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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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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.
Model Sistem Penunjang Keputusan Untuk Menentukan Jurusan Calon Siswa Baru Menggunakan Metode Profile Matching Pada SMK XYZ Agus Umar Hamdani; Savira Aprilya
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.v5i1.2274

Abstract

SMK XYZ is a Vocational School based on technology and located in South Jakarta. This school has several majors, namely Software Engineering (RPL), Network Computer Engineering (TKJ) and Multimedia (MM). Every new school year, new students of new students who register increases. However, there are problems encountered in the process of selecting student majors, namely inaccurate decision making, there is no ranking, decision making has not used the method and is still using Microsoft Excel, so it requires quite a long time in determining student majors. The purpose of this study is to create a decision support system that is expected to help in determining the right majors for new students in SMK XYZ in accordance with the criteria set by SMK XYZ. This research resulted in a decision support system using the Profile Matching Method as a method for determining alternative final values. Reports produced by this system are value reports that contain the values calculated by students' grades. This decision support system was created using MySQL as a database and Microsoft Visual Studio 2008 as a system creation tool. With this support system, it can help the student in processing data and decision making in order to determine student majors.
Deteksi Kelayuan Pada Bunga Mawar dengan Metode Transformasi Ruang Warna Hue Saturation Intensity (HSI) dan Hue Saturation Value (HSV) Dede Wandi; Fauziah Fauziah; Nur Hayati
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.v5i1.2562

Abstract

The rose is a plant of the genus Rosa. The rose consists of more than 100 species with various colors. In selecting and sorting roses, roses are often found that are still fresh and wilted. Based on the problems faced in roses, a system design is carried out that can detect the wilting condition of roses. By applying the HSI and HSV methods to image processing applications, it is hoped that it can help in choosing the condition of roses. With research methods through observation and literature study. To see the conditions, roses can be divided into wilted flowers and fresh flowers. In its implementation and classification, by detecting the color of roses in the HSI and HSV color space, from a total of 230 images of red and white roses that tested 200 images using HSI and HSV, the value of Range was obtained on the HSI, H = 0.240634 - 0.5, S = 0.781818 - 1, and I = 0.477124 - 1 in the Fresh category, while the HSI Wilt Category, H = 0.170495 - 0.5, S = 0.40239 - 1, I = 0.562092 - 1. and also obtained the value of Range with HSV with Fresh category H = 0.240634 - 0.5, S = 0 - 0.988235, V = 0 - 0.988235, and Wilt category H = 0.170495-0.5, S = 0 - 0.996078, V = 0 - 0.996078. With an accuracy value of the HSI and HSV of 86.9%. Therefore, it can be concluded that the detection of wilting in roses using the HSI and HSV methods is the fastest in the process using the HSI method because it reads all the min-max values.
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
Perbandingan Metode AHP dan Metode SAW Dalam Kelayakan Pemberian Kredit Motor Sarwindah Sarwindah; Marini Marini; Syarah Syarah
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.v5i1.2466

Abstract

In this study, two methods were used to determine the feasibility of giving motorbike credit, namely the Analytical Hierarchy Process (AHP) and the Simple Additive Weighting (SAW) method to determine the weight of the accuracy value in the feasibility of granting motor loans. Results based on the Hierarchical Weighted Factor Matrix with AHP for all criteria normalized hierarchical weighting for all criteria with the elements in each column divided by the total number in the respective column, then you will get the normalized relative weight. The eigenvector value generated from the average relative weight value for each row shows that the most important criterion for customers who wish to apply for credit. Income with a weight of 0.649 or 64.9%, then followed by a family card with a weight of 0.088 or 8.8%, and domicile is 0.21 or 21%. Whereas the results based on ranking using the SAW method for all Kritera whose weighting is normalized is that the V1 ranking is the first rank because it has a value greater than the other values of 1.03 where V1 is the preference value of alternative A1, so that A1 in this case is Yogi Danuarta who be the best alternative or selected prospective customers to get motorbike loans.
Pengaruh N-Gram terhadap Klasifikasi Buku menggunakan Ekstraksi dan Seleksi Fitur pada Multinomial Naïve Bayes Esti Mulyani; Fachrul Pralienka Bani Muhamad; Kurnia Adi Cahyanto
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.v5i1.2672

Abstract

Libraries have the main task in the processing of library materials by classifying books according to certain ways. Dewey Decimal Classification (DDC) is the method most commonly used in the world to determine book classification (labeling) in libraries. The advantages of this DDC method are universal and more systematic. However, this method is less efficient considering the large number of books that must be classified in a library, as well as labeling that must follow label updates on the DDC. An automatic classification system will be the perfect solution to this problem. Automatic classification can be done by applying the text mining method. In this study, searching for words in the book title was carried out with N-Gram (Unigram, Bigram, Trigram) as a feature generation. The features that have been raised are then selected for features. The process of book title classification is carried out using the Naïve Bayes Multinomial algorithm. This study examines the effect of Unigram, Bigram, Trigram on the classification of book titles using the feature extraction and selection feature on Multinomial Naïve Bayes algorithm. The test results show Unigram has the highest accuracy value of 74.4%.
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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