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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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Analisis Forensik Aplikasi Michat Menggunakan Metode Digital Forensics Research Workshop
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3946

Abstract

The development of information technology has had various positive and negative effects. The positive impact that information technology can have is to make it easier for people to communicate with others in the world, and the negative impact is that society is out of control when using its applications. It is an attitude that causes various crimes in the world caused by cyberspace (cybercrime) One of the most widely used instant messaging applications is Michat. The MiChat app causes cybercrime, pornography, online gambling, fraud, cyberbullying and drug trafficking. Evidence research is conducted using one of the frameworks of the digital forensic research workshop. In this framework, forensic identification, preservation, collection, investigation, analysis, and presentation phases are designed to find evidence of digital crime. The forensic tools used to collect evidence are mobility forensic express pro, a DB browser for SQLite, and oxygen forensic detective. Results are presented in the form of reports and evidence, and text chat files, contacts, images, audio, video, and web caches are generated. Forensic tools have a 100% success rate in finding evidence. Comparing the functions of the three forensic tools, the mobility forensic express pro has a processing rate of 66.7%, DB browser for SQLite has 33.3%, and oxygen forensic detective has 83.3%. Digital evidence can be used as corroborating evidence in a trial
Perbandingan Metode Dempster-Shafer dan Certainty Factor Untuk Mendiagnosa Jenis Gangguan Bipolar Berbasis Website
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3596

Abstract

Bipolar is a mental illness that have very drastic emotional transformation. Bipolar disorders can interfere sufferer's activity if it has not been detected early. In general, the bipolar disorders sufferers difficult to control their circumstances or moods and it requires the proper treatment of the expert. An expert system to diagnose the kind of bipolar disorders built on this study using comparative methods of Depmster-Shafer and certainty factor based on website. The main expectation of this expert system application is to make it easier for the expert to diagnose bipolar disorders as well as to speed up the consultation process. In addition, this study aims to compare the two methods to determine the best method. The accuracy of this study is 93% of the certainty factor method while for the Dempster-Shafer method is 80% which can be summarized that certainty factor method is better than Dempster-Shafer in diagnose bipolar disorders because it has a higher degree of accuracy.
Analisis Sentimen Terhadap Implementasi Program Merdeka Belajar Kampus Merdeka Menggunakan Naïve Bayes, K-Nearest Neighboars Dan Decision Tree
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3554

Abstract

The development of technology are getting faster must be accompanied by the ability to adapt to changes from manual to digital, in the field of education. The Industrial internships, independent projects, student exchanges, community service projects, humanitarian initiatives, and other programs are part of the Merdeka Belajar - Kampus Merdeka program, which was launched by the Ministry of Education and Culture. The various of Merdeka Belajar -Kampus Merdeka program got a variety of responses from the public, including positive, negative, and neutral remarks posted on social media. The existence of these comments is able to create a growing sentiment among the general public and academics. Based on these problems, the researchers used twitter comments as a data source to conduct a sentiment analysis on the implementation of their Merdeka Belajar - Kampus Merdeka program. The data from Twitter will be categorized into positive, negative, and neutral classes using the Naïve Bayes method, K-Nearest Neighboars, and Decision Tree. There was a total of 475 data points divided into two groups: training data and testing data. The training data accounts for 80% of the entire data, while the remaining 20% is used for testing, with an accuracy of 99.22% for Naïve Bayes, 96.90% for K-Nearest Neighboars, and 37.21% for Decision.
Rancang Bangun Aplikasi Game Pembelajaran Augmented Reality Berbasis Android Dengan Metode Co-CreaARGBL
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3953

Abstract

In a time of pandemic like this, all sector activities, in urban and rural areas, become very difficult and activities are limited. The public is asked to maintain health protocols by using masks, washing hands, maintaining distance, and staying away from crowds. Many activities such as school, working, and worship and many other activities that can gather many people do online with the help of video conferencing support software. Institution for teaching and learning activities including those affected by the Coronavirus Disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The impact of activities carried out online and carried out almost every time in the world of learning is a decrease in participants’ enthusiasm due to boredom and monotonous impression without further interaction between participants and interactive media. So from these problems it is felt that there is a need for new media that can make online video conferencing learning activities not bored, which can make participants more active and not get bored easily during video conference. By using the Co-CreaARGBL method, making interactive augmented reality game-based learning media into a fun learning game with 3 main stages, that a Training, Interactive Design, and Classroom Evaluation, so that online learning becomes easy and fun by combining interactive multimedia elements that make participants interact more with fun learning media so they are not easily bored and seem monotonous.
Analisis Kepuasan Konsumen Terhadap Kualitas Pelayanan E-Commerce Jd.Id Menggunakan Metode E-Servqual
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3893

Abstract

This study aims to determine which dimensions have a significant effect on customer satisfaction and to find out which service dimensions are the main priority to be improved using the E-Servqual method. The E-servqual method is the method used to measure the quality of services provided online. The dimensions of E-servqual that will be used in this research are system availability, fulfillment, efficiency, privacy, compensation, responsiveness, and contact. Collecting data in this study by distributing questionnaires with the respondent's criteria, namely JD.ID E-Commerce users. The results of this study indicate that the variables of efficiency, system availability, compensation, and responsiveness have a significant effect on JD.ID consumer satisfaction while fulfillment, privacy, and contact variables have no significant effect on JD.ID consumer satisfaction
Klasifikasi Transaksi Penipuan Pada Kartu Kredit Menggunakan Metode Resampling Dan Pembelajaran Mesin Mukhlis Febriady; Samsuryadi Samsuryadi; Dian Palupi Rini
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3515

Abstract

The high number of credit card fraud causes a lot of losses for both users and credit service providers. Because the rate of credit card transactions is very fast, it is necessary to detect credit card fraud as early as possible. However, another challenge that is no less important is the amount of data that is imbalanced between valid and invalid transactions. One solution to the problem of data imbalance is to use a resampling method that can improve the quantity of data so that the accuracy results are good. In this study, three types of resampling methods were implemented, SMOTE, bootstrap, and jackknife. Furthermore, to validate the success of the resampling method, three types of machine learning methods were used. The machine learning methods are SVM, ANN, and random forest. From the test results, it was found that the combination of resampling SMOTE and random forest methods produced the best performance with values of accuracy, precision, recall and F1-score of 99.95%, 81.63%, 90.91% and 86.02%, respectively.
Klasifikasi Status Gizi Balita Menggunakan Naïve Bayes dan K-Nearest Neighbor Berbasis Web Rizky Setiawan; Agung Triayudi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3566

Abstract

One of the efforts in increasing the progress of a country is improving the quality of nutrition. Good balanced nutrition can increase the body's endurance, increase the level of intelligence and make a person develop normally. Infancy is a period of development and growth that requires more nutritional content than other age groups, making it the most vulnerable to nutritional disorders. Nutritional status under 5 years can be seen using the Anthroperti method. Calculations done manually make the process take a long time and errors often occur in entering data. Data mining can make decisions on the nutritional status of toddlers faster by looking at patterns in previous data. Naïve Bayes and K-Nearest Neigbor are one of the methods in classification. Naïve Bayes has the advantage of being able to achieve high accuracy values with minimal training data. Meanwhile, the K-Nearest Neighbor method has the advantage of being able to work optimally on data that has random errors (noise). Using 412 nutritional data for toddlers, the results obtained with Naïve Bayes getting an accuracy of 80.60%, while with K-Nearest Neighbor, an accuracy of 91.79% was obtained.
Perbandingan Metode WP dan SAW dalam Sistem Pendukung Keputusan untuk Menentukan Tingkat Keberhasilan Guru Mengajar di Tingkat SMK Harmayani Harmayani; Reza Arvania Harahap
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3571

Abstract

To improve student learning achievement, the learning process must take place well with the support of teachers who have competence, and the spirit of the teacher. In the current situation, schools do not have a system that can help assess the level of teaching success from a teacher to students at school, so that the principal and parents of students cannot know the success of teachers in teaching and guiding students. Realizing this problem, the writer is interested in building a decision support system by comparing 2 methods. Researchers will use the Weight Product and Simple Addictive Weighting methods. At this stage the results of the calculation of the Weight Product method will be compared with the results of the calculation of the Simple Additive Weighting method. Where the results of the comparison are that there are results that are not too significant but the results of the comparison are more dominant towards the SAW method. The accuracy of the SAW method reaches a value of 90% because there is a normalization process from the original alternative value. As for the WP method, it only uses a weighting of the existing alternatives.
Penerapan Elektronik Customer Relationship Management (E-CRM) Dalam Penjualan Roti Berbasis Web Anggi Mela Ariska; Novica Irawati; Ahmad Muhazir
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.4002

Abstract

UD Roti Ali is a home industry engaged in the production of bread making. The rapid development of technology in the world has had a major influence on the performance of bread making in all business fields, especially in the food manufacturing business. The business strategy of retaining old customers is more profitable than finding new customers, so it is necessary to maintain relationships with customers. UD Roti ali does not yet have a strategy to get new customers to find out information about products and prices. Currently UD Roti Ali does not yet have the right relationship with customers, one of which is the sales and ordering process is still done manually, where customers directly come to UD Roti Ali or call to place an order for products, then recording customer order data is still done by recording in the memorandum, so errors often occur in recording customer order data. This affects the bakery business, so UD Roti Ali needs an electronic system using the CRM method to build and manage the right relationship between UD Roti Ali and its customers. Therefore, UD Roti Ali needs a special strategy regarding proper customer service and product marketing in electronic form using a web-based CRM (E-CRM) method which is useful for making it easier for UD Roti Ali and customers, for UD Roti Ali it is easier to manage sales data and customer data, while for customers it is easier for customers to find out information about products, make it easier to make orders, payments, as well as the discount/promo and bonus features provided by UD Roti Ali to customers. So that this web-based system can help UD Roti Ali in maintaining customer loyalty.
Forecasting Stok Sparepart Sepeda Motor Menggunakan Metode Double Exponential Smoothing(DES) Gusrina Surianingsih; Havid Syafwan; Andy Sapta
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.4028

Abstract

PT. Anugerah Karya Abiwara II is a company engaged in the service sector in the workshop that serves its customers. The problem that occurs is the difficulty of determining the goods and the number of goods that must be provided every month in order to continue to meet customer needs. Stock or inventory is a number of goods provided by the company to meet consumer demand. Without adequate inventory, a business will not run smoothly. Therefore, to be more efficient, the authors designed a forecasting system with the Double Exponential Smoothing method using Visual Basic 2010 programming and MySQL database. The data predicted for the past 1 year are April 2021-March 2022 and the data will be forecasted in April. By calculating the Double Exponential Smoothing, the MAD value is 46.65, MSE 3975.26, RMSE 63.05, and the MAPE value is 21.48%, which means that the forecasting accuracy is almost 80%. So the algorithm with the DES method can be applied to the spare part stock forecasting process making it easier to determine the spare part stock in the next period.

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