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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
Telkom University Opinion Topic Modeling on Twitter Using Latent Dirichlet Allocation During Covid-19 Pandemic Tandya Rizky Pratama; Donni Richasdy; Mahendra Dwifebri Purbolaksono
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.v6i4.4426

Abstract

In the current digital era, the development of information technology is growing rapidly. The development of information technology is followed by the development of social media, one of the social media that is on the rise is Twitter. Because there are many Twitter users around the world, Twitter stores a lot of data that can be used for something, one of which is to determine the category of public opinion about a company or university, in this study the focus is more on the category of public opinion about Telkom University. The public opinion can be grouped or categorized to make it easier to determine the topic being discussed. Determining opinions manually will take a long time due to the large number of tweets. Therefore, there must be another method to determine the categories of public opinion on Twitter. One of them is the Latent Dirichlet Allocation (LDA) method with a dataset of tweets of Indonesian-language Twitter users. With this method, grouping tweets on a large scale is more efficient. From the modeling made, the most optimum results obtained with a coherence score using the c_umass method of -15.33029 with a combination of 9 topics, 0.31 alpha value, and 0.01 beta value.
Metode Algoritma Support Vector Machine (SVM) Linier Dalam Memprediksi Kelulusan Mahasiswa Oktaviana Bangun; Herman Mawengkang; Syahril Efendi
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.v6i4.4572

Abstract

The accumulation of student databases can occur if students are unable to complete their studies, namely graduating at a predetermined time. Data mining techniques are often used to process student data so that they can produce predictions of student graduation in order to graduate at a predetermined time. One of the data mining techniques that is often used is the Support Vector Machine (SVM) algorithm. This study aims to analyze the performance of the SVM algorithm to produce a predictive model of student graduation in order to graduate at a predetermined time in the Public Health Study Program, Faculty of Public Health, Deli Husada Health Institute. The method used in this study is a linear SVM algorithm starting from data retrieval by selecting the attributes that will be used for the next stage, data processing consists of cleaning data whose contents do not exist and data transformation which is the determination of the category of each data, modeling is done with the SVM algorithm. from training data and testing and evaluation data to validate and measure the accuracy of the model. The test results with the amount of training data as much as 70% and testing data as much as 30% shows that the linear SVM algorithm provides an accuracy value of 90%
Deteksi Hama Pada Daun Apel Menggunakan Algoritma Convolutional Neural Network Dede Husen; Kusrini Kusrini; Kusnawi Kusnawi
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.v6i4.4667

Abstract

Today the need for fruit consumption is increasing along with the increasing human population and awareness of the consumption of nutritious foods, apples are one of the most consumed fruits by humans worldwide. According to data quoted from the Indonesian National Statistics Center in 2021, apple production in 2021 decreased from the previous year from 519,531 tons to 509,544 tons. One of the causes of the decline in apple production is the presence of pests on the apple plant. At least there are several types of pests that can be identified on apple leaves, namely Apple Scrub (Venturia inaequalis), Apple Black Root (Botryosphaeria) and Apple Cedar/Rust (Gymnosporangium juniperi virginianae). The research stage begins with conducting several literature studies regarding related research, then formulating and validating the problem and starting to collect data from the Kaggle public dataset. Then in the experimental stage, the author divides the dataset into three parts with a percentage of 80% training data, 10% validation data and 10% testing data. The image classification method used is the Convolutional Neural Network (CNN) algorithm to create a model that can classify image data, the process of implementing the author uses the python programming language to build the model. The author conducted several experiments by making changes to several model parameters that affect the accuracy of the model. To evaluate the performance and accuracy of the model using a confusion matrix. The results of the study indicate that image size, data augmentation and the number of epochs greatly affect the accuracy of the model, from the test results the CNN model with the best accuracy is the model with the image size parameter 256x256, horizontal flip, vertical flip and random rotation data augmentation and the number of the 60th epoch has the highest accuracy rate of 99.66%. The results of this study are expected to be implemented in an application that can be used directly by farmers in detecting pests on apple plants quickly and accurately.
Implementasi Metode Moora Pada Sistem Pendukung Keputusan Penilaian Kinerja Karyawan Heri Susanto; Fitra Kurnia; Yusra Yusra; Lola Oktavia
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.v6i4.4750

Abstract

Employee performance appraisal is needed by an agency or company with the aim of evaluating performance and improving the quality of competent human resources and high loyalty for each employee at work, then an agency or company can give awards to each of its employees such as contract extensions, salary increases , get special promotions, appointments, and allowances, which can motivate every employee. This study aims to facilitate a planner in a company PT. SUPRACO INDONESIA in providing performance appraisals of each employee uses a decision support system using the Multi Objective Optimization On The Basic Of Ratio Analysis (MOORA) method. This employee performance appraisal decision support system uses a sample of 3 employees from 11 employees using the MOORA method of calculation. the final results of the calculations carried out are: for the first rank in alternative 2 with a value of 5.7805, while the second rank in alternative 1 with a value of 5.7736, and third place in alternative 3 with a value of 5.7671. In the tests carried out using Blackbox Testing, for all the features on the system running 100% with very good information and testing using the UAT (User Acceptance Test) method, it showed that the results of system user acceptance were 92%.
Sistem Pakar Diagnosis Tingkat Stres Berbasis Android dengan Metode Certainty Factor Noviandi Noviandi; Diah Aryani; Arief Ichwani
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.v6i4.4727

Abstract

The number of cases of Corona Virus Diesis (COVID-19) according to the World Health Organization (WHO) is 93,217,287 people. In the case of Covid-19, one of which is making changes in behavior is education. The teaching and learning process has changed into bold learning in the education sector. Students who continuously carry out the learning process at home can increase stress because previous research data stated that the level of severe anxiety experienced by students was one of them caused by daring learning, which reached 95.59%, and students reached 97.69%. This research aims to develop an expert system for dealing with stress in high school students. The method used for making the expert system is the Certainty Factor. Based on functionality testing using black box testing, it shows that all components produce the expected and appropriate results, then for accuracy testing using a confusion matrix through a comparison between manual calculations and system calculations, so that the accuracy test results are 100%. Therefore, the expert system for diagnosing stress diseases in high school students can be said to be feasible.
Penggunaan Metode AHP dan Topsis dalam Pemilihan Penyedia Suku Cadang Instalasi Perawatan Sarana Rumah Sakit Wahid Al Jufri; Agung Triayudi; Ben Rahman
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.v6i4.4497

Abstract

Determination in choosing a supplier is one of the strategic programs and needs to be more objective, often the decision making in choosing a supplier is only based on intuition, habit and experience, until now there is no mechanism or method for this that is suitable or only according to universal select criteria. Hospital Facility Maintenance Facility (IPSRS) is a facility that oversees all maintenance and repair work on non-medical facilities at the National Brain Center Hospital, including building maintenance, electrical systems, plumbing, AC management, surveillance camera or CCTV maintenance, and motor generator repair. and telephone control generator. To select the expected spare parts supplier, it is necessary to apply the SPK Ideal Solution Similarity Order Preference Technique (TOPSIS) method and combine it with the Analytical Hierarchy Process (AHP) method to facilitate the process of selecting more than one alternative. The criteria determined in this study are S1 with Price, S2 with Quality, S3 with Speed and S4 with Completeness. With these criteria, it can be used as material to determine the Decision Support carried out by the system. In the results of this study the determination of the criteria using AHP with the results of the Consistency Ratio value of 0.004 which means if the value is above 0.01 then the results are declared consistent. As well as for the design using the Topsis method, the positive ideal solution on the criteria S1 is worth 0.13282, S2 is worth 0.07954, S3 is 0.04085 and S4 is 0.0422. Meanwhile, for the negative ideal solution, S1 is worth 0.04981, S2 is 0.02983, S3 is 0.02043 and S4 is 0.0211. The first rank is P7 with a value of 0.813 and the last order is P8 with a value of 0.13. So, from the results of the assessment carried out by the system based on the weight value for ranking using the TOPSIS method which occupies the top three positions, PT. Cipta Karya Teknik with a total of 0.813 or 81.3%, followed by PT. Karya Mandiri Indonesia with a total of 0.802 or 80.2%, and PT. Indah Harapan Nusa with a total of 0.796 or 79.6%. As for the bottom three positions are PT. Tunggal Teknik Indo with a total of 0.292 or 29.2%, then PT.Harapan Maju Bersama which has a total of 0.139 or 13.9% and the last one is PT. Forward Rise Simultaneously with a value of 0.130 or 13%.
Netflix Movie Recommendation System Using Collaborative Filtering With K-Means Clustering Method on Twitter Muhammad Tsaqif Muhadzdzib Ramadhan; Erwin Budi Setiawan
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.v6i4.4571

Abstract

Nowadays, the development of technology is very rapid, so watching movies at home has become a means of entertainment. Netflix is one of the platforms for watching movies and provides various movie titles. However, because of the many movie titles, it makes it difficult for users to determine the movie they want to watch. The solution to this problem is to provide a recommendation system that can provide movie recommendations to watch. Collaborative filtering is a method that exists in the recommendation system by providing recommendations based on the ratings given by other users. Collaborative filtering is divided into two, namely based on items (item-based) and based on users (user-based). Twitter is a social media used to write posts called tweets. For this system, tweets serve as data that will be processed into ratings. This research was conducted using k-means clustering with collaborative filtering and collaborative filtering only. By using a dataset obtained from Twitter by crawling data and added with ratings from IMDb, Rotten Tomatoes, and Metacritic. Which resulted in a dataset with 35 users, 785 movie titles, and 6184 reviews. Then preprocessing the data with text processing, polarity, and labeling. And get the dataset that will be used for this experiment. The results of this research test show that k-means clustering with collaborative filtering gets the best results with the best prediction of 2.8466, getting an MAE value of 0.5029, and an RMSE value of 0.6354
Sistem Pendukung Keputusan Pemilihan E-Commerce Terbaik Menggunakan Metode MOOSRA Zulfi Azhar; Neni Mulyani; Jeperson Hutahaean; Ade Mayhaky
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.v6i4.4775

Abstract

Online transactions are transactions that are very popular with many parties today because of the ease of access, ease of transactions and security possessed by each e-commerce, the number of parties who use e-commerce because of the dependence and availability of smartphones and the habits of the current generation on digital age. Every transaction habit contains its own risk to its users, so it is necessary to know the things that must be fulfilled as a user in choosing e-commerce to reduce the risk that will be accepted in the future. This study uses a decision support system logic in analyzing the selection of the best e-commerce using the moosra method. Consider using the method not only based on decisions made by yourself but based on considerations from several previous studies. The results obtained from this study using the moosra method are the highest value of 3.26323 on e-commerce lazada as the best e-commerce.
Analisis Kualitas Rancangan Point of Sale Menerapkan Metode Mean Squared Error Fithrie Soufitri; Ellanda Purwawijaya
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.v6i4.4767

Abstract

The development of the business prompted the company to always strive to improve the quality of products and services to consumers. The service can purchase goods was done electronically and can also be done online or electronic commerce. Implementation of business solutions is a commitment to improve its corporate customers a competitive advantage in terms of efficiency, effectiveness, performance, and business development. The research purpose is to analyze the quality of point of sale (POS) designs to support a purchasing service system that can help Nasi Kapau Unidar restaurants. This creation begins with data collection using the mean squared error (MSE) method with a flowchart approach and Unified Modeling Language (UML) with the result of the accuracy with mean squared error of 0.44.
Sistem Informasi Pendugaan Kekerasan Terhadap Perempuan dan Anak Menggunakan Metode Small Area Estimation Misbahul Munir S; Nurul Mutiah; Syahru Rahmayudha; Renny Puspita Sari
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.v6i4.4523

Abstract

Based on data obtained from the SIMFONI-PPA Application, the Office of Women's Empowerment, Child Protection, Population Control and Family Planning (DP3AP2KB) Sambas Regency, in 2017 there were 95 cases of violence against women and children in Sambas Regency, then in 2018 there were 43 cases, followed by in 2019 as many as 49 cases, and in 2020 as many as 64 cases. This shows an increasing trend in the number of cases of violence that occur from year to year. The increasing trend is caused by the lack of access to information to make complaints, the processing of data on areas of violence that has not been integrated, so that the government does not have up-to-date data to anticipate. To support DP3AP2KB in handling and preventing violence, this research builds a system based on the estimation of violence against women and children by utilizing the Small Area Estimation Method, especially the IDW interpolation technique. This research was carried out by processing data through the ArcGIS application to determine the pattern of areas prone to violence, using interpolation techniques to predict unmeasured variables at various locations, with IDW assuming that the closer a point is to an unknown point, the greater the effect. . IDW uses the values measured at points around the location, to estimate the value of the variable at the location in question. Then the results of data processing is implemented in a web-based geographic information system. The system that has been built has been tested using the black box method and calculated using a Likert scale, obtaining a value of 86.20% which is included in the Very Good category.

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