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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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Penerapan MOORA pada Evaluasi Kinerja dalam Mengefektifkan Biaya Operasional Arridha Zikra Syah; Yessica Siagian
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.v5i3.3112

Abstract

Sales performance evaluation is a stage in conducting an examination and assessment of information seeking performance or work results of employees / workers in the sales field of a company, this is done in an effort to streamline the company's operational costs because a salesperson is the peak in the achievement and turnover of an operational cost. company, carried out by a salesperson where a salesperson certainly sells products produced by the company or organization with a predetermined sales level, so it is necessary to conduct an assessment or evaluation of sales performance in order to appoint and find out the quality level of sales performance, to reward good sales performance will increase motivation and enthusiasm for sales work achievement so as to be able to streamline operational costs, a systemized selection is made using the MOORA (Multi-Objective Optimization On The Basis Of Ratio Analysis) method. in measuring sales performance evaluation so that the implementation process is more structured and runs honestly and fairly. The results obtained in the study that alternative A1 is a sales that has the best performance with a value of 0.546616.
Pengaruh Text Preprocessing terhadap Analisis Sentimen Komentar Masyarakat pada Media Sosial Twitter (Studi Kasus Pandemi COVID-19) Syifa Khairunnisa; Adiwijaya Adiwijaya; Said Al Faraby
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.v5i2.2835

Abstract

COVID-19 is a pandemic that is troubling many people. This has led to a lot of public comments on Twitter social media. The comments are used for sentiment analysis so that we know the polarity of the sentiment that appears, whether it is positive, negative, or neutral. The problem when using twitter data is that the tweet data still contains many non-standard words such as abbreviated writing due to the maximum limitation of characters that can be used in one tweet. Preprocessing is the most important initial stage in sentiment analysis when using Twitter data, because it affects the classification performance results. This study specifically discusses the preproceesing technique by performing several test scenarios for the combination of preprocessing techniques to determine which preprocessing technique produces the most optimal accuracy and its effect on sentiment analysis. Feature extraction using N-Gram and word weighting using TF-IDF. Mutual Information as a feature selection method. The classification method used is SVM because it is able to classify high-dimensional data according to the data used in this study, namely text data. The results of this study indicate that the best performance is obtained by using a combination of cleaning and stemming; and normalization of words, cleaning, and stemming with the same accuracy of 77.77%. the use of unigram results in higher accuracy compared to bigram. Mutual Information is able to reduce overfitting problems by reducing irrelevant features so that train and test accuracy is quite stable
Implementasi Metode SMARTER Untuk Rekomendasi Penerima Bantuan Raskin Masa Covid 19 Julfikar Rahmad; Volvo Sihombing; Masrizal Masrizal
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.v5i2.2914

Abstract

The problem of poverty is a classic problem that occurs in every country, both developed countries and developing countries like Indonesia. In every country, there are many programs carried out by the government to overcome the problem of poverty, one of which is the RASKIN program carried out by the Indonesian government. The method used to complete this research is SMARTER (Simple Multi Attribute Rating Technique Exploiting Ranks). During the Covid 19 pandemin, which is currently happening, various kinds of assistance are needed for middle and lower class people in rural areas, thus to distribute assistance, assistance distribution techniques are needed so that it reaches the right people. The SMARTER method was chosen because it is a form of decision support model used in decision making with multi attributes that will be used to solve decision-making problems. The research was conducted in Sei Beluru Village, Meranti District, Asahan Regency. In Sei Beluru Village, several criteria were obtained from direct observation of the field, namely the area of the house floor, the type of floor of the house, the type of house wall, the toilet facilities, the source of drinking water, lighting, materials. fuel used, frequency of eating, ability to buy meat, ability to buy clothes, ability to seek treatment, monthly income, education of the head of household, ownership of assets. Decision support systems using the Smarter method are able to analyze data on people who are entitled to receive Raskin assistance. The results obtained from this study are that from several prospective recipients of Raskin assistance with the specified criteria, it is found that the most prioritized alternative has the highest value of 0.603 using the Smarter method.
Temporal Prediction on Students’ Graduation using Naïve Bayes and K-Nearest Neighbor Algorithm Ahmad Marzuqi; Kusuma Ayu Laksitowening; Ibnu Asror
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.v5i2.2919

Abstract

Accreditation is a form of assessment of the feasibility and quality of higher education. One of the accreditation assessment factors is the percentage of graduation on time. A low percentage of on-time graduations can affect the assessment of accreditation of study programs. Predicting student graduation can be a solution to this problem. The prediction results can show that students are at risk of not graduating on time. Temporal prediction allows students and study programs to do the necessary treatment early. Prediction of graduation can use the learning analytics method, using a combination of the naïve bayes and the k-nearest neighbor algorithm. The Naïve Bayes algorithm looks for the courses that most influence graduation. The k-nearest neighbor algorithm as a classification method with the attribute limit used is 40% of the total attributes so that the algorithm becomes more effective and efficient. The dataset used is four batches of Telkom University Informatics Engineering student data involving data index of course scores 1, level 2, level 3, and level 4 data. The results obtained from this study are 5 attributes that most influence student graduation. As well as the results of the presentation of the combination naïve bayes and k-nearest neighbor algorithm with the largest percentage yield at level 1 75.40%, level 2 82.08%, level 3 81.91%, and level 4 90.42%.
Penggunaan Text Modeling Untuk Identifikasi Kesalahan Penulisan Kata Pada Teks Pidato Bupati Banggai Sulawesi Tengah Suparno, Daffa Setiawan; Rosyda, Miftahurrahma
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.v5i3.3051

Abstract

Typing errors or typography are errors made when typing a document or text, typing errors can occur due to mechanical failure or slipping of the hand or finger. Generally, typing errors are something that often occurs when someone is typing and is considered normal, but this typing error in some contexts can change the meaning of the word or even the meaning of the sentence itself, This causes the need for correction again after someone has finished typing, but the correction process is mostly still manually so the results of the correction depend on how carefully someone makes corrections and how many documents will be corrected. Therefore we need a system that can make corrections quickly and accurately, the correction process can be done by various methods, one of which is using the text modeling method. In this study, the test data used 10 documents of the Banggai Regent's important speech, Central Sulawesi. The text modeling method can be combined with other supporting methods such as word2vec, where word2vec will be used as a recommendation for corrected words. This study creates a system that can correct word errors in important speech documents of the Banggai Regent, Central Sulawesi by using text modeling and Word2Vec methods, the results obtained from the system that has been made are the system has good performance and gets maximum test results
Perbandingan Metode Klasifikasi Data Mining Untuk Rekomendasi Tanaman Pangan Wibowo, Merlinda; Ramadhani, Rafian
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.v5i3.3086

Abstract

Determination of the right food crops needs to be done to improve the community's economy in the agricultural sector. The use of traditional cropping patterns needs to be changed by utilizing information technology. The utilization of data from local governments can be used to assist in providing recommendations for types of food crops by processing them with several data mining methods. This method can extract information to find patterns and knowledge from the data. The classification method approach is used as a grouping of data based on data attachment to sample data. This study uses several classification methods, namely Naïve Bayes, Decision Tree, Support Vector Machine (SVM), Neural Network, Random Tree, Random Forest, dan K Nearest Neighbor (KNN). These methods were successfully compared to find out which method is the best to help recommend appropriate and accurate food crops based on the results of the classification performance of each method. Random Tree was chosen as the best method for the results of this performance comparison using discretization and normalization methods at the pre-processing stage of the data. It can be seen based on the results of the Accuracy, Precision, Recall, and F1-Score values on the use of discretization of 98%, respectively. Meanwhile, normalization showed that the results of the Accuracy, Precision, Recall, and F1-Score values are 99%, respectively.
Model Pengembangan Sistem Informasi Akademik Berbasis User Centered Design Menerapkan Framework Flask Python Ngantung, Ronaldo Kristoforus; Pakereng, M A Ineke
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.v5i3.3054

Abstract

Along with the rapid development of the times, one of which is in the field of information technology, this is increasingly demanding that we have to work faster. The ineffective technological development at SMK Negeri 1 Bitung makes students and teachers still using the manual system in academic activities, such as inputting grades, in providing information on school activities and so on. SMK 1 Negeri Bitung needs technology development solutions as school infrastructure. In this study, an Academic Information System was designed by implementing the Flask Python Framework technology. This study shows the performance of the system to help the process of academic activities to be better
Penerapan Metode K-Means Untuk Menganalisis Minat Nasabah Hutagalung, Juniar; Sonata, Fifin
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.v5i3.3113

Abstract

Insurance is a mechanism of protection or protection from the risk of loss by transferring the risk to another party. Sometimes a product that has just emerged becomes a product that is superior in terms of sales, so that interest in a product is not absolutely measured from the year the product was released. The constraint factors include the marketing of the product when it was launched. Offering products with low premiums along with the benefits that customers want. However, insurance companies still have difficulty in classifying superior products that are in great demand by prospective customers. For this reason, a technique for grouping insurance products is needed to make it easier for companies to see superior products and choose products that suit the needs of their customers. Analyzing and processing data using the K-Means method in the clustering of insurance products is the aim of this study. The application of the K-Means algorithm is to help calculate the purity value from the results of the clustering carried out so that the clustering of insurance products is in accordance with the needs of its customers. The application of the K-Means method with clustering techniques for data mining produces information on insurance products that are more attractive to potential customers. This is very appropriate in grouping data types because it is easier to implement and its application can filter quickly and precisely. Calculations using the K-Means method with a data sample of 55 customers obtained 3 clusters, namely cluster 1 for fire insurance which has 30 customers, cluster 2 for accident insurance 24 people and cluster 3 for health insurance 1 person.
Diagnosa Dini Penyakit Mata Menerapkan Metode Case Based Reasoning (CBR) Prasetyo, Dwi Yuli; Rianto, Bayu; Rais, Muhammad Sandi; Suwanti, Nurita
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.v5i2.2779

Abstract

The eye is a sense organ found in humans. The eye has the ability to adjust the amount of light that enters, focus attention on objects near and far and produce a continuous image and is conveyed to the brain. Distractions that cause damage to the eyes, can occur due to eye fatigue, lack of sleep, exposure to dust, too long in front of the computer and so on. This study aims to analyze and design an expert system for early diagnosis of diseases of the eye that includes disease information, both symptoms and solutions, and plays a role in replacing and mimicking the reasoning process of an expert in solving specification problems. The method used for reasoning is case base reasoning (CBR) and the results of the study are an expert system for early diagnosis of computerized eye diseases that can be used to provide useful information in diagnosing disease
Analisa Perbandingan Performansi Hot Standby Router Protocol (HSRP) dengan Gateway Load Balancing Protocol (GLBP) Pada Router Spoke DMVPN Claudia, Michelle; Rifqi, Muhammad
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.v5i2.2846

Abstract

The use of internet connections to develop Virtual Private Network (VPN) lines in companies has been massively applied. An example is the use of Dynamic Multipoint VPN (DMVPN) technology from Cisco, which can connect Spoke or branch offices through HUB or data centers. Besides requiring a secure network, companies also need high network availability. One of them is by using the redundancy method in order to minimize downtime when device damage occurs. In this research, the spoke router will apply two redundancy methods by Cisco, which are Hot Standby Router Protocol (HSRP) and Gateway Load Balancing (GLBP). This research aims to compare the QoS performances and downtime between the two protocols in order to discover the suitable method for DMVPN networks at branch offices. The test scenario is conducted on the GNS-3 simulator using the File Trasnfer Protocol (FTP) service. The obtained test result shows that the HSRP throughput value is smaller from the GLBP with a difference of 0.20%, the increase in the average delay of the HSRP is smaller from the GLBP with a difference of 1.07%. The HSRP data transfer time is faster than GLBP with a difference of 1.49%, and HSRP downtime is 4.13% faster than GLBP. The conclusion is that a suitable redundancy solution for spoke router using the HSRP method

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