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INDONESIA
IT JOURNAL RESEARCH AND DEVELOPMENT
Published by Universitas Islam Riau
ISSN : 25284061     EISSN : 25284053     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Engineering
Information Technology Journal Research and Development (ITJRD) adalah Jurnal Ilmiah yang dibangun oleh Prodi Teknik Informatika, Universitas Islam Riau untuk memberikan sarana bagi para akademisi dan peneliti untuk mempublikasikan tulisan dan karya ilmiah di Bidang Teknologi Informatika. Adapun ruang lingkup dalam jurnal ini meliputi bidang penelitian di teknik informatika, ilmu komputer, jaringan komputer, sistem informasi, desain grafis, pengelolaan citra dan multimedia.
Arjuna Subject : -
Articles 7 Documents
 1 
Search results for , issue "Vol. 8 No. 1 (2023)" : 7 Documents clear
Evaluate of Random Undersampling Method and Majority Weighted Minority Oversampling Technique in Resolve Imabalanced Dataset Untoro, Meida Cahyo; Yusuf, Muhammad Asyroful Nur Maulana
IT Journal Research and Development Vol. 8 No. 1 (2023)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2023.12412

Abstract

Classification is a model for making predictions based on existing data. Imbalanced data leads to misclassification or modeling errors where the data is not relevant and results in poor classification modeling. A poor classification model is caused by imbalanced data in the classification label, and there is a need for data balancing as a solution to resolve this issue. The methods used to handle data imbalance are Random Undersampling and MWMOTE. The goal is to see the implementation of Random Undersampling and MWMOTE working well in addressing the imbalanced dataset and to know the performance and accuracy in modeling. The dataset used is an open source dataset from Kaggle consisting of Diabetes data, Bank Turnover data, Stroke data, and Credit Card data with various data ratios, with the goal of addressing the problem of imbalanced data. Model evaluation was performed using the confusion matrix and decision tree algorithm by looking at the precision, recall, f-measure, and accuracy values from the Random Undersampling and MWMOTE methods. Random Undersampling can address the problem of imbalanced data with a precision of 76.28%, recall of 76.74%, f-measure of 76.48%, and accuracy of 76.21%. MWMOTE can address the problem of imbalanced data with a precision of 86.04%, recall of 87.30%, f-measure of 86.66%, and accuracy of 86.61%. It can be concluded that the MWMOTE method is better than the Random Undersampling method because the average evaluation of the confusion matrix of the Random Undersampling method is smaller than the MWMOTE method.
The Study Program Selection System: Integrated Analytical Hierarchy Process (AHP) and Technique For Others Preference by Similarity to Ideal Solution (TOPSIS) Approach Erlina, Marni; Okfalisa, Okfalisa
IT Journal Research and Development Vol. 8 No. 1 (2023)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2023.13562

Abstract

The study program selection in several high schools or madrasah aliyah (MA) in Riau province is conducted manually. The initial survey found that the study program is commonly chosen by following the friend’s preference and parents’ option instead of their knowledge capability and desire. As a reflection, many students fail to adhere to the school subjects, obtain unsatisfactory results, and even change their study program. Therefore, this paper aims to assist students in altering the appropriate study program by considering students' capabilities, talents and interests by developing a multi-criteria decision support system (DSS). This DSS employs the integrated AHP approach for criteria weighting and TOPSIS for ranking alternatives. Herein, seventy students' data from grade ten MAN 2 Kuantan Singingi grows into this case study. The automation system analysis is executed through the web base DSS system using PHP programming language and MySQL database. As a result, AHP calculates the significance values of the criterion whereby the student interest score values at 0.34, academic report, potential academic test, physiological test, Pre-Test/Post-Test, interview scores, and teacher recommendation scores at 0.21, 0.14, 0.11, 0.09, 0.06, and 0.05, respectively. Subsequently, TOPSIS ranks the students according to the assessment and criteria weighting based on the standard requirement of study program in Mathematics and Science program (MIPA) and Social Science program (IIS). The DSS study program selection application has been tested using the Blackbox and User Acceptance Test (UAT) methods. Both of these approaches indicate that this application is functionally approved and capable of aiding the users in the optimal study program selection, with 81.9% agreement. In a nutshell, this DSS has successfully recommended the optimum study program per the students’ talents, interests, and capabilities and provided the direction development of students’ expertise area for the next level of education.
Corn Leaf Diseases Recognition Based on Convolutional Neural Network Mutia Fadhilla; Suryani, Des; Labellapansa, Ause; Gunawan, Hendra
IT Journal Research and Development Vol. 8 No. 1 (2023)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2023.13904

Abstract

Maize or known as corn is one of the most important agricultural commodities in Indonesia beside rice. Indonesia is located in a tropical area which has high rate of rainfall and humidity which makes it easy for fungi and bacteria that caused plant disease to thrive. It could be a threat which is a decrease of corn harvest due to plant diseases. To prevent this, a deep learning approach can be implemented to recognize plant diseases automatically based on visual pattern on leaves. In this study, we proposed a CNN-based model for corn leaf diseases recognition. Based on the results, the proposed method has great performance which accuracy score of 93%. Besides that, the proposed method achieved up to 100% precision and recall, and up to 99% F1 score.
Employee Daily Report Application Using Flutter Framework (Case Study: PT. Planet Selancar Mandiri) Setiawan, Panji Rachmat; Fahturrahman, Rizki; Fadhilah, M Rizki
IT Journal Research and Development Vol. 8 No. 1 (2023)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2023.14058

Abstract

Planet Surf Retail company is a company that moves under PT. Planet Selancar Mandiri management has the first Planet Surf store located at Galleria Shopping Mall, Jogjakarta, since 1997 and still operates. Planet Surf has 54 stores spread across 31 cities throughout Indonesia and continues to grow to meet customer fashion needs. Each store has one leader and eight to ten employees. Nowadays, Planet Surf still uses third-party applications to help their jobs daily. The employees report their activity, employment, and progress using third-party applications, and the leader sees it. But the problem is third-party applications can not organize their report by name, date, and category. It makes there a condition that the leader misses seeing employees' reports, employees find it hard to report their activities, and misunderstandings between employees and the leader. In this research, the Author tries to develop an Android application to see if it can help employees and leaders finish their jobs. Features from the Application are daily reports, job reports, and progress reports, and the leader can create reports for all employees.
Selection of Tourist Destinations in the Thousand Islands (Kepulauan Seribu) Based on the Preference Value of the Simple Additive Weighting Method Khasanah, Fata Nidaul Khasanah
IT Journal Research and Development Vol. 8 No. 1 (2023)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2023.10967

Abstract

One of the potentials that can improve the economy of local communities is development in the tourism sector. Kepulauan Seribu is an archipelago area in the north of Jakarta, this area has tourism potential in the form of a cluster of islands. This group of islands has different characteristics to be used as a tourist attraction, including marine tourism, historical tourism and nature reserve tourism (conservation). Islands that have historical tourism potential are the reason for conducting research related to the selection of tourist destinations in the Kepulauan Seribu, such as Kelor, Onrust and Cipir island. The obstacles of the community in finding the right tourism potential are still lacking information from the aspects of attractions, accessibility and facilities. To assist tourists in choosing a place, a decision support system is needed that can be completed using the Simple Additive Weighting method. There are five assessment criteria including scenery, photo spots, transportation, toilets and places to eat/resto. Determination of weights on criteria using a statistical approach from the questionnaire results. The result of the preferred tourist recommendation preference value is the island of Kelor because there are seven highest scores obtained by the island compared to Onrust and Cipir island.
Restful API Security Using JSON Web Token (JWT) With HMAC-Sha512 Algorithm in Session Management Dalimunthe, Syabdan; Hasri Putra, Emansa; Fadhly Ridha, Muhammad Arif
IT Journal Research and Development Vol. 8 No. 1 (2023)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2023.12029

Abstract

Information systems are technologies that can help work systematically. However, the existing systems or applications are not yet integrated with one another, making many processes have the same function on different systems, for example the authentication process is built using the web service concept. Integration or interoperability of information system software involving various components, which may create gaps that can disrupt system security. In this study, security has been implemented in web services using JSON Web Token (JWT) with the HMAC-SHA512 algorithm which is stored in browser cookies. From the research results, this concept is very suitable to be applied to applications or information systems on different platforms that use the same service, JWT tokens are also successfully stored in browser cookies. In addition, a comparison was also made between the HMAC-SHA512 and HMACSHA-256 algorithms and in the final result it was found that the total time difference was 185 ms and the average time difference was 6.17 ms. It can be concluded that the HMAC-SHA512 algorithm is 0.9861% faster than the HMAC-SHA256 algorithm.
Forecasting Simcard Demand Using Linear Regression Method Sitompul, Monica; Hasan, Mhd Arief; Devega, Mariza
IT Journal Research and Development Vol. 8 No. 1 (2023)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2023.12202

Abstract

The purpose of this research is to get a prediction of how package card growth will be based on sales data from SINAR E-XIX CELL. The method used for this forecasting is linear regression, based on the number of card packs sold which is the causal variable. The accuracy of predictions is carried out using Python based on the results of research conducted with data on simcard sales over a period of two years, it was found that in the following year the number of growth in demand for sim cards in the coming year has decreased, but there is one card that has experienced an increase in the number of growth in the following year. which will come. Forecasting using Linear Regression can be said to be classified as very well based on using python. After doing the forecasting it can be concluded that in the next few years the demand for cards will be less.

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