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INDONESIA
Jurnal Riset Informatika
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.
Arjuna Subject : -
Articles 26 Documents
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Search results for , issue "Vol 5 No 3 (2023): Priode of June 2023" : 26 Documents clear
K-Means Binary Search Centroid With Dynamic Cluster for Java Island Health Clustering Muhammad Andryan; Muhammad Faisal; Ririen Kusumawati
Jurnal Riset Informatika Vol 5 No 3 (2023): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.511

Abstract

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 deficient 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
Comparison of Conventional Machine Learning and Deep Neural Network Algorithms in the Prediction of Monkey-Pox Cucu Ika Agustyaningrum; Rizka Dahlia; Omar Pahlevi
Jurnal Riset Informatika Vol 5 No 3 (2023): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i2.522

Abstract

Smallpox syndrome, also known as monkeypox, is an uncommon zoonotic viral infection brought on by the monkeypox virus, which belongs to the genus orthopoxvirus and family Poxviridae. Injury-related mortality in primates ranges from 1 to 10%. Data mining is a method for analyzing data. Deep neural networks and traditional machine learning methods are both used in the data analysis process. The Python programming language is used during the comparison procedure of this research algorithm to generate values for accuracy, f1 score, precision, recall, ROC, and AUC. The test results demonstrate that using sigmoid activation function parameters, the deep neural network algorithm's accuracy is 70.08%, F1 score is 79.18%, precision is 68.59%, recall is 62.65%, and AUC is 62.65%. In comparison to using conventional machine learning algorithms, the adagrad optimizer with learning rate 0.01 and 0.2 dropout has a higher value. The conventional machine learning model algorithm has the best xgboost, F1 score, precision, recall, and AUC scores when compared to other approaches: 64.40%, 64.45%, and 78.14%. According to these numbers, the average fairness disparity between deep neural network algorithms and traditional machine learning is 5.68%, F1 score is 13.79%, precision is 4.14%, recall is 1.75%, and AUC is 1.75%.
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): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.527

Abstract

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 have an impact on progress in the field of informatics in the form of information media as well as learning materials
The Best Employee Decision Support System Using the Analytical Hierarchy Process Method at PT ASDP Indonesia Ferry (Persero) Deny Novianti; Anggi Oktaviani; Dahlia Sarkawi; Aldyanto Aldyanto; Ahmad Faren Syahidan
Jurnal Riset Informatika Vol 5 No 3 (2023): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.454

Abstract

The selection of the best employees aims to spur employee morale in improving employee performance and dedication in the company. The selection of best employees is selected based on company criteria. PT ASDP Indonesia Ferry (PERSERO), the best employee criteria applied by the company are Work Quantity, Work Quality, Attendance, Teamwork, and Initiative. Employee assessment is carried out every month by the assessment team (Vice President (VP) and Manager). The problem faced is determining the best employees with criteria and alternatives that are calculated manually. This system is a Decision Support System (DSS) built using the Analytical Hierarchy Process (AHP) method. Previously, the evaluation process for selecting the best employees had never been done. Some of the problems encountered were the absence of an employee performance appraisal process, no appropriate selection method, and a Decision Support System (DSS) was not available that could make it easier to assess the selection of the best employees.
Application of Fuzzy C Means and TOPSIS in Warehouse Selection at PT Warung Islami Bogor Dewi Primasari; Khidir Zahid Muchtadiabillah; Freza Riana
Jurnal Riset Informatika Vol 5 No 3 (2023): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.517

Abstract

PT Warung Islami Bogor needs a warehouse to store goods that come from suppliers. Currently, the selection of warehouses is still done manually and is subjective. It is feared that this will lead to inaccuracies in renting the warehouse. So an application is needed to assist companies in choosing a warehouse. The fuzzy C-Means method can be used to classify warehouse data based on the characteristics of each group. After obtaining the next group is to make a rating of each group. One method that can be used is the TOPSIS method. The TOPSIS method can be applied to this application to rank the data warehouses that have been grouped. In the selection of this warehouse, there are several criteria. The criteria used are price, building area, distance from the head office (HO), parking area, and number of floors. The calculation process is done by dividing the warehouse data into several groups and ranking them to obtain the best recommendations. This application uses the PHP programming language with the Laravel framework—testing using a black box. Fuzzy C-Means and TOPSIS calculations show that Warehouse CCC is the best warehouse in Cluster 1 with a value of 0.797, and the Warehouse in Front of Gas Station Villa Bogor Indah is the best in Cluster 2 with a value of 0.613.
Internal Factor Analysis of Non-Performing Loans Using Multiple Linear Regression Method Muhammad Irfandi; Fitria Fitria
Jurnal Riset Informatika Vol 5 No 3 (2023): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.535

Abstract

Loans are the largest source of income from banks compared to other sources of income. To ensure bank continuity, Bank income must exist from interest on loans, reaching almost 95% of all bank activities. For companies and banks that apply loan differences, loans are receivables which are cash that is delayed in receipt. Having problem loans can weaken a bank's financial condition. In general, two factors cause problems with loans, namely internal and external factors of the bank. Bank internal factors can be controlled by banks, compared to external factors, to prevent problem loans. Therefore, in this study, an analysis of internal factors affecting problem loans was carried out. The internal factors analyzed are the things that become the process and the essential part of the loan process, which includes loan supervision, acceptance procedures, and loan guarantees. This analysis is carried out to minimize the risk of non-performing loans caused by the inner side of the organization. The method used for analysis is using multiple linear regression analysis. Multiple linear regression analysis analyzed the relationship between the three independent variables (loan monitoring, acceptance procedures, and loan guarantees) and one dependent variable (non-performing loans). Multiple linear regression analysis provides predictions of the value of the dependent variable if the value of the independent variable increases or decreases and describes the direction of the relationship between the independent variable and the dependent variable, whether each independent variable is positively or negatively related. Based on the analysis results, the influence of loan monitoring factors, acceptance procedures, and loan guarantees on problem loans can be concluded that there is an influence between loan supervision and acceptance procedures on problem loans. At the same time, there is no effect between loan guarantees on problem loans.
K-Means Clustering Method for Determining Waste Transportation Routes to Landfill Almas Nurfarid Budi Prasetyo; Maimunah Maimunah; Pristi Sukmasetya
Jurnal Riset Informatika Vol 5 No 3 (2023): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.540

Abstract

Waste is worsening in Magelang City, especially in urban areas. As a result of poorly managed waste disposal, a landfill is needed. Magelang City has a landfill called TPA Banyuurip, located in Plumbon Hamlet, Banyuurip Village, Tegalrejo Subdistrict, Magelang City. From this case, the application of the kmeans clustering method to determine the efficiency of the waste transportation route to the landfill is needed. The research began by conducting direct observations at the Banyuurip landfill by interviewing the drivers of waste vehicles to find out information such as waste sources, transportation schedules, etc. In this study, the data used are the name and address of the supplier, sub-district, coordinate point, and distance from the supplier's place to the landfill. After data collection, data preprocessing is done by dividing and selecting data based on sub-districts. Then the data is processed using the kmeans clustering algorithm to divide the route efficiency and the haversine formula algorithm to determine the closest distance between clusters. After the data has been successfully processed, the number of clusters is 4 for north Magelang, where each cluster will become a corridor with four routes. For central Magelang, 2 clusters with two routes, while for south Magelang, the results are 4 clusters with four routes. From these results, the evaluation results using silhouette score for data clustering of 3 sub-districts are 0.632560 for North Magelang, 0.640667 for Central Magelang, and 0.630186 for South Magelang. This method is expected to help in grouping routes and mapping supplier areas effectively and efficiently in the waste transportation process in Magelang City.
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): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.542

Abstract

In order 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, which had 10 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. On the basis of 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.
Application Mobile-Based Augmented Reality for Endemic Animals of Central Kalimantan Herdy Andriksen; Donny Avianto
Jurnal Riset Informatika Vol 5 No 3 (2023): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.528

Abstract

The existence of endemic animals typical of Central Kalimantan, such as orangutans and hornbills, is included in the protected species situation because the population numbers have increased slightly along with the clearing of land for the plantation sector, making orangutan and hornbill areas that should be beautiful and natural disappear. Because of this, a medium for conveying information and a unique introduction to the public is needed to know how important it is to know and know the various endangered species in Central Kalimantan to preserve animals. Therefore, this research aims to create an application for Central Kalimantan endemic animals using Mobile-based Augmented Reality to introduce Central Kalimantan's rare animals, starting from the area of residence, characteristics, leading food, and information about animal habitats. The application development process uses the Markerless Augmented Reality (AR) method, which displays 3D objects without using unique markers such as photos or images. The application development stage includes the planning, design, data collection, 3D object creation, application development and application testing using Blackbox testing with the Text Case method, which produces application testing descriptively explaining the application work process. The application for displaying 3D objects was tested in 5 trials, with an average of 5 seconds, and the marker appeared to display 3D objects. This application can have an impact on progress in the field of informatics as a medium for delivering information and learning media using Augmented Reality Markerless.
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): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.541

Abstract

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. During storage, the papaya fruit is initially green, 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.

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