cover
Contact Name
Mesran
Contact Email
mesran.skom.mkom@gmail.com
Phone
+6282161108110
Journal Mail Official
mib.stmikbd@gmail.com
Editorial Address
Jalan sisingamangaraja No 338 Medan, Indonesia
Location
Kota medan,
Sumatera utara
INDONESIA
JURNAL MEDIA INFORMATIKA BUDIDARMA
ISSN : 26145278     EISSN : 25488368     DOI : http://dx.doi.org/10.30865/mib.v3i1.1060
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)
Articles 52 Documents
Search results for , issue "Vol 5, No 3 (2021): Juli 2021" : 52 Documents clear
Penerapan Metode Forward Chaining dan Naïve Bayes Untuk Mendiagnosa Penyakit Tanaman Kakao Hilman Hadi; Ucuk Darusalam; Andrianingsih Andrianingsih
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.v5i3.3096

Abstract

Cocoa is one of the many plantation products in Indonesia which has considerable economic value, and has plantation land and its production each year has increased significantly. The lack of agricultural extension experts in providing direction, guidance, and information dissemination about the development of cocoa plant diseases faced by the cultivators of these plants can have an impact on the cultivators. The method used in this research is the forward chaining and naïve Bayes method. This system is expected to be useful for users in diagnosing cocoa diseases independently, of course easily and efficiently without having to require experts in their fields, with reference to the results and discussions carried out, the accuracy of this system has an accuracy value of about 95% in carrying out the diagnosis
Sistem Pembobotan Berdasarkan Teknik Analisis Korelasi Untuk Penerimaan Siswa Baru Menggunakan Metode SAW Nimas Dian Fitria; Aji Prasetya Wibawa
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.v5i3.3080

Abstract

New Student Admission (PSB) is an annual program held by the school to get students, according to the criteria desired by the school. One of alternatif method to determine the ranking of prospective new students is to use the SAW (Simple Additive Weighting) method. To reduce the subjectivity that arises in the use of the SAW method, a correlation analysis technique is used which is useful for knowing the level of correlation of each criterion on new student admissions. Based on the results of the research, it was found that the parents' income criteria had the highest weight (0.851), followed by math scores (0.845), English scores (0.831), physics scores (0.577), physical ability (0.539), and finally student interest (0.282). Meanwhile, the results based on ranking using the SAW method showed that students A3 (Alternatif 3) had the largest V1 value compared to other alternatifs, which was 3.54. So it can be concluded that A3 are students with the best final scores compared to other students.
Penerapan Metode ROC dan Weighted Aggregated Sum Product Assesment (WASPAS) dalam Penerimaan Asisten Perkebunan Rakhmi Khalida; Budianto Bangun; Mesran Mesran; Nona Oktari
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.v5i3.3092

Abstract

A plantation assistant is a person who is responsible for managing a plantation, in the selection of plantation assistants there are still obstacles in the selection, this is because many applicants enter and the assessment is still subjective. To overcome this problem, in this study, the author uses the Weighted Aggregated Sum Product Assessment (WSPAS) method to determine the acceptance of Plantation Assistants. The WASPAS method is considered in accordance with the selection of plantation assistants, because the WASPAS method will perform a ranking process based on attributes with different weights so that the results become more optimal. For maximum results, the author uses weighting by applying the Rank Order Centroid (ROC) method. The results of the study provide recommendations for the 8th alternative which has the highest value with a value of 0.970 to become a Plantation Assistant.
Perpaduan Algoritma Kriptografi Atbash dan Autokey Cipher dalam Mengamankan Data Muhammad Fadlan; Rosmini Rosmini; Haryansyah Haryansyah
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.v5i3.3019

Abstract

Data security is an important thing that must be done in the cyber era. The use of various kinds of digital technology in helping various human activities needs to be balanced with adequate data security. One of the ways that can be used in securing data is through cryptography. Atbash cipher is one of the cryptographic techniques used in securing data. However, this algorithm has a weakness because it only uses the process of reversing the position of the characters to be secured. This study proposes a cryptographic model that can maximize data security from the atbash cipher. The proposed model is a combination of the atbash cipher with the autokey cipher. The tests carried out on the proposed model have a 100% success rate, meaning that the encrypted message resulting from the proposed encryption process has been successfully restored to its original form through the proposed decryption process. The results of this study indicate that the atbash cipher cryptographic algorithm, combined with the autokey cipher algorithm can produce an encrypted message that is more difficult to crack.
Aplikasi Mobile Your Job MBTI (Myers-Briggs Indicator) Menggunakan Algoritma Fisher-Yates Shuffle Septi Andryana; Aris Gunaryati; Bimo Salasa Putra
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.v5i3.3095

Abstract

Work is something that everyone will do. This is because by working we will earn money that can make us able to fulfill our needs. But sometimes there are still quite a lot of people out there who don't even know what job is right for them. Therefore the author designed an application called Your Job based on Android, this application will provide suitable job recommendations based on the person's personality. In this study using the fisher-yates shuffle algorithm. Fisher-Yates shuffle algorithm can be applied to randomization of questions. The design of this application also uses the MBTI (Myers-Briggs Indicator) method to make it easier to determine a person's personality. After doing it to several people about this application. They gave a very good response, it is certain that the fisher-ystes shuffle algorithm runs well in randomizing the questions and using the MBTI method the accuracy level is almost 100% accurate.
Analisa Pola Penjualan Produk Sepeda Motor Yamaha Menggunakan Metode Algoritma Apriori Siti Nurlela; Lilyani Asri Utami
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.v5i3.3064

Abstract

The development of automotive industry in Indonesia can be classifiedas very rapid and annually increasing, causing highly competitive circumstances because many companies provide various types of motorcycle brands with quality and competitive prices. The company must create a marketing strategy pattern that can increase the level of sales efficiency of Yamaha motorcycle products. To overcome this problem, a strategy that can help increasing sales of motorcycle products is needed, in which by utilizing sales data owned by the company. Data mining can be used to process company sales data by looking for association rules with apriori algorithm on motorcycle product variables. From the results of the association rule analysis on sales data, with a minimum support of 30% and a minimum confidence of 75% can produce 3 rules with 3 products that are most in demand by consumers, namely the NEW MIOM3 CW, NEWAEROX155VVA and N-MAX, by knowing the most selling products, the company can add the most selling product supply and develop a marketing strategy to market the products with other products by examining the comparative advantage of the most sold products over the other products.
Penerapan Metode Simple Additivie Weighting Untuk Mengefektifkan Penilaian Kinerja Karyawan Neni Mulyani; Jeperson Hutahaean
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.v5i3.3103

Abstract

In this study, the application of the Simple Additive Weighting (SAW) method is needed to generate preference values for 16 employee data which is used as an alternative employee performance appraisal. The application of the SAW method in this case also aims to improve the results of decisions made by managers. So that in one period of performance appraisal of employees at the end of the year the manager can make decisions on employees who have very good performance (0.80 – 1.00) to employees who have poor performance. The results of the preference value from the calculation using the SAW method will be made in the form of an assessment range, so that based on the value of the range the manager can provide an employee performance assessment.
Metode Seleksi Fitur Untuk Klasifikasi Sentimen Menggunakan Algoritma Naive Bayes: Sebuah Literature Review Fitria Septianingrum; Agung Susilo Yuda Irawan
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.v5i3.2983

Abstract

In the era of the industrial revolution 4.0 as it is today, where the internet is a necessity for people to live their daily lives. The high intensity of internet use in the community, it causes the distribution of information in it to spread widely and quickly. The rapid distribution of information on the internet is also in line with the growing growth of digital data, so that the public opinions contained therein become important things. Because, from this digital data, it can be processed with sentiment analysis in order to obtain useful information about issues that are developing in the community or to find out public opinion on a company's product. The number of studies related to sentiment analysis that applies the Naive Bayes algorithm to solve the problem, so researchers are interested in conducting research on the use of feature selection for the algorithm. Therefore, this research was conducted to determine what feature selection is the most optimal when combined with the Naive Bayes algorithm using the Systematic Literature Review (SLR) research method. The results of this study concluded that the most optimal feature selection method when combined with the Naive Bayes algorithm is the Particle Swarm Optimization (PSO) method with an average accuracy value of 89.08%.
Pengembangan Learning Management System (LMS) dengan Menerapkan Video Based Learning dan Gamification Dalam Meningkatkan Motivasi dan Keterlibatan Mahasiswa Paradise Paradise; Merlinda Wibowo
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.v5i3.3087

Abstract

The learning model used greatly affects the learning process in the Covid-19 pandemic era. The online learning that has been passed in this one year has caused boredom. The learning process is too monotonous, the teacher's intonation is less varied, and not easy to interact directly with friends and teachers. Therefore, to achieve an effective and maximum learning process, the researcher proposes using video-based learning and gamification methods to increase deeper understanding of the material, motivation in learning, and student involvement in the learning process through the Learning Management System (LMS). The material presented will be transformed into more interactive and interesting videos such as simple animated videos, tutorial videos, podcast videos, and others. This research aims to provide positive benefits for students to be more active in discussing and collaborating and enthusiastic in doing all learning activities. The test to measure the level of motivation and involvement can be carried out in three stages, namely with pre-test and post-test, T-test and analytical data from student access to the LMS according to the indicators involved in this study such as video completion, total video, total comments, total badges, and completion of the game level. This study result indicates a positive influence from the application of video-based learning and gamification methods on LMS to increase student motivation and engagement.
Penerapan Metode Data Mining Pada Point of Sale Berbasis Web Menggunakan Algoritma Apriori Adam Firmansyah; M Iwan Wahyudin; Ben Rahman
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.v5i3.3085

Abstract

To be able to understand which products have been purchased by customers, it is done by describing the habits when customers buy. Use association rules to detect items purchased at the same time. This study uses an a priori algorithm to determine the association rules when buying goods. The results of the study and analyzing the data obtained a statement that using the a priori algorithm to select the combined itemset using a minimum support of 25% and a minimum confidence of 100%, found the association rule, namely, if the customer buys at the same time. Buying goods has the highest value of support and trust. Likewise with the support value of 25%, the confidence value is 100%. In this way, if a customer buys an item, the probability that the customer buys the item is 100%