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Jurnal Riset Informatika

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Published by KresnaMedia Publisher

ISSN : 26561743 EISSN : 26561735 DOI : -

Core Subject : Science,

Computer Science & IT

Jurnal Riset Informatika, merupakan Jurnal yang diterbitkan oleh Kresnamedia Publisher. Jurnal Riset Informatika, berawal diperuntukan menampung paper-paper ilmiah yang dibuat oleh peneliti dan dosen-dosen program studi Sistem Informasi dan Teknik Informatika.

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Articles 26 Documents

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Search results for , issue "Vol. 5 No. 3 (2023): June 2023" : 26 Documents clear

Extreme Programming Method for Integrated Service System Website Development in Rejosari Village Eka Supriyati; Muhamad Azrino Gustalika
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

The Rejosari Village Hall provides a manual letter submission service which is sometimes problematic, including when residents are about to submit an application letter, they have to come directly to the village hall office while the residents are still out of town. Apart from that, there was no media information which resulted when they were going to submit the requirements for the letters they brought were not in accordance, then from the data collection, and the letters were still in the books. Therefore we need a service system for the submission of letters. This integrated service system for residents of Rejosari Village is a web-based information system, the use of technology in the form of a website makes it easier to receive all forms of existing information. The Extreme Programming (XP) method is applied in developing this system, a software engineering process that refers to an object-oriented approach. The stages of this method start from the planning, design, coding and testing stages using black box testing with descriptive analysis techniques, which produce tests in the form of a proportion value of 96.42% and have a possible interpretation. In addition, this system can impact progress in the field of informatics in the form of information media as well as learning materials.

K-Means Binary Search Centroid with Dynamic Cluster for Java Island Health Clustering Muhammad Andryan Wahyu Saputra; Muhammad Faisal; Ririen Kusumawati
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

This study is focused on determining the health status of each district/city in Java using the K-means Binary Search Centroid and Dynamic Kmeans algorithms. The research data uses data on the health profile of Java Island in 2020. Comparative algorithms were tested using the Davies Bound Index and Calinski-Harabasz Index methods on the traditional k-means algorithm and dynamic binary search centroid k-means. Based on the test, 5 clusters were found in the distribution area, including 11 regions with very high health quality cluster 1, 24 regions with high health quality, 28 regions with moderate health quality, and 28 clusters 4 with low health quality, 45 regions, and cluster 5 with poor health quality is 11 regions, with the best validation value of DBI 1.8175 and CHI 67.7868. Overall optimization of the dynamic k-means algorithm based on binary search centroid results in a better average cluster quality and a smaller number of iterations than the traditional k-means algorithm. The test results can be used as one of the best methods in evaluating the level of health in the Java Island area and a reference for decision-making in determining policies for related agencies.

Website Evaluation of The Faculty of Industrial Technology Universitas Islam Indonesia Using the System Usability Scale Method Rafi Arribaath Alfaresy; Chanifah Indah Ratnasari
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

To maintain and improve the quality of the website of the Faculty of Industrial Technology (FTI), Universitas Islam Indonesia (UII), usability testing is performed on the website using the System Usability Scale (SUS). This study aims to evaluate usability and analyze the user experience on the FTI UII website so that the faculty can follow up on it. Respondents consisted of 41 active FTI UII students. Respondents were asked to complete scenarios on the FTI website while being watched by examiners. They then filled out the SUS questionnaire with ten statements and a Likert scale for answers. Using the SUS method, the test scores were 69.32. Based on these results, the acceptability of the FTI web is in the MARGINAL HIGH range, the adjective rating is at an OK level close to GOOD, the grade scale is in class C, and the Net Promoter Score (NPS) could be passive on website users. Based on these results, it can be concluded that the usability of the FTI UII website is acceptable to users but has not yet attained a maximum score; therefore, a user has not yet recommended the site to other users. This confirms that the FTI website requires additional enhancements.

Comparison of KNN and SVM Algorithms in Facial Image Recognition Using Haar Wavelet Feature Extraction Neneng Rachmalia Feta
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

To process all the pixels in the face image, feature extraction can be performed using the Haar Wavelet method so that it processes identifiers with lower dimensions. However, a classification algorithm must separate the distance between classes with minimal data to classify low-dimensional facial images. KNN and SVM algorithms are classifiers that can be used for facial image recognition. When classifying images, SVM creates a hyperplane, divides the input space between classes and classifies based on which side of the hyperplane the unclassified object is placed when it is placed in the input space. KNN uses a voting system to determine which class an unclassified object belongs to, taking into account the nearest neighbor class in the decision space. When classifying, KNN will generally classify accurately, resulting in some minor misclassifications that plagued the final classified image. This study aims to compare the two algorithms on image identifiers with low dimensions resulting from haar wavelet extraction. The research results obtained are facial image classification using the haar wavelet extraction method using the SVM algorithm to obtain an accuracy of 98.8%. Whereas when using the KNN algorithm, the accuracy obtained is 96.6%. The results of this study show that the SVM algorithm produces better accuracy in facial image recognition using haar wavelet feature extraction compared to the KNN algorithm. The SVM algorithm can recognize facial images even though it uses image training data with various face poses and sizes, resulting in higher accuracy.

Classification for Papaya Fruit Maturity Level With Convolutional Neural Network Nurmalasari Nurmalasari; Yusuf Arif Setiawan; Widi Astuti; M. Rangga Ramadhan Saelan; Siti Masturoh; Tuti Haryanti
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

Papaya California (Carica papaya L) is one of the agricultural commodities in the tropics and has a very big opportunity to develop in Indonesia as an agribusiness venture with quite promising prospects. So the quality of papaya fruit is determined by the level of maturity of the fruit, the hardness of the fruit, and its appearance. Papaya fruit undergoes a marked change in color during the ripening process, which indicates chemical changes in the fruit. The change in papaya color from green to yellow is due to the loss of chlorophyll. The papaya fruit is initially green during storage, then turns slightly yellow. The longer the storage color, the changes to mature the yellow. The process of classifying papaya fruit's ripeness level is usually done manually by business actors, that is, by simply looking at the color of the papaya with the normal eye. Based on the problems that exist in classifying the ripeness level of papaya fruit, in this research, we create a system that can be used to classify papaya fruit skin color using a digital image processing approach. The method used to classify the maturity level of papaya fruit is the Convolutional Neural Network (CNN) Architecture to classify the texture and color of the fruit. This study uses eight transfer learning architectures with 216 simulations with parameter constraints such as optimizer, learning rate, batch size, number of layers, epoch, and dense and can classify the ripeness level of the papaya fruit with a fairly high accuracy of 97%. Farmers use the results of the research in classifying papaya fruit to be harvested by differentiating the maturity level of the fruit more accurately and maintaining the quality of the papaya fruit.

Latent Dirichlet Allocation for Uncovering Fraud Cases on Twitter Sallu Muharomah; Chanifah Indah Ratnasari
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

Fraud is a phenomenon that continues to exist in society with a modus operandi that continues to evolve with the times. The mode of operation of fraud is continually evolving with technological advancements, globalization, and consumer behavior shifts. In today's digital age, social media is important in spreading information regarding fraud. Twitter is a social media platform that is widely used. Twitter provides easy and fast access to relevant information. As a result, to raise fraud awareness, it is critical to study the mode of operation of fraud spread on social media, particularly on Twitter. The Latent Dirichlet Allocation (LDA) approach is used in this work to classify and identify fraud issues often addressed by Indonesian Twitter users. By applying LDA modeling, this study aims to understand more comprehensively the fraudulent topics that often appear on Twitter. The research found that seven fraud topics are most commonly discussed by Twitter users in Indonesia, with the highest cohesion value of 0.491899.

Stunting Early Warning Application Using KNN Machine Learning Method Nani Purwati; Gunawan Budi Sulistyo
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

Stunting in toddlers is defined as a condition of failure to thrive due to chronic malnutrition in the long term. The problem of stunting in Indonesia is an issue that is still a concern for the Indonesian government. The prevalence of stunting in Indonesia is still relatively high, coupled with the COVID-19 pandemic, which has impacted the economic sector. For this reason, research on stunting is still a critical topic. This study aims to classify toddler stunting using the k-Nearest Neighbor classification algorithm and build a website-based early detection application for toddler stunting cases. The research results using the k-Nearest Neighbor Algorithm trial obtained a relatively high accuracy of 92.45%. Implementing an early detection system for stunting cases has proven to help health workers classify toddlers as stunted or not. This application is also helpful as an archive and facilitates data reporting. The application has eight main menus: the Puskesmas data menu, Posyandu data, toddler data, weighing, weighing results, development menu, and stunting early warning menu, which contains malnourished and stunted toddlers.

Covid-19 Social Aid Admission Selection Using Simple Additive Weighting Method as Decision Support Tyas Setiyorini; Frieyadie Frieyadie; Aditiya Yoga Pratama
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

The process of receiving Covid-19 social assistance to residents who are recorded as social aid recipients in the RT.07 RW.10 Kp. Sukapura Jaya area is still uneven. The second problem is that there is no particular mathematical calculation to determine the value of the weight of the criteria, especially for residents who are recorded as receiving Covid-19 social aid in the RT.007 RW.10 Kp. Sukapura Jaya area. The gradual decline in social aid programs so that the number that falls does not match the data of social aid recipients. This caused a polemic for RT administrators in distributing social aid programs. The decline in social aid programs does not match the number of citizens recorded. It overcomes citizens who cause social jealousy—analyzing the problems experienced by the RT management in the distribution of Covid-19 social assistance, especially the RT.07 RW.10 Kp. Sukapura Jaya area to residents who are recorded as recipients. Selecting Covid-19 social assistance recipients, especially in the RT.07 RW.10 Kp. Sukapura Jaya area. So the application of methods as decision support is needed, and it is needed to help determine the weight of particular criteria for citizens who are recorded as more in need. This study proposes a decision support method using the Simple Additive Weighting (SAW) method, which is expected to help decision-making in solving problems for selecting Covid-19 social aid recipients in the RT.07 RW.10 Kp. Sukapura Jaya community. The purpose of the study is to select residents who are recorded to receive social aid who are more in need first will get Covid-19 social aid.

Implementation of the Saw Method to Discover the Optimum Internet Service Recommendations for Online Gaming Gunawan Gunawan; Ita Yulianti; Ami Rahmawati; Tati Mardiana; Nanang Ruhyana
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

Currently, the development and use of the Internet have a more complex function so that it can change the paradigm of people's lives, including in aspects of entertainment, especially games. With the rise of numerous ISPs in Indonesia, different internet service packages are now available, particularly for gamers, such as Indihome, Biznet, First Media, and My Republic. The variety of services makes it difficult for users to choose an internet package that suits their needs. Therefore, this research aims to build a decision support system that can facilitate users in choosing the ideal internet service for gamers based on five criteria: quota, network speed, connection, cost, and the number of users using the SAW method. The data collection methods used are observation, questionnaires, and interviews. The research results obtained from data processing using the SAW method through Microsoft Excel are then implemented into a website-based program. With this program, it is hoped that it can be a tool for users in determining the service package to be purchased.

The Determination of Development Priorities Road Infrastructure at “Dinas Pekerjaaan Umum dan Penataan Ruang Kabupaten Balangan” Using AHP and Bayes Methods Haderiansyah Haderiansyah; Deni Mahdiana; Ade Davy Wiranata; Mirza Sutrisno
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

The construction industry is a significant part of the gross domestic product of any country, and its success can lead to the long-term economic and social development of lives in general. Many studies have found a positive link between public infrastructure and the economy. Infrastructure investment directly affects economic growth. Well-designed infrastructure will have long-term financial benefits. The Ministry of Public Works and Housing (Pekerjaan Umum dan Perumahan Rakyat / PUPR) has played an essential role in strengthening the monitoring and evaluation of the implementation of infrastructure development by local authorities, including making the right policies in determining infrastructure development priorities. The Analytical Hierarchy Process (AHP) and Bayes method were used in this study. First, we used AHP to derive independent weights for criteria. Then, we determined the closeness between priorities to produce a sequence of infrastructure development priorities. Based on the results, using Analytical Hierarchy Process (AHP) and Bayes Method showed that Lampihong-Panaitan, Halong-Tabuan, and Bihara-Tariwin roads are Priorities for development. Then the Wangkili-Pudak road, and finally, the Awayan-Bihara. Decision support systems using the AHP and Bayes methods can determine priorities for road infrastructure development at the Office of Public Works and Public Housing in Balangan Regency.

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Tati Mardiana

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jurnal.jri@kresnamediapublisher.com

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Journal Mail Official
jurnal.jri@kresnamediapublisher.com

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Location
Kota banjar,

Jawa barat

INDONESIA