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)
Articles
47 Documents
Search results for
, issue
"Vol 4, No 4 (2020): Oktober 2020"
:
47 Documents
clear
<![CDATA[Implementasi Metode Simple Additive Weighting Pada Aplikasi Penentukan Karyawan Terbaik ]]>
<![CDATA[Wowon Priatna]]>;
<![CDATA[Joniwarta Joniwarta]]>;
<![CDATA[Rinaldi Tunnisia]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30865/mib.v4i4.2293
<![CDATA[Election of the best employees is an important aspect of employee performance management in a company because it produces useful information for employee administrative decisions such as promotions, awards, and other decisions. Making the best employee selection not only selects and determines the right employees, but it is also important for managers to plan mature policies in motivating and developing potential employees. The problem with choosing the best employees in company agencies is the difficult decision making by managers in determining who the best employees are really worthy because of limited time and the number of employees and work that must be done by managers so that the best employee implementation is only chosen by the manager and assessment. The criteria are ignored which causes the assessment results to be subjective. One of the methods built to solve problems in the best employee decision making is done by using the Simple Additive Weighting (SAW) method, which is then ranked for the best alternative in the form of employee assessment scores. In this study, the implementation of SAW used 5 criteria to determine the best employees, namely skills, personality, initiative, attendance and loyalty. The calculation results from the implementation of the SAW method are used as a reference for designing the best employee determination application. The system design uses the Unified Modeling Language (UML) and builds applications with PHP programming and MySQL databases.]]>
<![CDATA[Analisis Kepuasan Alumni Terhadap Pelayanan Akademik dengan Metode Importance Performance Analysis Berbasis Web (Studi Kasus: Universitas CIC) ]]>
<![CDATA[Marsani Asfi]]>;
<![CDATA[Kusnadi Kusnadi]]>;
<![CDATA[Kristianto Kristianto]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30865/mib.v4i4.2343
<![CDATA[Increasing development of information technology and competition among tertiary institutions, analysis quality of academic services in the competitive era such as now is an important thing for university to do. The purpose of this research is to build a web-based computer system for analyzing alumni satisfaction with the quality of academic services at CIC University, the sample data used were 31 Alumni CIC University who graduates in 2019. The analytical method used was Importance Performance Analysis method, this method is an analysis technique which is used to find out which attributes have a big influence on satisfaction, where the measured attributes will be grouped in 4 quadrants. The results of this research is alumni satisfaction analysis systems for academic services at CIC University with Importance Performance Analysis method. The results of the system test of 31 alumni sample data assessing 9 attributes of academic services at CIC University, obtained 33.33% or 3 attributes included in Quadrant I which means that attributes are recommended to be improved. 11.11% or 1 attribute included in the Quadrant II, it mean that attribute has succeeded in satisfying the Alumni and its performance must be maintained. 22.22% or 2 attributes are in the Quadrant III category, it mean that atrributes have a low priority to be improved. While in Quadrant IV there are 33.33% or 3 attributes, it mean that these attributes have good performance, but are not considered important by Alumni]]>
<![CDATA[Penerapan Algoritma K-Means Untuk Pengelompokkan Penyakit Kronis pada Warga Lansia (Studi Kasus Pada: Posyandu Lansia RW 07) ]]>
<![CDATA[Utomo, Wargijono]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30865/mib.v4i4.2410
<![CDATA[Health is very valuable for all humans, anyone can experience health problems, especially for the elderly. Posyandu elderly RW 07 Pulogebang sub-district is one of the health services available for elderly residents. One of the government's efforts to deal with health problems is by establishing posyandu for elderly residents, considering how elderly people are vulnerable to health problems. At this time, health problems have the potential to attack people who are elderly, and have a history of chronic disease and a weak immune system, more likely to develop disease. In order to provide proper treatment, the elderly posyandu officers classify elderly people who have a history of chronic disease so that they can provide appropriate education and treatment. The data collection and counseling methods carried out by the elderly posyandu are still random and take turns with elderly residents in RW 07, Pulogebang sub-district. However, this method has the risk of being less accurate with the resulting data, because each resident has a different history of disease. Therefore we need an analysis of the health data of the elderly, so that it can be seen the distribution of people who have a history of chronic disease. One solution is to use data mining. So that in this study the clustering technique was used using the K-Means algorithm to classify patients with chronic disease in the elderly residents of RW 07, Pulogebang Village.]]>
<![CDATA[Klasterisasi Mineral Batuan di Lapangan X berdasarkan Data Spektral menggunakan K-Means Clustering ]]>
<![CDATA[Pane, Sulaiman Abdullah]]>;
<![CDATA[Sihombing, Felix Mulia Hasudungan]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30865/mib.v4i4.2352
<![CDATA[Technology continues to be applied in the field of geology in various branches of science, one of which is the use of machine learning methods which are included in artificial intelligence technology. Machine learning methods able to identifying rock minerals. Rock mineral clustering is carried out to identify the distribution of the optimal number of mineral groups based on geological information held in rock drilling results data during the geological exploration stage in the Manjimup region, Western Australia. Identification of rock minerals through clustering is carried out using unsupervised machine learning with the K-Means clustering method. The data used in this research are data from the measurement of the electromagnetic spectrum in the form of Thermal Infrared (TIR) spectral data derived from rock drilling results. The spectral data used consisted of 341 parameters so that the input dimension was reduced to reduce computational complexity using Principal Component Analysis (PCA) into two-dimensional data so able to visualized more easily. Based on the evaluation results, the optimal number of rock mineral groups through the results of clustering using K-Means based on geological information is 3 groups of rock minerals]]>
<![CDATA[Analisis Usability Pada Implementasi Sistem Pengelolaan Keuangan Masjid Menggunakan USE Questionnaire ]]>
<![CDATA[Fachruddin, Fachruddin]]>;
<![CDATA[Pahlevi, Muhammad Riza]]>;
<![CDATA[Ismail, Muhammad]]>;
<![CDATA[Rasywir, Errissya]]>;
<![CDATA[Pratama, Yovi]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30865/mib.v4i4.2520
<![CDATA[The financial management of mosques with the use of technology can make financial data more organized, filed neatly and transparently. Moreover, financial reports are data that must be accounted for in order to be trusted by the public. However, it is necessary to know how good a financial management system is. By using the USE Questionnaire we can find out that an application can still run in accordance with applicable business processes without changing the data flow and some rules and reports that have been running previously. The need to analyze usability testing on financial applications is to support automatic and computerized mosque financial management and is considered very good in user testing. This study resulted in an average rating for the "Usefulness" instrument, the "Ease of Use" instrument, the "Ease of Learning and Satisfaction" instrument, which scored well above 93%. The “Usefulness†instrument received an average of 99.00%, the “Ease of Use†instrument received an average of 94.55%, the “Ease of Learning and Satisfaction†instrument received an average of 93.82%. Thus it can be stated that the mosque financial application built for mosque management is able to meet good criteria in the rules of the USE Questionnaire method.]]>
<![CDATA[Identifikasi Bawang Merah dan Bombay dengan Pendekatan Radial Basis Function Neural Network (RBFNN) ]]>
<![CDATA[Agusriandi, Agusriandi]]>;
<![CDATA[Elihami, Elihami]]>;
<![CDATA[Widiawati, Wilda]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30865/mib.v4i4.2334
<![CDATA[A fact that identification in a human knowledge is very important role. Identification is able to summarize the knowledge, so it is easy to understand. Therefore, the classification of leek or red onion is an interesting study because the similarity of physical appearance of morphology between these two commodities is difficult to distinguish directly. This research tries to detect the difference between Bombay onion and red onion by using neural network with RGB color feature extraction method and gabor filter. The results of the detection are able to classify the types of onions, whether the onion is included in the type of leek or red onion. Many methods can be used to perform classification, one of which is Radial Basis Function Neural Network (RBFNN). After performing simulation with Matlab program, 100 images that become test data can be recognized perfectly. ]]>
<![CDATA[Implementation of TF-IDF Method and Support Vector Machine Algorithm for Job Applicants Text Classification ]]>
<![CDATA[Luthfi, Muhammad Faris]]>;
<![CDATA[Lhaksamana, Kemas Muslim]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30865/mib.v4i4.2276
<![CDATA[Tens of thousands of people are applying for job in PT. Telkom each year. The goal of the recruitment process is to get new employees which can fit PT. Telkom's working culture. Due to the high number of applicants, the recruitment process takes a lot of time and affecting higher cost to spend. We're proposing a popular combination of Term Frequency-Inverse Document Frequency (TF-IDF) as the extraction method and Support Vector Machine (SVM) as the classifier to filter the applicants' interview text. SVM generally produces better accuracy in text classification compared to Random Forest or K-Nearest Neighbors (KNN) algorithm. However, TF-IDF has several developments to improve its flaws, one of them is Term Frequency-Relevance Frequency (TF-RF). As a comparison, in this study we use three extraction methods: TF only (without IDF), TF-IDF, and TF-RF. We use interview texts from PT. Telkom as the data source. The results of combination SVM with TF-IDF can produce 86.31\% of accuracy, with TF only can produce 85.06\%, and with TF-RF can produce 83.61\% of accuracy. The results show extracting method TF-IDF can still outperform TF-RF in term of accuracy.]]>
<![CDATA[Implementasi Metode One Time Password pada Sistem Pemesanan Online ]]>
<![CDATA[Nani Sarah Hapsari]]>;
<![CDATA[Yenni Fatman]]>;
<![CDATA[Isbandi Isbandi]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30865/mib.v4i4.2195
<![CDATA[The most commonly used security system in the authentication method is the password. The ease of implementation is a major factor in the use of password-based systems and the use of insecure networks is still a threat for some applications, for example on this online ordering website based application. Where the seller must register in advance to be able to place an order. Therefore, it is necessary to have a mechanism to prevent the negative impact of various security attacks, one of which is by implementing a two factor authentication system, it can be built using a combination of username and password and validated ownership with dynamic passwords one time password. One method for generating One Time Password (OTP) is Time-based One Time Password (TOTP), this method generates a dynamic password that changes following a specified time lag. Where the password is generated through the Secure Hash Algorithm 256 (SHA-256) encryption process with the help of a pseudo random number generator that produces a 6-digit hexadecimal value. The results of the system testing at the beginning to the end of the system testing are the application of scenarios that obtain test results in the form of outputs and assessments with a range of values around 95% - 100%. The average results achieved are successful and appropriate based on the design carried out.]]>
<![CDATA[Analisa Data Mining Menggunakan Frequent Pattern Growth pada Data Transaksi Penjualan PT Mora Telematika Indonesia untuk Rekomendasi Strategi Pemasaran Produk Internet ]]>
<![CDATA[Harpa Erasmus Simanjuntak]]>;
<![CDATA[Windarto Windarto]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30865/mib.v4i4.2300
<![CDATA[Utilizing a lot of stored sales transaction data can provide useful knowledge in making policy and business strategy for PT Mora Telematika Indonesia. To realize the things can be applied with the Market Basket Analysis. Association Rule is a data mining technique which is a procedure in the Market Basket Analysis to find the knowledge of consumer purchase patterns. This pattern can be an input in making business policies and strategies. A pattern is determined by two parameters, which are support (supporting value) and confidence (value of certainty). In this study, the Market Basket Analysis used a Frequent Pattern Growth (FP-Growth) algorithm to find patterns by implementing TREE data structures or called FP-Tree. One of the patterns resulting from the analysis of data on sales transactions in the period of January 2018 to April 2018 is 7 Association rules with the highest lift ratio value is if there is an installation of OxygenHome 25-Super Double Then there will be installation OxygenHome 15-Super Double with elevator ratio 4.59%, support value of 3,125%, and confidence value 0.67%.]]>
<![CDATA[Pemanfatan Arima Untuk Prediksi Harga Emas Dalam Sistem Rekomendasi Trading Gold Option ]]>
<![CDATA[Yuliana Melita Pranoto]]>;
<![CDATA[Reddy Alexandro Harianto]]>;
<![CDATA[Iswanto Iswanto]]>
<![CDATA[ JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020 ]]>
Publisher : <![CDATA[STMIK Budi Darma ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30865/mib.v4i4.2246
<![CDATA[In gold option trading, it is necessary to analyze both fundamental and technical data. In this study technical analysis is used to predict Gold Prices to help traders in making decisions. ARIMA is a method that completely ignores the independent variables in forecasting and is able to be a solution to predict gold prices and is used for the gold trading recommendation system. This is evidenced by the validation of high MAD = 16.93, MSE = 453.00, MAPE = 1.13%. And validation is low MAD = 12.23, MSE = 237.54, MAPE = 0.83%. And validation low MAD = 16.76, MSE = 576.32, MAPE = 1.12%. The results of the recommendation system from the ten trials predicted by Arima are recommended. When compared to the price in the field the target profit is 7% per week from ten experiments if on average the profit has exceeded the target.]]>
