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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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Effect Of MVVM Architecture Pattern on Android Based Application Performance Hammamul Achdan Epiloksa; Dana Sulistyo Kusumo; Monterico Adrian
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.v6i4.4545

Abstract

The performance of android-based mobile applications is very important to pay attention to because performance will be related to how users will feel the experience of the application. This relates to memory usage and CPU usage on android devices when using applications. There are several ways used to improve the performance of android-based mobile applications, one of which is by applying an architecture pattern. The use of the right architecture is expected to produce good performance for android devices when running an application. Therefore, the author conducted a study on whether the application of the MVVM architecture pattern by changing the program code with the refactoring method will affect memory usage, CPU, and code execution time in Android-based applications. This is implemented using the Android Studio application and using android profiler tools to measure the performance of the application.
Sistem Klasifikasi Penjualan Produk Alat Listrik Terlaris Untuk Optimasi Pengadaan Stok Menggunakan Naïve Bayes Irfan Reza Pratama; Maimunah Maimunah; Endah Ratna Arumi
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.v6i4.4418

Abstract

Optimization is a process of solving a problem so that it can provide the best conditions that can provide a maximum or minimum value. In a business, optimization of stock procurement is an important thing, including in terms of product sales. If the stock of a product is empty then the sales potential decreases. Therefore we need a method to optimize the stock so that it can supply consumer demand and ultimately increase sales. Data mining can be applied in the sales system by creating a sales classification model for the best-selling products. In this study, the sales classification of the best-selling products at electronic stores was carried out using Naïve Bayes. The data used in this study is data on sales of electronic products for 3 months. In the early stages, preprocessing is carried out, namely by encoding labels. Model testing was carried out using percentage split and cross validation with several trials. Through the use of percentage split, the best accuracy is obtained at 93.3% with a comparison of 30% of test data and 70% of training data. The best accuracy using cross validation was obtained by 84% for 7-fold. The classification system that has been created is capable of classifying the best-selling products every quarter of a year. Through the use of the best-selling product classification system, the store can find out the best-selling product stock so that the stock is not empty. Thus the procurement of store stock can be more optimal and sales will increase.
Implementasi Metode HSI pada Transformasi Ruang Warna Dalam Mendeteksi Kematangan Buah Mangga Udang Yuni Franciska Br Tarigan; Karina Andriani; Rika Rosnelly; Wanayumini Wanayumini
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.v6i4.4547

Abstract

Mango is a plant that is widely cultivated in Indonesia. Mango is a fruit that is popular and favored by almost the entire world population. Mango is not a native plant from Indonesia but is a fruit plant native to India that has a distinctive taste. The shelf life is very short because it is a fruit that is easily damaged or rotted in a certain period of time. The use of technology Digital image is an image that can be processed directly by a computer. A digital image can be represented by a matrix consisting of M columns and N rows, where the intersection between the columns and rows is called a pixel (picture element), which is the smallest element of an image. Image processing is a form of processing an image or image by numerical processing of the image, in this case, each pixel or point of the image is processed. One image processing technique utilizes a computer as software to process each pixel of an image. For image processing applications that perform object recognition, it will be easier if the object is identified using the difference in its hue value by limiting a certain value of the hue value to the object. The HSI color space model is a color space system similar to the performance of the human eye. HSI works by combining the color or grayscale contained in the image. Based on the reference value range of the Mango Shrimp fruit that has been determined in the process using the HSI method, it can be concluded that the test image of the Mango Shrimp fruit with a value of H=32 S=0.675 I=83 then the manga can be said to be ripe.
Penerapan Metode Dempster Shafer Pada Sistem Pakar Diagnosa Penyakit Rabies Juan Veron Christian L Sirait; Iqbal Kamil Siregar; Cecep Maulana
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.v6i4.4751

Abstract

Rabies is a disease caused by the bite of animals such as dogs, cats and bats, if not treated quickly it can cause death. Patients can make a diagnosis for easy treatment of the disease. The number of patients who died because of the bites of animals that transmit Rabies. Animal owners still do not understand the consequences of the bites of the animals they maintain. Advances in expert systems can overcome this problem, namely by designing a web-based computer system that is integrated with databases and programming languages such as PHP-MySQL so that can help people with Rabies to diagnose the symptoms and types of the disease. The purpose of this research is to build an expert system to diagnose web-based Rabies. The application of the expert system in making this decision uses the Dempher Shaper method by generating true and false values on the new and old knowledge bases and comparing them with the weight values in each frame so that the percentage of the disease type is obtained. The result of the system implementation is that the system provides questions in the form of symptoms that must be answered by the patient based on the symptoms experienced by the patient and the results of the process the system will provide information on the type of Rabies Rabies (Prodromal Stage) = with a confidence value of 80.4% and can also obtain a solution.
Work Readiness Prediction of Telkom University Students Using Multinomial Logistic Regression and Random Forest Method Haura Athaya Salka; Kemas Muslim Lhaksmana
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.v6i4.4546

Abstract

Work readiness for college graduates is an essential and significant thing to get a job immediately after graduation. But what happens is that many graduates are unemployed after graduation or do not get jobs that match the majors they have studied for more than four years. Therefore, by using a people analytics approach, this study aims to predict the work readiness of Telkom University students and find out what factors affect student work-readiness after graduation. The model built is a multi-classes classification model. This model uses Chi-square Test calculation for feature selection, Multinomial Logistic Regression and Random Forest as a classification method, and confusion matrix as an evaluation method. Multinomial Logistic Regression is used because several studies use this algorithm for categorical data, while Random Forest is used to compare which model produces better accuracy. This study conducted several test scenarios, which obtained the best model by performing hyperparameter tuning and handling unbalanced data with SMOTE-ENN. Handling imbalanced data with SMOTE-ENN is used to improve accuracy scores and predict classes well, especially for minority class. The best accuracy of the Multinomial Logistic Regression method is 53.9%, and Random Forest is 48.5%.
Application of Data Mining using Naive Bayes for Student Success Rates in Learning Bayu Angga Wijaya; Vijay Kumar; Berlian Fransisco Jhon Wau; Juliansyah Putra Tanjung; N P Dharshinni
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.v6i4.4639

Abstract

Education is a very important part of human life because through education quality human resources will be formed. Quality education can be read and measured by the achievement of various indicators. However, achieving these indicators is not easy, because learning success is influenced by several factors. One of the factors that can affect the success of learning is the learning system. To understand the level of student success in learning, a data mining processing technique is needed. The algorithm that will be used in this research is the naive Bayes algorithm. This study uses 601 datasets per year from Academic Year 2019/2020 to Academic Year 2021/2022, the data used are attendance score data, assignment scores, mid-exam scores, semester exam scores, and averages. The test is divided into 3, namely testing for the Academic Year 2019/2020 dataset, testing for the Academic Year 2020/2021 dataset, and testing for Academic Year 2021/2022 using the split validation operator. The test results using the Academic Year 2019/2020 – Academic Year 2020/2021 student score dataset have an accuracy value of 95.01% while the Academic Year 2021/2022 student score dataset has an accuracy value of 97.79%.
Sistem Pakar Diagnosa Penyakit Pencernaan Menggunakan Metode Case Based Reasoning (CBR) Berbasis Web Arfian Jumintar Sitorus; Jhonson Efendi Hutagalung; Ari Dermawan
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.v6i4.4764

Abstract

The main factors causing digestive disorders are food that is not good in terms of hygiene and health, nutritional balance, improper diet, infection, and abnormalities in the digestive organs so that they will contract several digestive diseases such as appendicitis, ulcers, stomach ulcers, hepatitis. , diarrhea and constipation. Early treatment is needed before consulting specifically with a digestive disease specialist before the disease is severe. In this case, it is necessary to have a system that can replace specialist doctors in diagnosing early symptoms of digestive diseases considering the high cost of consulting a doctor. This diagnostic expert system is very much needed in diagnosing early symptoms of the causes of digestive diseases. The application of the system is equipped with a Case Based Reasoning that solves new cases based on reasoning from old cases. The implementation has resulted in gastric cancer of 67.01% according to the symptoms selected by the patient, then the system also provides treatment advice, and provides information on the handling or treatment of gastric cancer, so that with this application it can help doctors in diagnosing the disease quickly.
Pengelompokan Cuaca Kota Palembang Menggunakan Algoritma K-Means Clustering Untuk Mengetahui Pola Karakteristik Cuaca Shanaz Khairunnisa; Muhammad Ihsan Jambak
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.v6i4.4810

Abstract

Weather related information is one of the things that is very important and has a big influence on all kinds of life activities such as in public safety, socio-economics, agriculture, aviation, and so on.The weather in each place or region is different, this happens because of the different weather elements in each place/region. By using data mining clustering techniques, weather clustering will be carried out in the city of Palembang. K-means is the algorithm chosen for clustering the weather in the city of Palembang. The test was carried out using daily weather data for 2020-2021 from BMKG by utilizing rapidminer application as learning techniques for data. So that we will get a group of weather characteristics of Palembang city based on similarities and dissimilarities. From the test results, the best k was obtained at k=3 with the parameters  Measure Types ( NumericalMeasure ) and Divergences ( DynamicTimeWarpingDistance ) as well as a local random seed of 2500 seen from the results of the Davies-Bouldin Index (DBI). This weather grouping can later provide information on how the weather character is and reduce the impact of sudden changes in weather conditions.
Sistem Pakar Untuk Mendiagnosa Penyakit Paru-Paru dengan Menggunakan Metode Teorema Bayes Alex Wenda; Kraugusteeliana Kraugusteeliana; Andik Adi Suryanto; Sitti Nur Alam; Karya Suhada
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 1 (2023): Januari 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i1.5394

Abstract

Health is one of the most expensive assets that no one can buy. So that health is the most important thing for every human being, which is priceless. One of the important organs in the human body that greatly affects health is the lungs. The lungs are a part of the human body that plays a role in the respiratory system. Where the respiratory system holds the main control in human life after the heart. at the time of examination of the lungs, the costs required are relatively expensive. So because of the high cost of inspection and the lack of funds owned by the community, so that in the end the community becomes hesitant to carry out an examination. To help the community in dealing with these problems, a system is needed that can help the community diagnose or find out the disease that is being experienced by the community. The system is an expert system. An expert system is a system developed by experts using technology. Expert systems need methods. The method used in this study is the Bayes Theorem. The main function of this Bayes Theorem is to calculate the probability of an event or event occurring through the basis of the effect resulting from an observation or observation. After carrying out calculations based on this method, information was obtained that 90% of patients who consulted had Lung Cancer.
Performa Support Vector Machine Pada Klasifikasi Lahan dan Air Tanah Angellina Angellina; Dyah Erny Herwindiati; Janson Hendryli
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 1 (2023): Januari 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i1.5279

Abstract

Groundwater is one of the sources of water in the world. The availability of groundwater is one of the factors that plays an important role in carrying out daily life activities, including for drinking, cooking, washing, irrigating rice fields, and many others. One source of groundwater in Jakarta is obtained from the Ciliwung River which is passed by the Bogor and Depok areas. However, the existence of springs and groundwater continues to decrease until now. The purpose of this paper is to discuss the first stage of the classification of groundwater availability in several sub-districts in the Bogor and Depok areas. The results of phase one will present a mapping of green areas along with their classification. Data taken from Landsat 8 Satellite Imagery - United States Geological Survey (USGS). The Support vector Machine (SVM) method is used to classify the availability of groundwater. The input data for the training process are the Normalized Difference Vegetation Index, Soil Adjusted Vegetation Index, and Enhanced Vegetation Index constants. The results of the evaluation using linear kernel produced a green F1 score of 89.58%, half green 65.62%, and dry 83.44%. While the results of the evaluation using the polynomial kernel produced a green F1 score of 83.58%, half green 25.68%, and dry 66.59%.

Page 74 of 119 | Total Record : 1182

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