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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 78 Documents
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Search results for , issue "Vol 6, No 4 (2022): Oktober 2022" : 78 Documents clear
Penerapan k-Means Clustering Berdasarkan Analisis RFM Terhadap Segmentasi Pembeli untuk Meningkatkan Strategi CRM Tigar Cahyo Wiguno; Yessica Nataliani
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.v6i4.4472

Abstract

An industry requires a good strategy in running its business. Saga Bako is a small industry that sells various types of tobacco and its equipment. However, Saga Bako has not yet implemented a Customer Relationship Management (CRM) strategy in its service to buyers. It is necessary to segment customers to find out less profitable buyers and buyers who provide large profits. The use of data mining also contributes when segmenting customers through the use of purchase data. The methodology applied in this research is CRISP-DM with purchase data at Saga Bako from January to March 2022. The k-means algorithm is applied in the formation of clusters based on the Recency, Frequency, Monetary (RFM) model, with the help of Weka 3.8.5 tools. The Elbow method is used to determine the best number of clusters (k). The results obtained are from 47 buyers with 663 transaction data divided into three clusters, 26 low potential buyers, ten medium potential buyers, and 11 high potential buyers.
Prediction of Rainfall Classification of Java Island with ANN-Feature Expansion and Ordinary Kriging Irfani Adri Maulana; Sri Suryani Prasetiyowati; Yuliant Sibaroni
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.v6i4.4556

Abstract

Precipitation is one of the most important climatic variables in many aspects of our daily lives. High rainfall intensity can cause floods, landslides, and other natural disasters. Therefore, rainfall prediction is important for predicting natural disasters, assisting farmers in production decisions, and crop harvesting. In this research, a system is built to create a rainfall prediction map using a machine learning approach and spatial interpolation algorithms in Java, Indonesia. In the field of weather prediction, the artificial neural network approach is a popular machine learning method. The artificial neural network (ANN) method is a method that has the advantage of studying connections in the previously unknown hidden layer between input data and output data through training procedures. By using the ANN method, historical weather and climate data can be applied to create a classification model and predict rainfall classes. The classification of data is determined based on the attributes of historical weather and climate data, namely temperature, humidity, air pressure, evaporation, sunlight, and the level of rainfall in the time range per day and month. From the results of the ANN modeling, it was found that the 5C month model with an accuracy value of 89% as the best monthly ANN model, and the 6C day model with an accuracy value of 81% as the best daily ANN model. After going through ANN modeling, there is a spatial interpolation algorithm that is often used to estimate rainfall, namely Ordinary Kriging. The Ordinary Kriging approach is used to reduce the estimated variance and estimate the rainfall value in the case study area. After going through Ordinary Kriging modeling, a rainfall prediction map for the next six months and seven days is made based on the coordinates as a result of the research. The results of this research are rainfall prediction maps for the next six months and the next seven days on Java Island.
Smartphone Purchase Recommendation System Using the K-Nearest Neighbor (KNN) Algorithm Bayu Rahmat Setiaji; Dody Qori Utama; Adiwijaya Adiwijaya
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.v6i4.4753

Abstract

Indonesia is in the fourth position of the countries with the most smartphone users worldwide. Smartphones are needed in today's modern times. Smartphones are also used not only for long-distance communication but also for carrying out daily work. Smartphones are currently used for study and work and also become entertainment to play. Therefore, smartphones are very much sought after for the suitability of users who carry out their daily activities. So this research is very helpful for users to find smartphones that support their daily activities such as studying, working, and playing. This research is based on a website that can make it easier for users to see their smartphone recommendations directly. The analysis uses the K-Nearest Neighbor (KKN) method to see the ratings reviewed by other users who have tried using their smartphones with different phone brands. The calculation method in the current study uses 3 KNN calculations and uses the concept of combining calculations to find the maximum recommendation results. The result of the recommendation system using the K-Nearest Neighbor method is in the form of a review stating whether the user agrees or disagrees. In the current study, there have been 100 reviews from users, and it has a percentage of 78% for success and 22% for failure.
Penerapan Algoritma C5.0 Data Mining Untuk Mengetahui Pola Kepuasan Mahasiswa Terhadap Pelayanan Akademik Agung Triayudi
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.v6i4.4961

Abstract

Students are one of the important aspects in improving the quality of higher education. One of the services provided to students is academic services. Knowing the satisfaction of academic services to students for tertiary institutions is quite important. The process carried out to determine student satisfaction has several obstacles, such as the use of a special process to determine student satisfaction. Knowing the pattern of student satisfaction with academic services must be known. To find out the pattern of student satisfaction, it can be done by processing data based on the questionnaire data that has been done previously. Data mining is a process of processing data stored in data warehouses. Data mining performs large data processing with the aim of obtaining valuable information stored in the data set. The C5.0 algorithm is one of the algorithms in data mining that can help solve problems in data processing. The C5.0 algorithm gets results based on the decision tree, the results from the decision tree will later become a new rule or role. The results obtained from the research process are a rule or pattern that can be used to determine the attributes or services that cause dissatisfaction with academic services to students.
Pendekatan Clustering untuk Menganalisis Efisiensi dan Kinerja Mahasiswa Berdasarkan Data Menerapkan Metode K-Means Amelia Rahmadhani
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.v6i4.4922

Abstract

The purpose of this study is to cluster the efficiency and performance of students. This is because the academic community is currently faced with several challenges in terms of analyzing and evaluating the progress of a student's academic achievement. In the real world, classifying student performance is a scientifically challenging task. Recently, several studies have applied cluster analysis to evaluate student outcomes and used statistical techniques to divide their scores in relation to student performance. This approach, however, is not efficient. In this study, we combined two techniques, namely k-mean and elbow clustering algorithm to evaluate student performance. Based on this combination, the performance results will be more accurate in analyzing and evaluating the progress of student performance, the application of the Elbow method according to this study gives the best number of clusters to 3, and when the K-Means method is applied, data is generated that the number of students is 73 students, from 4 repetitions. There are 3 clusters, namely the category of "Achievable", "Potential for Achievement", and "Less Achievement", with the results of the "Achievable" cluster as many as 34 students with a percentage of 47.22%, the cluster "Potential for Achievement" as many as 24 students with a percentage of 33.33 %, and the "Less Achievement" cluster as many as 15 students with a percentage of 19.45%.
Analysis and Design of Game-Based Learning Applications for Early Childhood Using Children-Centered Design Method Stefanus Wisnu Adi Nugroho; Indra Lukmana Sardi; Rosa Reska Riskiana
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.v6i4.4453

Abstract

Early childhood education is a very important stage to prepare early childhood to enter a higher level in basic education. Therefore, appropriate learning methods are needed so that children can be motivated to learn, because early childhood requires interactive and fun learning methods by playing. Based on observations and interviews conducted, early childhood education still uses conventional learning methods. The conventional learning method makes children feel bored while learning and less motivated to learn, especially recognizing the letters of the alphabet and numbers. Game-based learning is a learning method that is an innovation for early childhood learning because it can motivate children to be more enthusiastic in learning. According to existing research, mobile game-based learning is very effective in motivating early childhood learning. Children-centered design is used as a research method because this method places children as the main object of research. Quality in Use Integrated Measurement is used as a usability testing method. The user experience obtained from the results of the analysis will be implemented into a game-based learning application that suits the user's needs. The results of the tests carried out showed results of 87% for low personas, 91% for mid persona, and 95% for high persona.
Question Answering Chatbot using Ontology for History of the Sumedang Larang Kingdom using Cosine Similarity as Similarity Measure Rinaldi Jasmi; 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.v6i4.4530

Abstract

Information can also be a means of learning for humans. Including information about history because history can be a means of learning for the younger generation to appreciate the nation's culture and build national identity. In the past, the Sumedang Larang kingdom was one of the many kingdoms in West Java, Indonesia, that could be used as much information as a lesson. Technological developments make more and more information available for study. We need the proper means to find the information we need. This study aims to build a Question Answering (QA) system to create a means for the younger generation to be more familiar with the history of the kingdom in the past. The QA system offers an information retrieval system that is easy to access and can immediately provide the answers we need. This QA system was built using ontology as a knowledge base and cosine similarity to determine the similarity between user questions and the dataset. The QA system that has been built is tested by providing a set of questions so that the system's performance can be measured, and the results of system testing get a precision value of 70% and a recall value of 90%.
Rancangan dan Evaluasi Usability Pada Aplikasi Website Media Pembelajaran Cyberbullying Menggunakan Metode Gamifikasi Abimanyu Manusakerti; Merlinda Wibowo
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.v6i4.4627

Abstract

Cyberbullying is bullying act carried out on social media to cause harm the victim. The potential for cyberbullying is very high among teenagers. This is due to high frequency of using social media, increasing cases of cyberbullying, and the lack of education about cyberbullying. Cyberbullying education has been carried out using digital literacy educational activities using digital literacy only focus on introducing and preventing cyberbullying in the form of seminars or lectures. However, using this method has many shortcomings, for example someone easily forgets the material presented and gives less space to develop creativity. Interactive education is needed to increase motivation to learn about cyberbullying. The gamification method is very suitable to be applied in learning because the gamification method involves game elements such as points, leaderboards, badges, challenges, and achievements. In addition to using the gamification methods, visual media such as images and animation video is also suitable for learning. This research utilizes gamification-based learning and visual media to deliver the material as a prototype application for cyberbullying learning sites. This research aims to provide education and increase motivation to learn about more interactively cyberbullying. This research involved 42 respondents with a range of ages between 12-21 years. This research will use System Usability Scale (SUS) to evaluate the prototype's usability. The usability score from the prototype in this research is 77.8, meaning the prototype is acceptable to use.
Sistem Penentuan Paket Penjualan dengan Algoritma FP-Growth Serta Metode Up dan Cross Selling Febriantho Febriantho; Samidi Samidi; Gregorius Mikael; Endang Saputra
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.v6i4.4800

Abstract

The Car Spare Part Shop is one of the Car Spare Parts Shops in Tangerang Regency. Based on interviews conducted with shop owners at the Car Spare Parts Store, it was stated that there was a decrease in sales income every month, so there was limited capital in purchasing car spare parts products which resulted in difficulties in choosing which car spare parts products to order. The purpose of this study is to create a system to process and utilize sales transaction data using the FP-Growth algorithm as well as up selling and cross selling methods which will later be used to sell car spare parts that are purchased simultaneously in a sales package determination system. The sales transaction data used is 6,674 transaction data for 1 year of operation of the Car Spare Part Shop (July 2021 - June 2022) with 30,956 records in Microsoft Excel format. The prototype system uses the Python framework flask and mysql database. Validation test results ensure that the software that has been made is in accordance with the expected functional requirements specifications. The results of the system quality test with ISO 9126 can be concluded in the criteria of Very Good with a value of 98.59%. With the results of the Functionality aspect of 99.25%, the results of the Reliability aspect of 98.13%, the results of the Usability aspect of 98.33% and the results of the Efficiency aspect of 98.66%. The results of system security testing with Acunetix and LOIC software have been carried out and the system is still stable and the system is declared safe when used.
Sentiment Analysis on Twitter Social Media towards Climate Change on Indonesia Using IndoBERT Model Muhammad Fadhil Mubaraq; Warih Maharani
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.v6i4.4570

Abstract

The phenomenon of climate change is a change in temperature and weather patterns in the long term. This incident became a frightening specter for everyone because consciously or unconsciously the bad effects of climate change are already in sight. This has become an urgency for all levels of society so that this topic has become quite hot on Social Media, especially on Twitter. The topic of climate change in Indonesia on Twitter Social Media can be analyzed so that it can be seen how people's sentiments towards this phenomenon. This research utilizes the Transformer architecture, namely IndoBERT, IndoBERT itself is the development of the BERT architecture by the IndoNLU team which has 74 million words from various Bahasa Indonesia sources. Therefore, this method was chosen in the hope of helping sentiment analysis on the topic of climate change so that public sentiment can be mapped. The test results obtained an F1-Score values of 95.6% with a tuning parameter of 0.00002 learning rate and 16 of batch size. Hopefully the results of this research can be used in future research.

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