JURNAL MEDIA INFORMATIKA BUDIDARMA
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)
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<![CDATA[Sistem Informasi Penyebaran Lokasi Pelatihan Desa Berbasis GIS di Balai Besar Pengembangan Latihan Masyarakat Jakarta ]]>
<![CDATA[Anhar Hawari]]>;
<![CDATA[Agung Triayudi]]>;
<![CDATA[Ira Diana Sholihati]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 3 (2020): Juli 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/mib.v4i3.2190
<![CDATA[Jakarta Large Community Development Training Center is one of the work units in the Ministry of Villages, Disadvantaged Regions Development and Transmigration, that has the task and function to train rural communities. Every year the community trained can reach thousands of people consisting of several villages. Because the development of information technology maps can be displayed digitally by using Geographic Information Systems (GIS), so that it is more efficient and easily accessed by anyone and anywhere, this digital map will be integrated using the web. This research will be developed using HTML, CSS and Javascript website frameworks as front end, PHP as backend and MySQL by utilizing phpMyAdmin features as a database, all the programming languages will be processed using Codeigniter Framework. The final results of this study will be a Geographic Information System form for training distribution by displaying training locations, training data, as well as video documentation when training takes place, the data will be presented in Google Maps form so that it can easily find the location of training deployments that can later be used as a reference to determine the next training location]]>
<![CDATA[Aplikasi Mikrokontroler Atmega8535 Pada Robot Cerdas Pengangkut Tempat Sampah (Box) Menggunakan Sensor Warna Tcs3200 ]]>
<![CDATA[Suhada Suhada]]>;
<![CDATA[Hasdari Helmi]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 4 (2019): Oktober 2019 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/mib.v3i4.1251
<![CDATA[The robot is a tool that is basically serves to make something easy in human’s work. Trash hauler robot can be utilized by people to assist in providing ease for the cleanlines of the environment. The robot uses program language C which is processed in application of CodeVision AVR. Completion of the steps in the application of this research is to design a program, create a program, do a test of the robot, refinement of program, and the last is the process of program improvement. The Program could be implemented by requiring there is hardware that will be output of the whole research result. The Program is inside of Microcontroller Application ATMega8535 on this intellegent robot of hauler (Box) Trash can be used as a guide for users of technology to increase knowledge and continue the innovation of the useful new technology creation.]]>
<![CDATA[Sistem Informasi Eksekutif Fakultas Teknologi Komunikasi dan Informatika Universitas Nasional ]]>
<![CDATA[Fendy Sulistyo]]>;
<![CDATA[Septi Andryana]]>;
<![CDATA[Winarsih Winarsih]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 3 (2020): Juli 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/mib.v4i3.2137
<![CDATA[Current technological developments, in the activities of information search and decision making at the Faculty of Communication and Information Technology of the National University have not been effective. Because the amount of data available makes it difficult for users to find the specific data needed. Like looking for student data based on class, religion and gender. Therefore, the Executive Information System of the Faculty of Communication and Information Technology of the National University was designed to be web-based so that users could find the required data. Application trial results to search for student data, the system can display search results by force, religion and gender with 100% accuracy. In searching the system data lecturers can display search results based on their latest education, expertise and research with 100% accuracy. Then for the data search system teachers can display search results based on the latest education and expertise with 100% accuracy. The system can also display the number of students by force, the number of lecturers based on expertise and the number of education personnel based on recent education in graphical form]]>
<![CDATA[Analisis Sentimen Terhadap Kandidat Presiden Republik Indonesia Pada Pemilu 2019 di Media Sosial Twitter ]]>
<![CDATA[Cahyo Prianto]]>;
<![CDATA[Nisa Hanum Harani]]>;
<![CDATA[Indra Firmansyah]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 4 (2019): Oktober 2019 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/mib.v3i4.1549
<![CDATA[The development of technology today has been growing rapidly and has an impact on the behavior patterns of people who feel it. The Ministry of Communication and Information (KOMINFO) released a data that of 265 million people of Indonesia, there are around 54% have used internet technology or about 143 million people. In one survey IDN Research Institute said that there are three Social Media that are widely used in Indonesia, namely Facebook, Instagram and Twitter. This study focuses on extracting data in the form of text produced from social media twitter that responds to the account of the RI presidential candidates in the 2019 elections. Sentiment analysis is obtained through tweet classification using sentiment analysis tools such as NRC Lexicon and Bing Lexicon so that information is obtained in the form of positive polarity and negative polarity from community tweets towards the Presidential candidates in the 2019 elections. Using March data before the 2019 election, for candidate 01 Joko Widodo, the NRC Lexicon analysis gave a value of 249 and bing lexicon of 267 with an average value of 0.11, while for candidate 02 Prabowo Subianto the NRC Lexicon analysis gave a value of 195 and bing lexicon of 204 with an average value of 0.085. Using april data after the 2019 election. Candidate 01 Joko Widodo still received a lot of responses from netizens but the sentiment value shifted more negatively compared to candidate 02 Prabowo Subianto. For candidate 01 Joko Widodo the NRC Lexicon analysis gave a value of 17 and bing lexicon of -273 with an average value of -0,246, while for candidate 02 Prabowo Subianto the NRC Lexicon analysis gave a value of 238 and bing lexicon of -73 with an average value of -0.02430939.]]>
<![CDATA[Analisis Sentimen Pembelajaran Daring Pada Twitter di Masa Pandemi COVID-19 Menggunakan Metode Naïve Bayes ]]>
<![CDATA[Samsir Samsir]]>;
<![CDATA[Ambiyar Ambiyar]]>;
<![CDATA[Unung Verawardina]]>;
<![CDATA[Firman Edi]]>;
<![CDATA[Ronal Watrianthos]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/mib.v5i1.2580
<![CDATA[The WHO announced that more than 52 million people tested positive for Covid-19, and 1.2 million died in the second week of November 2020. Meanwhile, Indonesia recorded 463 thousand individuals with 15,148 deaths that were confirmed positive. Strategy against pandemics by incorporating socialization. However, learning that was initially bold as a technique became controversial due to the briefness of the adaptation process. a wide continuum of social reactions has resulted in the sudden transition from face-to-face learning to bold learning on a large scale. This research focuses on public opinion on online learning during the Indonesian COVID-19 pandemic in early November 2020. The analysis was carried out on Twitter by mining document-based text that was interpreted using the Naïve Bayes algorithm. The results show that online learning has a positive sentiment of 30 percent, a negative sentiment of 69 percent, and a neutral 1 percent over the period. Due to community dissatisfaction about online learning, a significant amount of negative sentiment is created. Some tweets indicate disappointment with the words' stress 'and' lazy 'in the conversation being high-frequency words.]]>
<![CDATA[Penerapan Algoritma C4.5 Untuk Prediksi Loyalitas Nasabah PT Erdika Elit Jakarta ]]>
<![CDATA[Khotibul Umam]]>;
<![CDATA[Diah Puspitasari]]>;
<![CDATA[Acmad Nurhadi]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 1 (2020): Januari 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/mib.v4i1.1652
<![CDATA[C4.5 algorithm is a decision tree algorithm group. This algorithm has input in the form of training samples and samples. While samples are data fields which we will use as parameters in classifying data. From the variable transaction frequency the company can see which customers are loyal to the company based on historical customer transaction data, but there are still some variables that make customers loyal to the company. These variables are age, customer gender, company sales gender, educational background, customer transaction frequency. The company knows how to predict customers who will be loyal to the company based on the experience of some of the variables above, but the company does not know the most influential variable in the assessment of loyal customers because of some of the variables above are not interconnected and it is uncertain if one variable can make a decision whether the customer loyal. Based on the decision tree that has made the most influential attribute on customer loyalty is the educational background because it has the highest gain value of 1.545292721 and as the root of the decision tree while the client's gender does not significantly affect customer loyalty because it is always at the last node with the gain value which is 0.623919119.]]>
<![CDATA[Penentuan Siswa SMK Kimia Analisa Terbaik Yang Akan Dikirim Mengikuti Olimpiade Kimia Tingkat Nasional Menerapkan Metode Entropy dan MOORA ]]>
<![CDATA[Yendrizal, Yendrizal]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/mib.v4i4.2350
<![CDATA[SMK Chemistry Analysis is a special and concentrated junior high school in matters related to chemistry, chemistry is very important in human life because every element on earth contains chemicals so chemistry is a department that is very much in demand by many circles, both industrial and non-industrial, so that many students, especially those majoring in Chemistry Analysis, want to do their best to prove their ability in the lessons they persevere by taking part in the Olympics, the Olympics that are followed are usually at the national level between SMK / SMA students and the equivalent which will later become an honor If you can win the chemistry Olympiad, to win an Olympiad it takes students who are really able to take part in competitions, of course schools need to make a selection first in order to get students who really excel and deserve to take part in the Olympics, in the selection it must be done. Do it systematically in order to produce fairness in student selection and minimize failures in participating in the national level chemistry Olympiad, namely by using a decision support system by applying the MOORA method which previously used the entropy method in obtaining subjective weights that will be used in calculating all aspects of decision support]]>
<![CDATA[PERANCANGAN SISTEM PAKAR DIAGNOSA PENYAKIT ASIDOSIS TUBULUS RENALIS MENGGUNAKAN METODE CERTAINTY FACTOR DENGAN PENULUSURAN FORWARD CHAINING ]]>
<![CDATA[Rahmi Ras Fanny]]>;
<![CDATA[Nelly Astuti Hasibuan]]>;
<![CDATA[Efori Buulolo]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 1, No 1 (2017): Maret 2017 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/mib.v1i1.316
<![CDATA[Renal tubular acidosis and commonly referred to as kidney disease, especially in the renal tubules, according to some scientific medical fields of renal tubular acidosis are quite rare, with clinical manifestations that are not specific so that the diagnosis is often delayed. In normal circumstances, the kidneys absorb the acid of the metabolic waste from the blood and throw it into the urine. The cause of renal tubular acidosis disease is due to hereditary factors or may result from medications. Forward Chaining is a search method or tracking technique that begins with existing information merging rules to produce a conclusion or goal. This advanced tracking is great if it works with problems that start with the initial information recording and the final completion, as the whole process will be done in sequential order.]]>
<![CDATA[Perancangan User Interface Design dan User Experience Mobile Responsive Pada Website Perusahaan ]]>
<![CDATA[Moh Dani Ariawan]]>;
<![CDATA[Agung Triayudi]]>;
<![CDATA[Ira Diana Sholihati]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 1 (2020): Januari 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/mib.v4i1.1896
<![CDATA[Human-Centered Design Method is a method of approach in the development and design of a system that focuses on the user according to aspects of the needs and habits of the user. Difficulty in accessing information on the website becomes a problem faced by the user and in terms of visual website can not be responsive when accessed via mobile. The initial stage carried out in this method is observation which aims to find and to better understand the problems faced by users to conduct testing to find out whether the solutions provided can be understood and easily used by the user. Website testing is done by giving tasks to the user to interact on the website prototype, as the final result of success in the aspect of ease and comfort of the user using the website. After testing the user directly the test results are obtained, ie the user already feels quite understanding and easy when using the website that was created. The responsive mobile feature created also makes users feel helped when using a website on a smartphone.]]>
<![CDATA[Penerapan Data Mining Pada Penerimaan Dosen Tetap Menggunakan Metode Naive Bayes Classifier dan C4.5 ]]>
<![CDATA[Sadikin, Muhammad]]>;
<![CDATA[Rosnelly, Rika]]>;
<![CDATA[Roslina, Roslina]]>;
<![CDATA[Gunawan, Teddy Surya]]>;
<![CDATA[Wanayumini, Wanayumini]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
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DOI: 10.30865/mib.v4i4.2434
<![CDATA[Recruitment is an important step in creating professional HR (Human Resources). The application of classification methods such as the Naïve Bayes method and C4.5 can be used in the classification of potential lecturers and can be accepted by the campus by calculating the equations for each criterion. The difficulty experienced is the ineffective use of the method to generate the required lecturer acceptance so that it is not in accordance with the applicant's expertise. One of the classification methods applied to data mining is the naïve Bayes method and C4.5. The purpose of this study is to determine the level of accuracy of the two methods used by using the Weka 3.8 tool based on the calculation of Correctly Classified Instance and Incorrectly Classified Instance. The accuracy results obtained with the naïve Bayes method are 83.7838% and the C4.5 method is 91.8919% from 37 training data. So the C4.5 method is a more appropriate method to use than naïve Bayes.]]>
