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Jurnal CoreIT

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Published by Universitas Islam Negeri Sultan Syarif Kasim Riau

ISSN : 2460738X EISSN : 25993321 DOI : -

Core Subject : Science,

Computer Science & IT

Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi published by Informatics Engineering Department – Universitas Islam Negeri Sultan Syarif Kasim Riau with Registration Number: Print ISSN 2460-738X | Online ISSN 2599-3321. This journal is published 2 (two) times a year (June and December) containing the results of research on Computer Science and Information Technology.

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Articles 8 Documents

Search results for , issue "Vol 8, No 2 (2022): December 2022" : 8 Documents clear

Analysis and Design of Information Systems for Lecturer Performance Reports at Jambi Muhammadiyah University Kurniawansyah, Kevin; Marthiawati. H, Noneng; Sari, Anita Puspita
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 8, No 2 (2022): December 2022
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

In a tertiary institution, the existence of lecturers is needed to carry out the tridharma activities of higher education and it is the responsibility of the lecturers themselves. Higher Education Tridharma covers Education, Research and Service. There are several problems that researchers see related to the performance of lecturers, especially for the University of Muhammadiyah Jambi Higher Education. So far, the processing of lecturer performance data at the University of Muhammadiyah Jambi is carried out conventionally, namely inputting data into Microsoft Excel by the admin on duty and additional files that have been submitted by each lecturer are simply stored on the computer without a data center or centralized data storage. . The purpose of this study is to analyze and design a lecturer performance report information system that is able to simplify business processes, use lecturer performance reports according to needs and process lecturer performance data which includes identity data, lecturer tridharma data, and other supporting data more effectively and efficiently by system prototyping method that produces a web-based lecturer performance report information system at the Muhammadiyah University of Jambi to overcome existing problems

Academic Information Service Chatbot Using HMM and AIML Affandes, Muhammad; Pizaini, Pizaini
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 8, No 2 (2022): December 2022
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

UIN Suska Riau campus led to an escalation amount of data and information that must be maintained, such as academic information. UIN Suska Riau is responsible for managing and providing academic information to students and other academic communities. We can ask the Customer Care Center (C3) in Academic System or come directly to the PTIPD UIN Suska Riau office for academic questions. There still has limitations to serving existing questions submitted through C3 because officers can only serve during working hours both online and offline. Chatbots can be used to support the work of C3 officers in serving the questions asked. This system is built based on Named Entity Recognition (NER) using Artificial Intelligence Markup Language (AIML). We perform NER analysis using HMM. This study uses the contents of the academic manual as a base knowledge with 150 categories of questions and 30 answers that produce an accuracy of 55%.

Application of Triple Exponential Smoothing Method to Predict LQ45 Saham Stock Price Nurdin, Nurdin
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 8, No 2 (2022): December 2022
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

The capital market is one of the investment models that is currently growing so rapidly because there are more and more digital-based investment platforms that can be accessed using mobile smartphones. The amount of interest in investing makes many people who experience losses due to not understanding the investment risks. For this reason, it is necessary to have the ability to analyze technically based on historical data. The object of this research is LQ45 shares in three companies, Indofood Sukses Makmur Tbk (INDF), Unilever Indonesia Tbk (UNVR), and Aneka Tambang Tbk (ANTM). The method used in this research is the Triple Exponential Smoothing method which is a prediction method that utilizes the statistical analysis method. The variables used in this study are historical prices ranging from Open, High, Low, and Close prices. The stages used are the collection of 125 historical data, where the data is taken through the Google Finance financial database. Then the Triple Exponential Smoothing calculation process is carried out, the data is stored in the database and presented in the form of graphs and tables. By using the parameter values = 0.13 and = 0.87 in the end it produces a Mean margin error level of Open price -0.10681%, High price -1.1156%, Low price 1.4616%, and Close price -0.2504%. The results of the study mean the margin of error is between -0.1% to 1%. The application of Triple Exponential Smoothing can be applied to predict stock prices. This research is to help investors analyze stock price movements.

Data Warehouse Design For Sales Transactions on CV. Sumber Tirta Anugerah Syaputra, Muhammad Dwiky; Nazir, Alwis; Gusti, Siska Kurnia; Sanjaya, Suwanto; Syafria, Fadhilah
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 8, No 2 (2022): December 2022
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Many data warehouses are implemented in companies engaged in retail, CV. Sumber Tirta Anugerah is one of the paint product retail companies that has not implemented it yet. As time goes by, the sales transaction data is getting more and more difficult to process because it is still stored in Microsoft Excel. This is a serious problem in utilizing historical data to assist in making a decision. It is difficult to store sales data because the data is quite large and a lot. Based on the above problems, a data warehouse design is needed for sales transaction data. This data warehouse design uses Kimball's nine-steps method and star schema. To perform the ETL process (extract, transform, and load) using Pentaho software. In this data warehouse design, Tableau software is used to visualize the processed data into a graph and dashboard report. The result of this research is a data warehouse design using nine steps and a star schema which gets a transformation response time of 4048 MS.

Detection of Certain Objects Wearing Masks in Real Time To Prevent the Spread of the Virus (Yolov3) Kusdarnowo Hantoro; Rusdianto Rustam; Amir Dahlan
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 8, No 2 (2022): December 2022
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

A significant increase in the spread of the corona virus (COVID-19) in the community is currently happening due to people not following the health protocol rules set by the ministry of health. One of the rules is to require people to wear masks while they are outside the home. Measures need to be implemented in anticipation of situations where people do not wear masks in public spaces. Therefore, the establishment of a mask detection system is chosen as a solution in order to solve the mentioned problem above. A real-time identification system for people wearing masks is proposed to be developed in this paper. The system utilizes Yolov3 with Darknet -53 as a deep learning mask detector and OpenCV as a real-time computer vision library, so that people doing activities in a public space captured by a video can be recognized and detected when they do not wear masks . In implementing deep learning, a data set of 4000 images is divided into two classes, i.e.,2000 images with masks f or data testing purposes and another 2000 images without masks for training custom objects. The Extreme Programming (XP) method as part of the Agile Process Model is adopted for system development. Computer language support and the latest system development tools have made it possible to utilize this method in an effort to develop this system rapidly. Requirement Analysis is conducted to obtain required processes before designing system. Writing code and testing the system will be the next step before the system is declared ready to be implemented in the public space. By adopting the XP development method, all of the above steps can be implemented repeatedly until the system delivers the expected results

Level Set Interactive Segmentation on Perforated Road Image using Region Based Active Countours Method with im’4 Anike, Marleni
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 8, No 2 (2022): December 2022
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

An image will have a lot of interpretation meaning when compared to a text. However, there is nothing wrong with the original image being manipulated to achieve a certain goal. In digital image processing (PCD) there are image manipulation techniques without touching other objects, this is due to the difficulty of separating one object from another. One of the digital image segmentation techniques that is widely used for PCD and computer vision is level set. In this research, the strength of active contour will be tested which will segment area-based objects with potholes using Matlab R2016a. inner region taking into account im = 4 with imresize(mask, 8) iterations of 500.

Netflix Stock Price Trend Prediction Using Recurrent Neural Network Irani H
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 8, No 2 (2022): December 2022
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Abstract— Stocks are investments that have dynamic movements. Stock price changes move every day even hourly. With very fast changes, stock prices require predictions to be able to determine stock market projections. Predictions are used to reduce risk when making transactions. In this study, predictions of stock price trends were made using the Recurrent Neural Network (RNN). The approach taken is to perform a time series analysis using the RNN variance, namely Long Short Term Memory (LSTM). Hyperparameter construction in the LSTM model testing simulation can estimate stock prices with maximum percentage accuracy. The results showed that the prediction model produced a loss function of 0.0012 and a training time of 73 m/step. The evaluation was carried out with the RMSE which resulted in a score of 17.13325. Predictions are obtained after doing machine learning using 1239 data. The RMSE and LSTM models are calculated by changing the number of epochs, the variation between the predicted stock price and the current stock price. Computations are carried out using a stock market dataset that includes open, high, low, close, adj prices, closes, and volumes. The main objective of this study is to determine the extent to which the LSTM algorithm anticipates stock market prices with better accuracy. Code can be seen at iranihoeronis/RNN-LSTM (github.com) Keywords— Stock Prediction, Time Series, Recurrent Neural Network (RNN), Long Short Term Memory (LSTM).

Combination RC4 Algorithm and Base64 Encryption on The Least Significant Bit Method Soleman, Soleman; Budiman, Dendi; Mubaroq, Sefty
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 8, No 2 (2022): December 2022
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

Steganography is an art form of hiding data or information on a medium. Steganography was created as a way to secure data by hiding it in other media so that it is "invisible". In steganography, secret data is hidden in a carrier such as sound, image or video. Securing messages using steganography is still vulnerable to third parties because the message inserted is still the original message, so that when it is successfully deleted from the message carrier it can be immediately identified. Given these problems, the steganography method needs to be combined with other methods to strengthen the level of data security, in this case a combination of steganography and cryptography will be carried out so that the embedded message will be different from the original message. Even if the data is deleted from the user, the message cannot be known immediately. In this trial, the RC4 cryptographic method which has a symmetric key and also Base64 will be implemented in the PHP and Android programming languages using the Least Significant Bit (LSB) steganography method which will create encrypted secret messages embedded in JPG format, JPEG image media formats on each the last bit of a pixel so that the eye does not see the difference between the inserted and non-inserted images with the original image variable/result of 131.91KB after the Encryption process the amount of data is 31.92KB with very small differences so that data security is maintained without being visible to the naked eye

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Home Page

OAI Link

Editorial Team

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Contact Name Suwanto Sanjaya

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Location Kab. kampar, Riau INDONESIA

Abstract

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Abstract

Abstract

Contact Name
Suwanto Sanjaya

Contact Email
suwantosanjaya@uin-suska.ac.id

Phone
-

Journal Mail Official
coreit@uin-suska.ac.id

Editorial Address
-

Location
Kab. kampar,

Riau

INDONESIA