so to maintain it, documentation is needed as an effort to preserve culture and for education. Based on the evaluation of the performance of the tests carried out using the confusion matrix method from 391 ornamental images, the results obtained are 98% accuracy
Deep Learning on Game Addiction Detection Based on Electroencephalogram Pangistu, Lalu Arfi Maulana; Azhari, Ahmad
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 3 (2021): Juli 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i3.3061

Abstract

Playing games for too long can be addictive. Based on a recent study by Brand et al, adolescents are considered more vulnerable than adults to game addiction. The activity of playing games produces a wave in the brain, namely beta waves where the person is in a focused state. Brain wave activity can be measured and captured using an Electroencephalogram (EEG). Recording brain wave activity naturally requires a prominent and constant brain activity such as when concentrating while playing a game. This study aims to detect game addiction in late adolescence by applying Convolutional Neural Network (CNN). Recording of brain waves was carried out three times for each respondent with a stimulus to play three different games, namely games included in the easy, medium, and hard categories with a consecutive taking time of 10 minutes, 15 minutes, and 30 minutes. Data acquisition results are feature extraction using Fast Fourier Transform to get the average signal for each respondent. Based on the research conducted, obtained an accuracy of 86% with a loss of 0.2771 where the smaller the loss value, the better the CNN model built. The test results on the model produce an overall accuracy of 88% with misclassification in 1 data. The CNN model built is good enough for the detection of game addiction in late adolescence. 

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