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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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Partner Sentiment Analysis for Telkom University on Twitter Social Media Using Decision Tree (CART) Algorithm Sean Akbar Ryanto; Donni Richasdy; Widi Astuti
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4533

Abstract

Sentiment analysis is an analysis in terms of opinion and meaning in the form of writing. Sentiment analysis is very useful for expressing opinions from any individual or group to improve branding.  Branding is a process to promote and improve the name of a brand or brands to attract the attention of consumers to be interested in trying the services of a company that runs in academic terms such as Telkom University. However, this requires cooperation between other associations as partners so that the branding carried out can be effective. One form of cooperation is by providing opinions about Telkom University so that consumers are more familiar with Telkom University on Twitter social media which is the largest social media used by many people because it can provide any opinion freely. Therefore, this study aims to analyze the sentiment submitted by partners for Telkom University on Twitter which is the main factor for promoting themselves to consumers. The process carried out is to take all tweets about Telkom University submitted by partners and then carry out the TF-IDF weighting process and classified using the Decision Tree CART algorithm based on positive, negative, and neutral sentiment categories. The best results obtained by the Decision Tree model of the CART algorithm are the Accuracy value of 86.73%, Precision of 87.06%, Recall of 87.55%, and F1-Score of 86.52%.
BERT Implementation on News Sentiment Analysis and Analysis Benefits on Branding Muhammad Faris Abdussalam; Donni Richasdy; Moch Arif Bijaksana
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4579

Abstract

The rapid development of information makes data processing easy and fast, especially in the business world, so many business brands have used the internet as a marketing medium for their operations. Now the business does not only depend on its operations; now, the opinion of the public media, especially on the news, has become an essential spotlight in today's business, especially against negative opinions that indirectly impact the image and product branding of the business, we need the proper means to help identifying and analyzing this kind of news. This study aims to identify and analyze sentiment with negative and positive indications on news titles from one of the sources of an Indonesian online news portal using the Bidirectional Representations from Transformers (BERT) sentiment analysis method, with the measurement of the confusion matrix metrics to measure and identify which headlines contains negative and positive indications. The sentiment analysis system offers identification and categorization with ease and immediately provide good results on identifying news. The results of this study, the sentiment model achieves an accuracy rate of 93% in identifying negative and positive news and F1-Score on negative identification rate of 92% and positive identification rate of 93%. The sentiment analysis system was built as effort to help analyzing against positive news indications or awful news as analysis benefits carried out to identifying alarming news indications towards branding.
Klasterisasi Konsentrasi Keahlian Siswa SMK Berdasarkan Kurikulum Merdeka Firman Sukmayadi; Alamsyah Firdaus; Christina Juliane
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4848

Abstract

The process of determining the concentration of expertise carried out at the YPC Tasikmalaya Vocational School has shortcomings such as making decisions based on the wishes of students without paying attention to academic grades at the previous level of education. So that there are some students who feel it is not right in choosing the concentration of expertise, resulting in a lack of competence possessed by students with the concentration of expertise selected. The choice of concentration of expertise is the right of every student, but if it is wrong it can cause a decrease in learning motivation and low learning achievement. This problem can be solved by using clustering method with K-Means algorithm. This study aims to classify students' interests in choosing a concentration of expertise at YPC Tasikmalaya Vocational School based on the Merdeka Curriculum. The results showed that the grouping of students' interests in choosing the concentration of expertise was formed into 4 clusters. The cluster with the most members is cluster 0, namely students who have an average score of 79 Mathematics, then Indonesian and English 83. Furthermore, the cluster with the least number of members is cluster 2, namely students who have an average score of 78 Mathematics and English, then Indonesian 79.
Analisis Sentimen Komentar Pengunjung Terhadap Tempat Wisata Danau Weekuri Menggunakan Metode Naive Bayes Classifier Dan K-Nearest Neighbor Gergorius Kopong Pati; Elfira Umar
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4635

Abstract

Trip Advisor is the largest travel site in the world that helps tourists in planning and booking travel. One of the recommended attractions on the TripAdvisor website is the Crystal Cave, which is located in Kupang City. Human habit in posting tourist attractions visited is a common thing to present human responses to one of the tourist attractions. Usually there are certain parties who want to know the sentiments and responses to one of the tourist attractions. Therefore, this study will conduct a sentiment analysis of one of the tourist attractions in the city of Kupang is the Crystal Cave. The analysis was carried out by classifying people's sentiments. The calcification method used in this study is Navie Bayes Classifier and K-Nearest Neighbor. From these two methods a comparison will be done to find out the level of accuracy. Sentiment classification consists of positive and negative. The purpose of this study is to provide information about the quality of one of the tourist attractions in the city of Kupang by using sentiment from visitors and determine the level of accuracy of the comparison of the two methods tested. The test results will be tested on the Rapidminer tool showing the level of accuracy of testing both methods.
Implementasi Algoritma Multiplicative Congruential Random Number Generator Pada Aplikasi Seleksi Mojang Jajaka Tito Sugiharto; Lutfi Slamet Riyadi; Heru Budianto; Dede Irawan
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4619

Abstract

Mojang Jajaka (MOKA) is one of icons of tourism ambassadors who come from most districts/cities in West Java. The selection of tourism ambassadors in Kuningan was organized by the Department of Youth, Sports and Tourism (DISPORAPAR) of Kuningan, and the Mojang Jajaka Association of Kuningan. One of the series of activities carried out is participant registration and written test selection. Currently the registration process and the written test selection are still carried out conventionally by collecting hardcopy files and writing tests using a sheet of paper. This is considered less effective and efficient because using paper often causes problems, namely tucked, damaged, and easily lost. In the written test activities, cheating often occurs when filling out answers. This study aims to apply the Multiplicative Congruential Random Number Generator Algorithm in randomizing the questions on the MOKA selection test. The selection process begins with participants registering on the application. Then the participant logs in and after that the admin sees the participant data and then verifies the participant data. After that the admin will do question management, where the admin will input 30 questions. Then the participants will carry out the exam process. The Multiplicative Congruential Random Number Generator algorithm will work to randomize the questions from 30 questions and 25 questions will be issued. This application is made using the Java programming language, PHP, Javascript and MySQL database. This study uses the RUP (Rational Unified Process) methodology which consists of 4 stages, namely Inception, Elaboration, Construction, and Transition. This study results a MOKA Selection Application that can simplify the registration process and written test selection for both participants and the Mojang Jajaka selection committee, Kuningan.
Rancangan Aplikasi Autentikasi Surat Digital dengan Metode One Time Password SHA-512 Berbasis Android Salwa Kamila; Lindawati Lindawati; Mohammad Fadhli
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4469

Abstract

Some administrative procedures in many institutes are still carried out conventionally, which is deemed less efficient and takes much time. On the other hand, communication with other parties requires a process of exchanging information, so a system is needed to confirm the validity of the information. Therefore, a digital letter system that can prove the validity of the information gained through the digital media right from the party concerned is developing. This can be overcome using the authentication method. Adding One Time Password (OTP) as an authentication method that employs one temporary password key can be the solution. This study uses the One Time Password (OTP) method as a validation system and the SHA-512 algorithm as an OTP code generator to generate random codes. This system leverages android technology on mobile to ease access to the correspondence administration system to make it easier to visit with features that prioritize information and access speed. This application is implemented at the State Polytechnic of Sriwijaya to improve the administrative process to run more effectively. The black box testing revealed that all available menus and features were appropriate, and the application already had a system that functions according to user needs. Moreover, in the One Time Password generation test with the SHA-512 algorithm, it was determined that the average response time for generating the OTP code was 4.4 seconds in 15 trials, which can be considered fairly accurate.
Comparative Analysis Performance of Naïve Bayes and K-NN Using Confusion Matrix and AUC To Predict Insurance Fraud Gandung Triyono; Dermawan Ginting
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4836

Abstract

Based on claim submission data from year 2019 to 2021 can be seen that the percentage of claims in one province is much higher than other provinces. During that period, the percentage of claims in that province reached 22% while the highest percentage in other provinces was only 6%. It is suspected that there has been a claim fraud in the province. The fraud allegedly started when customer submits a policy issuance for the elderly insured with a low sum insured so that the premium is also low. The insured's health condition at that time may not be good but it is not explained in the insurance application letter. To increase the sum insured, the policy is usually added with additional coverage. Fraud claim creates big loss for insurance company since the company has to pay the claim that they should not pay. Insurance company need to have a mechanism to avoid the fraud claim. From this research, it is expected to find the best methodology to be able to predict the potential of insurance claim fraud early when customers apply for policy issuance so that additional checks can be carried out for suspected submissions. The initial data available for this research is 14,778 claim records with attributes are : the date of claim submission, policy effective date, sum assured, type of claim, cause of claim, province and fraud. In order to get the best methodology on the accuracy and performance aspect to fulfill the expectation, two methodologies (Naïve Bayes and K-NN) are compared. Both Naive Bayes and K-NN methods are used with a comparison of training data and testing data is 80:20. Several combinations were performed for each of these methods. By using Confusion Matrix and AUC to measure the accuracy and performance of the two methods, it can be concluded that the best one is Naive Bayes with accuracy is 90% and AUC is 0.761. The attributes used are province, sum assured, additional coverage and the insured is the policy holder.
Klasterisasi Perguruan Tinggi Swasta di Madura Berdasarkan Kinerja Sumber Daya Manusia dan Mahasiswa Menggunakan Metode K-Means Clustering Yuli Sasmita; Muhsi Muhsi; Miftahul Walid
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4431

Abstract

The number of private universities in Indonesia in 2020 is 3,044 private universities, in East Java 328 private universities and in Madura 30 private universities. The number of private universities in Indonesia causes intense competition. Colleges should strive to maintain and improve performance in order to ensure their activities. Therefore, it is necessary to do or group private universities based on the performance of human resources and students to encourage these universities to improve their performance. The grouping of private universities is carried out using the k-clustering method which groups data into several clusters based on data groups which are. The results of this study, the grouping of private universities in Madura into 3 clusters, namely: Cluster 1 there are 4 private universities, Cluster 2 there are 7 private universities, and Cluster 3 there are 19 private universities.
Penerapan Metode Multi-Objective Optimization on The Basic of Ratio Analysis (MOORA) Dalam Seleksi Siswa Unggulan Sekolah Fifto Nugroho; Harmayani Harmayani; Mesran Mesran; Rabli Hari Mulia; Eko Maruli Tua Situmorang; Ricard Ricardo
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4856

Abstract

This study aims to determine the superior students in a school based on the achievements of the students. To solve this problem, the writer uses the Multi-Objective Optimization on The Basic of Ratio Analysis (MOORA) method. MOORA is a relatively simple method that can rank a number of alternatives by subtracting the previously weighted benefit and cost criteria. The results showed that the highest ranking value was found in alternative A1 with a result of 0.1906 and followed by alternative A2 with a result of 0.1901.
Question Answering using Ontology for Sumedang Larang History with Support Vector Machine Based on Telegram Bot Erbina Selvia Br Perangin-Angin; Z. K. A Baizal; Donni Richasdy
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4574

Abstract

Technological developments affect many aspects, one of which is historical education. History lessons can shape students' personalities and encourage an interest in historical knowledge. There are many stories from Indonesian history, one of which is the Sumedang Larang Kingdom. The Sumedang Larang Kingdom is one of the Islamic kingdoms in Pasundan. However, not many people know about this kingdom. The millennial generation is technologically advanced, so they can take advantage of technological advances to quickly introduce the history of Sumedang Larang. One of them utilizes the telegram bot using the Application Programming Interface (API), which can connect the system to the telegram platform. In addition, this technology can be used as a history learning attraction using the question answering system (QA). Our research aims to build a QA system that can introduce the history of Sumedang Larang to the millennial generation. Because this system uses ontology knowledge with concepts related to the Sumedang Larang domain, it can focus on the history of Sumedang Larang. Applying the support vector machine (SVM) algorithm to process classification text can make it easier to search for text categories. The test results show the performance of the SVM method with a test size parameter of 0.5, such as 74% and 78%. The performance test results are accuracy scores in the subject category and object classification.

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