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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 47 Documents
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Search results for , issue "Vol 4, No 4 (2020): Oktober 2020" : 47 Documents clear
Pengujian Konfigurasi Otomatis Penambahan Gateway Pada Virtual Router Menggunakan Aplikasi Otomatisasi Jaringan Berbasis Web Elin Sylvania Ginting; Suroso Suroso; Irawan Hadi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2485

Abstract

Current router configuration is still done conventionally, which means that to configure routers in a complex network, a network administrator configures the routers one by one. This is very inefficient, because if the router you want to configure is done in hundreds or thousands of routers, then the time needed by a network administrator is very long. Therefore, automation is needed. This study creates a web-based network automation application with python, the paramiko library which functions as a bridge between the server and network devices using the SSH (Secure Shell) protocol, and the django framework that can configure IP Gateway automatically. Network automation is carried out in a simulation using the GNS3 application on a previously designed network topology. The network automation application testing method used is the black-box testing method. The output of this research is a website consisting of a user page and an admin page that can configure virtual routers automatically.
Model Pengenalan Suara Teks Bebas Menggunakan Algoritma Support Vector Machine Muhammad Bobbi Kurniawan Nasution; Kusmanto Kusmanto; Sudi Suryadi; Ronal Watrianthos
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2436

Abstract

Voice authentication can be done because there are physical differences in the voice production organs of each person. The user's spoken sound pattern can be used as a voice command as desired. Some features such as accents, intonation, and the way pronunciation produce different patterns. For identification verification, voice data is divided into two groups: voice with defined text and voice with free text. Sounds resulting from the pronunciation of a particular word can be changed from analog to digital form. This change process will result in representation in vector form. One technique in voice recognition classification is the Support Vector Machine (SVM). The study aims to develop SVM algorithms to create free text-based speech patterns, recognition models. The sound pattern classification process uses three kernels for the data set so that the comparison results will be more accurate. The highest accuracy in the linear kernel is found in the 4th loop in the third fold with an accuracy rate of 94.40%. While in the polynomial kernel the highest accuracy at the 6th iteration of the second fold with an accuracy of 96.80%. The highest accuracy rate is found in the RBF kernel on the 8th loop of the third fold with 98.20% accuracy. These test results prove the RBF kernel has the best level of accuracy in free text-based speech recognition.
Penerapan Model Choo Sense Making Untuk Meningkatkan Sharing Knowledge Pada Laboratorium Media Komunikasi Devit Setiono
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2360

Abstract

The Media Communication Laboratory of Budi Luhur University has an assignment to support the learning of students of the Faculty of Communication Sciences (FIKOM). In its development can not be separated from the role of Information technology. The slow and static application of knowledge management makes many knowledge walkouts, plus the change of assistants every year make knowledge and experience not yet documented so that tacit knowledge is still stored in each assistant, causing dependence on senior assistants to solve a problem. The purpose of this study was to determine whether the use of the Choo Sense Making model is appropriate and can be applied to the Media Communication Laboratory. Researchers develop a knowledge management system model that is in accordance with the conditions of the Communication Media Laboratory using the framework of the Tiwana model, the choo sense making model for knowledge formation and integrated with the SECI model at the knowledge creation stage. The results of this study are the design of a knowledge management system model with a choo sense making model to share knowledge through an application through three processes of knowledge formation namely Sense Making, Knowledge Creating, and Decision Making. The results of testing the system using the path analysis model of the Technology Aceptence Model with 5 variables, namely, Perception of Usability, Perceived Ease of Use, Actual Use of the System, Attitude Toward Using and Behavioral Intention to Use shows results above 71,90%, which means the application of knowledge management system model choo sense making can be applied to the Communication Media Laborator
Evaluasi Pembangunan Sistem Pakar Penyakit Tanaman Sawit dengan Metode Deep Neural Network (DNN) Errissya Rasywir; Rudolf Sinaga; Yovi Pratama
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2518

Abstract

The limited knowledge of oil palm farmers on oil palm pests and diseases is related to oil palm productivity. Jambi Province is one of the largest oil palm producers on the island of Sumatra. Usually, to find out the types of pests and diseases in oil palm in the field, farmers need knowledge like that of experts about oil palm diseases. However, the limitation of facilities and capabilities becomes an obstacle. This study offers an expert system to analyze oil palm disease using deep learning. This method is deep learning with excellent accuracy. Various recent studies using DNN state that the classification accuracy results are very good. The data used for the expert system using the DNN algorithm comes from oil palm diagnostic data from the Jambi Provincial Plantation Office. After the oil palm disease diagnosis data is trained, the training data model will be stored for the oil palm disease diagnosis testing process. With a total of 11 classes (Leaf Spot Disease, Anthrox Leaf Blight, Leaf Rust Disease, Leaf Canopy Disease, Bud Rot Disease, Root Rot Disease, Fire Caterpillar or Setora Nitens, Red Mites or Oligonychus, Horn Beetle or Orycte rhinoceros, Bunch Borer Fruits and Nematodes Rhadinaphelenchus Cocophilus), with test variables including the number of classes, TP, TN, FP, FN, precision, recall, F1-score, accuracy, and Missclassificaion rate. The highest accuracy value was 0.88, while the lowest value was 0.83 and the average accuracy was 0.86. This shows that the results of expert system diagnosis on oil palm disease data with DNN are quite good.
Reduksi Atribut Pada Dataset Penyakit Jantung dan Klasifikasi Menggunakan Algoritma C5.0 Utomo, Dito Putro; Sirait, Pahala; Yunis, Roni
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2355

Abstract

Coronary heart disease, commonly referred to as cardiovascular, heart disease is a disease with a high mortality rate. Thus diagnosis is very important and is an important area of medical research. In the diagnostic process, the most frequently encountered problems are time in making decisions and the lack of accuracy in the classification process. Attributes are important in making decisions on heart disease so it is necessary to know the main attributes of heart disease. Often different results are obtained in the diagnostic process due to the many attributes used in decision making. So it is necessary to do a reduction process in the attributes of heart disease. Principal Component Analysis (PCA) method can be used for data reduction with large dimensions and ranking the attributes to be reduced. The classification process can be done using the C5.0 Algorithm and getting a level of accuracy in the classification process. The results obtained in this study reduce the 12 attributes of the heart disease dataset and classify them with a combination of attributes after the reduction process is carried out. The results obtained with the highest level of accuracy when classifying with 11 attribute combinations where there is 1 attribute that is reduced, the accuracy rate obtained is 89.11%.
Perancangan E-Katalog Promosi STMIK Triguna Dharma Dengan Metode User Centered Design Untuk Meningkatkan Layanan Kualitas Promosi Berbasis Web dan Mobile Azlan, Azlan; Prayudha, Jaka
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2136

Abstract

Promotion is an activity to spread information with the aim that the information attracts the recipient's attention. The promotion strategy undertaken by STMIK Triguna Dhamra is to visit five schools in one day where one school spends an hour doing promotions, promotions are carried out for three months in the North Sumatra region. Promotion is done by asking permission from the school to make a presentation in class, the presentation is done using the brochure media that has been provided and distributed to students. Given the media used is a brochure which is a promotional media made of paper so that the quality of promotional services is mediocre or less attractive. To improve the quality of promotional services, a promotional e-catalog was designed. E-catalog is a digital version of the catalog and the catalog is a kind of brochure that contains product information and is equipped with images. The STMIK Triguna Dharma promotion e-catalog which is designed based on web and mobile, in addition to improving the quality of promotional services as well as saving costs of promotion, saving time on promotion and supporting government programs to face the industrial revolution 4.0, namely digital-based. Web-based and mobile e-catalogs are designed using the User Centered Design method where the e-catalog design is based on the needs of the promotion team and the order of research methods using the Research and Development method which is designing e-catalog products and testing the effectiveness
Sistem Pakar Diagnosis Penyakit Tanaman Karet dengan Metode Fuzzy Mamdani Berbasis Web Hendrawan Hendrawan; Abdul Harris; Errissya Rasywir; Yovi Pratama
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2521

Abstract

Rubber plants can be attacked by various diseases originating from fungi, pests, animals and even cancer cells. A method that is able to diagnose rubber disease is needed so that it is hoped that it can help farmers detect symptoms early so that the productivity of rubber plantations can increase. This study developed an analysis of the results of the diagnosis of rubber plant disease using the Mamdany Fuzzy method. The choice of this method departs from the fuzzy mamdany research which states that the fuzzy mamdany method is able to resemble the workings of the human brain intuitively. With the implementation of the Expert System for Diagnosis of Disease in Rubber Plants with the Fuzzy Mamdani Algorithm, the work of diagnosing rubber plant diseases can be done more automatically. With 33 sympthon parameter data for rubber plant disease symptoms and 14 classes of rubber disease diagnosis tested using the Mamdany Fuzzy algorithm, the results obtained an accuracy of 81.74%, a value of 5-cross validation of 80.93% and a value of 10-cross validation of 82.30%. This shows that the application of the fuzzy mamdani algorithm produces good accuracy in diagnosing rubber plants.
Optimasi Klasifikasi Bayesian Network Melalui Reduksi Attribute Menggunakan Metode Principal Component Analysis Surizar Rahmi; Pahala Sirait; Erwin Setiawan Panjaitan
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2370

Abstract

Dimensionality reduction is a hot topic being discussed in its development has been carried out in various fields of research one of which is machine learning by reducing can reduce the capacity of dimensions without reducing (eliminating) information contained in the data. Principal Component Analysis is one of the proven reduction techniques capable of reducing data capacity without significantly eliminating the information contained in the dataset. In this research attribute reduction using principal component analysis using a dataset of factors affecting employee absence was taken from the University of California repository at Irvine (UCI). Combination with Bayesian Network to classify data as a comparison between before and after attribute reduction. This can be seen in the initial results before the reduction with an accuracy of 100% and after the fifth attribute reduction there is a decrease in accuracy by 89,7%
Diagnosa Tingkat Depresi Mahasiswa Akhir Terhadap Penelitian Ilmiah Menggunakan Algoritma K-Nearest Neighbor Bernadus Gunawan Sudarsono; Sri Poedji Lestari
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2448

Abstract

The achievement of a success is considered not an easy thing, such as reversing between a leaf and another, success must be achieved with sincerity, even risking everything that is in a person to achieve success and a lot of success can be obtained through higher education, higher education is a way Reaching goals, companies, industry and government prioritize higher education as trusted human resources, many final students experience depression due to many demands and several factors, excessive levels of depression result in all efforts and efforts will cause all chaos and can make someone making the wrong decision to result in death, a system is needed in diagnosing the level of depression in final students to reduce the risk of continuous depression using the k-Nearest Neighbor algorithm approach, with this algorithm it is il in the form of a decision on the level of depression experienced by final students
Sistem Pendukung Keputusan dalam Menentukan Judul Skripsi Mahasiswa dengan Metode WASPAS, COPRAS dan EDAS berdasarkan Penilaian Dosen Pristiwati Fitriani; Tomy Satria Alasi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2431

Abstract

The title of the thesis is the student's scientific exposure. Students are confused about determining the title of the thesis even though the rejected title can be used as learning by other students from the title that has been accepted or has not submitted the title, they do not understand the rules and assessments of all titles when submitted. In addition to this, lecturers related to fields who have researched or studied at a particular Faculty have not been utilized. One student proposes that there are three or more titles, this is very difficult if it is not explained in detail, then if it is rejected, they must submit it again until it is accepted so that it is ineffective and efficient that it must be overcome. This research produces a new technique in submitting a thesis title that is assessed automatically based on the lecturer's assessment, all resolved with a decision support system. Submission of a long thesis title is caused by many factors. Thesis title assessment must be understood by all groups. By adjusting the title with the vision and mission according to the study program. A decision support system is a technique for presenting a decision. In this case the settlement was done by using the WASPAS, COPRAS and EDAS methods. The WASPAS method is to use the compensation method, the attributes are independent, the qualitative attributes are converted into quantitative attributes. The COPRAS method is a normalized decision matrix, a weighted normalized decision matrix, a maximizing and minimizing index, a relative significance value. Then the EDAS method is very practical in conditions with contradictory attributes, and the best alternative is selected by calculating the distance from each alternative from the optimal value. Three methods of filtering and determining the title of the thesis. The criteria for receiving the thesis title are based on the feasibility assessment, renewal, conformity with the vision and mission and academic values associated with the submission of the thesis title. The assessment is also integrated with each lecturer who teaches subjects related to the thesis title. The research method in determining the title of the thesis with quantitative methods. Examining every relationship starting from students, lecturers, thesis titles, criteria related to determining thesis titles. Test all related theories in a measured manner and take test results based on hypotheses. This research produces a complex thesis title determination information system software. comparing the three thesis titles by one of the students, each thesis title has criteria, namely research renewal, vision suitability, mission suitability, student self-grade scores and similarities in existing research, from the results based on the three processed methods obtained " Algoritma Boyer Moore Untuk Penyaringan Pesan" Becomes an accepted title submission.

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