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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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Analisis Perbandingan Kinerja Algoritma Naïve Bayes, Decision Tree-J48 dan Lazy-IBK Indra Rukmana; Arvin Rasheda; Faiz Fathulhuda; Muh Rizky Cahyadi; Fitriyani Fitriyani
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 3 (2021): Juli 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i3.3055

Abstract

This research is focused on knowing the performance of the classification algorithms, namely Naïve Bayes, Decision Tree-J48 and K-Nearest Neighbor. The speed and the percentage of accuracy in this study are the benchmarks for the performance of the algorithm. This study uses the Breast Cancer and Thoracic Surgery dataset, which is downloaded on the UCI Machine Learning Repository website. Using the help of Weka software Version 3.8.5 to find out the classification algorithm testing. The results show that the J-48 Decision Tree algorithm has the best accuracy, namely 75.6% in the cross-validation test mode for the Breast Cancer dataset and 84.5% for the Thoracic Surgery dataset.
Aplikasi Stemming Kata Bahasa Lampung Dialek Api Menggunakan Pendekatan Brute-Force dan Pemograman C# Zaenal Abidin; Aldi Wijaya; Donaya Pasha
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i1.2483

Abstract

Lampung is one of the areas on the island of Sumatra that has the regional language and script of Lampung. In this province there are two main regional dialects, namely the dialect of fapi and the dialect of nyo. Research efforts for the preservation of the Lampung language digitally have been conducted by researchers from various Universities. The research stemming from Lampung dialects of api is based on the findings of the fact that the dictionary-based Lampung dialects of the Lampung language dialect cannot translate the affix words. Stemming of Lampung language dialects of api is worked with a Brute-force approach. In the Lampung language there are inflexional verbs and derivational verbs. Inflexional verbs are verbs formed from bases that are also categorized verbs while derivational verbs are verbs formed from bases that are categorized in addition to verbs such as nouns, adjectives, adverbs, pronouns and numerals. The purpose of this research is to (1) conduct word stemming with a Brute-force approach, (2) produce an application as a Lampung language word Stemmer dialect of api using C # programming language and online database using Firebase. The methods used in this study consisted of (1) Researchers are looking for, identifying, recording, manually typing 2000 words following the basic words of the Lampung dialect of api, (2) creating a stemming algorithm with a Brute-force approach (3) testing applications that have made. As for the result obtained is the application is able to do word stemming for words that have been identified in 2000 words and if stemming can not be done then the facility is provided to update the database used in the application to be used for stemming because the stemming application is very supportive of the application dictionary-based translation engine. The urgency of Stemming application research is to address the affix word in the Lampung language machine translation machine translation application for further research
Perancangan Web Marketplace Toko Sepatu Akshara.co dengan Sistem Rekomendasi Menggunakan Perhitungan Algoritma Apriori Dennise Gibran Manoppo; M Iwan Wahyudin; Winarsih Winarsih
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 3 (2021): Juli 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i3.3091

Abstract

In this advanced period, shoes arsse an essential requirement for practically all circles, a great deal of Online business organizations are arising and filling quickly in Indonesia, in addition to the quantity of dynamic web clients in Indonesia is expanding quickly from one year to another. Making Online business organizations contend to explore different techniques as far as advertising to draw in more individuals to purchase the items they offer to get by in the online businss market rivalry in this country, one illustration of a promoting methodology to draw in and increment public premium buys is the execution of the merchandise proposal framework in Online business. Consequently, in this investigation, an electronic Web based business will be made that can help Internet business organizations anticipate purchaser premium in a thing and afterward prescribe it to draw in more purchasers who come. This Web based business utilizes the Apriori Calculation way to deal with get more exactness in the information handling measure. The outcomes acquired from that examination are the making electronic Web based business by executing the suggestion technique showed on the "Akshara.co" framework include
Peningkatan Akurasi Klasifikasi Backpropagation Menggunakan Artificial Bee Colony dan K-NN Pada Penyakit Jantung Pandito Dewa Putra; Sukemi Sukemi; Dian Palupi Rini
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i1.2634

Abstract

Heart disease has ranked as the leading cause of death in the world, accounting for around 17.3 million deaths per year with some causes, as high blood pressure, diabetes, cholesterol fluctuation, fatigue, and some others which is collected on dataset. Heart disease dataset that was applied is cleveland heart disease with fourteen (14) data atribute. The method that was applied in this research was using Backpropagation algorithm on heart disease classifying, where will be combined Artificial Bee Colony and k-Nearest Neighbor algorithm for features or atribute choose due to this technique can increase classifier model accuracy which is produced as much as 94,23%.
Analisis Metode Analytic Hierarchy Process Dalam Sistem Pendukung Keputusan Pemilihan Taruna Berprestasi Lisda Juliana Pangaribuan; Tiara Sylvia; Liber Tommy Hutabarat
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i1.2758

Abstract

Process of selecting outstanding cadets is a multi-criteria problem, so get objectively achieving cadets, a decision support system with multiple criteria is needed. As an appreciation for achievement, a few universities provide scholarships for high achieving students. However, a few universities choose outstanding students based only on GPA. This study aims to analyze the application of the Analytic Hierarchy Process (AHP) method in the Decision Support System for the selection of cadets so that objectively achieving candidates can be determined. Because the number of prospective cadets with many achievements, Random Index (IR) value is obtained from IR table > 15. This study uses 4 criteria, namely the GPA criteria with eigenvectors = 0.111, Scientific works with eigenvectors = 0.563, extracurricular (Achievement) with eigen vector = 0.246 Foreign language proficiency with eigenvector = 0.08. From the research results obtained the value of CR = -0,987 <= 0.1, then the value of the comparison criteria is consistent. The results showed that there were differences in the ranking of outstanding cadets at the Medan Aviation Polytechnic according to the GPA and the AHP method
Autoregressive Integrated Moving Average (ARIMA-Box Jenkins) Pada Peramalan Komoditas Cabai Merah di Indonesia Ridha Maya Faza Lubis; Zakarias Situmorang; Rika Rosnelly
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2927

Abstract

Chili is one of the main staples in making a dish and chili is one of the values in a commodity that has superior value, the price of chili often experiences price fluctuations or what is known as the price which is always changing. data taken from BPS (Central Bureau of Statistics) data nationally from January 2001 to December 2015 data, this study also aims to be able to predict national chili prices which will later be used in research, namely discussing the Autoregressive Integrated Moving Average (ARIMA) method. In this study, the identification of the model was carried out using two tests, namely the stationarity test and the correlation test. The stationarity test is the Augmented Dickey-Fuller (ADF) test, the Philips-Perron (PP) test and the Kwiatkowski-Philips-Schmidt-Shin (KPPS) test using Minitab 9.The chili commodity is a very important commodity in the Indonesian economy, because In terms of consumption, chilies have a very significant market share, which can be seen from data from the Central Statistics Agency (BPS) with an inflation weight value of 0.35%. From the research, it was found that for the selection of the best method, namely ARIMA (3,1,0) because it has the smallest MSE value and the forecasting results for the next 12 periods in January 2016 ranged from Rp. 11,868.2 to Rp. 28,315.5 and so on until December 2016.
Implementasi Metode Case Based Reasoning Untuk Mendeteksi Kerusakan Televisi Sursih Wulandari; Marnis Nasution; Mustafa Haris Munandar
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2952

Abstract

The process of deteriorating television should indeed be done by an expert who is a television expert himself, but because television is a tool that is no longer common for people to know him, many people also have television in their respective homes. Even for television repairs, it is quite expensive, so some people who have televisions can do television maintenance at home. The lack of knowledge possessed by the community can lead to wrong handling of television maintenance / maintenance and this has a fatal impact. Hopefully the existence of this system can help the community in diagnosing the damage to their televisions. In that case they need not bother to call for repairmen or bring in a television repair shop. Here the authors provide solutions to solve the problems that often arise on television. In this study, it discusses how to care for television officers. The research objective is to analyze a desktop-based expert system program that contains the knowledge of an expert / doctor whose truth is believed to have the ability to be able to diagnose the disease from the symptoms of damage that has been damaged by television damage quickly and precisely. The stages of research carried out in this study include literature study, data collection, system design, system creation, system testing. Case Based Reasoning is a method used to build a knowledge-based system. The source of system knowledge is obtained by collecting the handling of cases by an expert / expert. Therefore, many problems in television damage are usually due to the negligence of the television owner himself. The first step in solving a problem is by first identifying the scope of the problem to be resolved, this also applies to any Artificial Intelligence (AI) programming. The results obtained in the study for the diagnosis of conjunctivitis were the value of old cases and new cases which obtained a high weight value, namely 1 from the third case
Analisis Ward and Peppard Model Pada Strategi Bisnis dan Perencanaan Strategis Sistem Informasi Daim Azhari Parinduri; Roslina Roslina; Zakarias Situmorang
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2977

Abstract

Muslim Nusantara Al-Washliyah University is a private university that already has information system technology and information technology as an effort to improve the competitiveness of higher education. However, the existence of the existing information system is still not perfect so that work becomes inefficient. Therefore, this research was conducted to make strategic planning of information systems so as to increase the competitiveness of higher education institutions. The model used in strategic planning in this study is the Ward and Peppard model. The strategic plan is drawn up for a timeframe of 2 phases. The process begins with Internal and External Business Analysis through SWOT Analysis, Value Chain Analysis, PEST Analysis and testing of strategy results using the Profile Matching method which is the choice to provide an assessment of recommended information system applications. There are three aspects in conducting the assessment and evaluation, namely new aspects, develop and continue.
Pengenalan Pola Angka Menggunakan Pendekatan Optimisasi Sistem Kekebalan Buatan (Artificial Immune System) Prahartiningsyah, Anggari Ayu; Kurniawan, Tri Basuki
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 3 (2021): Juli 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i3.2997

Abstract

The general election in Indonesia itself still experiences technical and non-technical problems where the technical problems occur in the recapitulation of votes from sheet C1 which are still incorrectly inputted and done manually. The problem occurred with the difference in the uploaded C1 data and the data in the KPU Situng and the C1 sheet uploaded was blurry, unclear, sheet C1 which was crossed out or folded in the KPU Situng. The purpose of this research is to reduce errors in data input and change the work that is done manually to the system, create a number pattern recognition system using an Artificial Immune System optimization approach, test and analyze the work of the system by taking into account the level of accuracy, preciseness and speed in recognize number patterns. The system created to applies an artificial immune system optimization approach with the Artificial Immune System using the Randomized Real-Valued Negative Selection Algorithm algorithm.
Pengembangan Model Untuk Prediksi Tingkat Kelulusan Mahasiswa Tepat Waktu dengan Metode Naïve Bayes Qisthiano, M Riski; Kurniawan, Tri Basuki; Negara, Edi Surya; Akbar, Muhammad
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 3 (2021): Juli 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i3.3030

Abstract

Many parameters affect the timeliness of student graduation, starting from the student's interest in certain majors, the type of class chosen, to the grades for each semester obtained. This is a determining factor in how students can graduate on time or not at the end of their education. So a model is needed to predict student graduation rates on time, using alumni data whose data is obtained from several universities in Palembang City. The model used is a Naïve Bayes algorithm which serves as a model for classification. The dataset used is alumni data that has been collected from several universities, while the attributes used are the Department, College, Class Type, Temporary IP Value from semester 1 to 4, graduation year, and college generation. Then from the attributes and models used, the researcher used the Python 3 programming language and the Jupyter Notebook tools to process the prepared dataset. Furthermore, the distribution of the dataset is divided by 70% for training data and 30% for testing data. To test the algorithmic process used by researchers using K-Fold Validation. The results of this study are the accuracy of the prediction model carried out, where the accuracy results obtained from the Python 3 programming language and the Naïve Bayes algorithm are 0.8103.

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