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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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Sistem Pendukung Keputusan Pemilihan Peserta Jaminan Kesehatan Masyarakat (Jamkesmas) Menerapkan Metode MOORA Mesran Mesran; Swandi Dedi Arnold Pardede; Arahman Harahap; Andysah Putera Utama Siahaan
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 2, No 2 (2018): Apriil 2018
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v2i2.595

Abstract

Decision support system as a computer-based system consisting of components, among other components of the language system (language), components of knowledge systems (knowledge) and components of the problem processing system (problem processing) which interact with each other, which helps decision making through the use of data and decision models to solve problems that are semi-structured and unstructured. This study uses the MOORA Method in determining who is entitled to become participants Jamkesmas based on criteria by using a formula that results more accurate and targeted.
Implementasi Algoritma Neural Network dalam Memprediksi Tingkat Kelulusan Mahasiswa Ridwan Ridwan; Hendarman Lubis; Prio Kustanto
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 2 (2020): April 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i2.2035

Abstract

Higher education institutions are demanded to be quality education providers. One of the instruments used by the government to measure the quality of education providers is the number of graduates. The higher the graduation level, the better the quality of education and this good quality will positively influence the value of accreditation given by BAN-PT. Therefore, in this study the researchers provided input for research conducted at Bhayangkara Jakarta Raya University to predict student graduation rates using the Neural Network algorithm. Neural Network is one method in machine learning developed from Multi Layer Perceptron (MLP) which is designed to process two-dimensional data. Neural Network is included in the Deep Neural Network type because of its deep network level and is widely implemented in image data. Neural Network has two methods; namely classification using feedforward and learning stages using backpropagation. The way Neural Network works is similar to MLP, but in Neural Network each neuron is presented in two dimensions, unlike MLP where each neuron is only one dimensional in size. The prediction accuracy obtained is 98.27%.
Pemanfaatan Google Formulir Sebagai Sistem Pendaftaran Anggota Pada Website Asosiasi Untung Rahardja; Ninda Lutfiani; Mochamad Sandi Alpansuri
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 2, No 4 (2018): Oktober 2018
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v2i4.789

Abstract

Indonesian private university associations still use conventional system. this can be seen there is no registration of members online and registration work and this data collection is still using file system in the form of printout form. Then performed a system of checking and inputting data. If there is an error in charging the data, then do the system repetition. Things like this are deemed very ineffective because it will cause the buildup of files. This process is the one that until now runs in the association of Indonesian private universities. Therefore, Indonesian private university associations utilize google forms to support member registration activities online on the website of Indonesian private college association. Google form is a form facility that can be used to get the data of someone either in the form of questionnaire or registration, provided google platform which can easily be used for free in Google Drive. By making observations in the form of data collection, by doing a direct observation of an existing problem, it is considered less effective and efficient in managing a member report conducted conventionally through several convoluted processes and tend to require a long time so it is less effective. So that the need for a conventional system to be online so that with the online registration is aimed to improve the effective and efficient workers in managing data collection and registration of members previously done conventionally at the association of Indonesian private universities.
Simulasi Penggunaan Intrusion Detection System (IDS) Sebagai Keamanan Jaringan dan Komputer Barany Fachri; Fadli Hamdi Harahap
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 2 (2020): April 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i2.2037

Abstract

In the current era of information technology, computer network security is part of a system that is very important to maintain the validity and integrity of data and to ensure the availability of users' morning services from anywhere and anytime. And on one hand humans are very dependent on information systems. That causes the statistics of network security incidents to increase sharply from year to year. So we need a solution to overcome this, one of which is by simulation. Simulations are carried out to simulate existing real network security systems with properties that are easier to observe than the original system, to determine system performance. In this research, a system that is able to cope with threats that may occur optimally in a fast time is needed, this will speed up the process of handling disruptions and system or service recovery. One way that can be used to overcome or overcome this is to use the Intrusion Detection System (IDS). One application that supports intrusion detection system (IDS) is Snort. Snort is able to do an analysis of the forms of intruder attacks that misuse network protocols
Penerapan Sistem Pakar Menggunakan Metode Nearest Neighbor Mendiagnosa Gangguan Kesehatan Pengguna Minuman Keras Lince Tomoria Sianturi; Tegar Sabatia Tarigan
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 1 (2019): Januari 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v3i1.1060

Abstract

Expert systems in general are systems that try to adopt human knowledge to computers so that computers can solve problems as is usually done by experts. Or in other words an expert system is a system that is designed and implemented with the help of certain programming languages to be able to solve problems as done by experts. It is expected that with this system, lay people can solve certain problems, either 'a little' complicated or even complicated 'without' the help of experts in the field. As for experts, this system can be used as an experienced assistant. This system diagnoses the types of health problems of liquor users based on the symptoms entered into the system. This developed application aims to determine which liquor users consume by only paying attention to the criteria experienced by liquor users. Using the Nearest Neighbor Method is able to show a measure of certainty about a fact from the existing criteria. System output in the form of search results for liquor users is used by users based on symptoms.
Analisis Sentimen Persepsi Masyarakat Terhadap Pemilu 2019 Pada Media Sosial Twitter Menggunakan Naive Bayes Safitri Juanita
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 3 (2020): Juli 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i3.2140

Abstract

According to the BAWASLU evaluation a variety of related negative content supports supporting prospective couples to burst into various social media pages. So sometimes the content leads to a hoax issue to the issue of religious and inter-group Racial (SARA). One of the social media used by the people of Indonesia is Twitter, according to Kompas.com number of Twitter daily users globally claimed to be increasing, this appears to be the 3rd Quarter Twitter Financial Report of 2019 on Twitter's 3rd quarter of 2019 Financial reports, daily active users on the Twitter platform are recorded to increase by 17 percent, to the number of 145 million users. So it is necessary that a sentiment analysis study can capture a pattern of community perception on social media Twitter against the 2019 elections and it is expected that this research can help interested parties to increase voter participation rate in the next 5 years. This research method uses the Indonesian tweet data taken from 16 April 2018-16 April 2019, further data in preprocessing, text transformation, stemming Bahasa Indonesia, specifying attribute class, load dictonary and a classification of Naive Bayes using Weka. The conclusion of this study was the classification of Naive Bayes finding that the 2019 election tweet dataset had a negative perception pattern of 52% much greater than the positive perception of 18% and the neutral perception had a value of 31% higher than positive perception. Naive Bayes ' degree of classification accuracy against the training dataset is 81% and the dataset testing 76%, the average precision value for positive sentiment is 86.65%, negative sentiment is 77.15%, and neutral sentiment is worth 80.95% while the average recall rate on positive sentiment is 36.8%, negative sentiment is 93.2% and the neutral sentiment is 86.8%
Message Queuing Telemetry Transport dalam Internet of Things menggunakan ESP-32 Moh Noor Al-Azam; Darian Rizaludin; Yulius Satmoko Raharjo; Aryo Nugroho
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 3 (2019): Juli 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v3i3.1160

Abstract

Message Queuing Telemetry Transport (MQTT) is a connectivity protocol between machines or now better known as the Internet of Things (IoT). This protocol recognizes two basic functions of M2M communication, namely publish and subscribe (pub/sub). The MQTT protocol is designed as a very simple and very lightweight message delivery protocol, designed for devices that are limited and with low bandwidth capacity, high latency or on an unreliable network. The design principles are to minimize bandwidth requirements and device resource requirements, and keep trying to ensure reliability and guaranteed delivery rates. In this paper, VerneMQ performance reliability is tested - one of the MQTT brokers, with several stressing levels using ESP-32 as a publisher and notebook with the python application as a subscriber.
Analisis Sentimen Terhadap Layanan Indihome Berdasarkan Twitter Dengan Metode Klasifikasi Support Vector Machine (SVM) Rian Tineges; Agung Triayudi; Ira Diana Sholihati
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 3 (2020): Juli 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i3.2181

Abstract

In the year 2018, 18.9% of the population in Indonesia mentioned that the main reason for their use of the Internet is social media. One of the social media with an active user of 6.43 million users is Twitter. Based on the surge of information published via Twitter, it is possible that such information may contain the user's opinions on an object, such objects may be events around the community such as a product or service. This makes the company use Twitter as a medium to disseminate information. An example is an Internet Service Provider (ISP) such as Indihome. Through Twitter, users can discuss each other's complaints or satisfaction with Indihome's services. It takes a method of sentiment analysis to understand whether the textual data includes negative opinions or positive opinions. Thus, the authors use the Support Vector Machine (SVM) method in sentiment analysis on the opinions of the Indihome service user on Twitter, with the aim of obtaining a sentiment classification model using SVM, and to know how much accuracy the SVM method generates, which is applied to sentiment analysis, and to see how satisfied the Indihome service users are based on Twitter. After testing with SVM method The result is accuracy 87%, precision 86%, recall 95%, error rate 13%, and F1-score 90%
Klasifikasi Berita Bahasa Indonesia Menggunakan Mutual Information dan Support Vector Machine Lalu Gias Irham; Adiwijaya Adiwijaya; Untari Novia Wisesty
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 4 (2019): Oktober 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v3i4.1410

Abstract

News is a source of information disseminated in various types of media. In order to make it easier for news readers to obtain the desired news, the news needs to be classified. The large number of scattered news creates difficulties in classifying the news based on the topic. Therefore the author conducted a study to classify news into 12 classes (culture, economy, entertainment, law, health, life, automotive, education, politics, sports, technology, and tourism) automatically against 360 Indonesian news data. In this study several test scenarios were conducted to see the effect of stopword removal and stemming methods on data preprocessing, the effect of mutual information in selecting features, and performance of Support Vector Machine in classifying news data. The test results showed that the data using only stemming without stopword removal, using the MI selection feature and SVM classification method produced the best results of 94.24%, compared to the other methods.
Klasifikasi Status Stunting Pada Balita Menggunakan K-Nearest Neighbor Dengan Feature Selection Backward Elimination Lonang, Syahrani; Normawati, Dwi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 1 (2022): Januari 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i1.3312

Abstract

The main problem regarding nutrition faced by Indonesia is stunting, where Indonesia is ranked fifth in the world with the largest stunting prevalence rate in 2017, which is 29.6% of all Indonesian children. Stunting is a child under five years who has a z-score value of less than -3 standard deviations (SD). Stunting has a negative impact, namely it can disrupt the physical and intellectual development of toddlers in the future. In this case, the examination of stunting status by medical personnel is still carried out manually which takes a long time and is prone to inaccuracies. This study aims to classify stunting status in toddlers by applying the K-Nearest Neighbor method using the Backward Elimination feature selection to get fast and accurate results. Based on the results of this study, the average accuracy produced by the K-Nearest Neighbor algorithm at k=5 is 91.90% with 9 attributes and the average accuracy produced by the K-Nearest Neighbor algorithm with the addition of Backward Elimination is 92.20%. with 8 attributes. These results indicate that the application of Backward Elimination can increase the accuracy value of the K-Nearest Neighbor algorithm and also perform attribute selection.

Page 41 of 119 | Total Record : 1182

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