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INDONESIA
Jurnal Riset Informatika
Published by KresnaMedia Publisher
ISSN : 26561743     EISSN : 26561735     DOI : -
Core Subject : Science,
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 442 Documents
SENTIMENT ANALYSIS OF IPUSNAS REVIEWS USING NAIVE BAYES AND K-NEAREST NEIGHBOR ALGORITHMS Augst Nurandini; Zahra Revadinika Apriliani; Eka Nada Rinjani; Pungkas Subarkah
Jurnal Riset Informatika Vol. 8 No. 3 (2026): Juni 2026
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v8i3.528

Abstract

This study aims to analyze the sentiment of iPusnas application user reviews using the classification method with the K-Nearest Neighbor (KNN) and Naive Bayes algorithms. The data used are secondary data in the form of user reviews obtained from the Google Play Store in the period of January to December 2025 totaling 2415 reviews. This study uses a text mining approach with text preprocessing stages, feature extraction using the Bag of Words (BoW) method, and sentiment clas, sification using the Naive Bayes and K-Nearest Neighbor (KNN) algorithms. Model evaluation uses Test and ScoreConfusion Matrix, and Word Cloud. The results show that the Naive Bayes method has better performance with an accuracy value of 0.705 compared to K-Nearest Neighbor (KNN) with an accuracy value of 0.615. Testing the K parameter in the KNN algorithm shows that the best K value is obtained at K = 6 with an accuracy of 0.615. This study shows that Naive Bayes is more effective in classifying sentiment in iPusnas application user reviews.
APPLICATION OF WEB-BASED DECISION SUPPORT SYSTEM FOR SUBSIDIZED 3 KG LPG DISTRIBUTION ROUTE OPTIMIZATION USING CLARKE AND WRIGHT SAVINGS ALGORITHM Melissa Chandra; Lasker Pangarapan Sinaga
Jurnal Riset Informatika Vol. 8 No. 3 (2026): Juni 2026
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v8i3.541

Abstract

The distribution of subsidized 3 kg LPG cylinders often relies on manually planned routes based on drivers’ experience, resulting in inefficient distribution operations. This study aims to develop a web-based Decision Support System integrated with WebGIS visualization for optimizing subsidized 3 kg LPG distribution routes using the Clarke and Wright Savings Algorithm. The research method consisted of problem analysis, literature review, data collection, route optimization, system development, and system evaluation. Route optimization was performed using demand data from 22 LPG outlets while considering vehicle capacity constraints. The optimization results generated five distribution routes with a total travel distance of 85.87 km, compared with 98.78 km for the company's existing routes, resulting in a distance reduction of 12.91 km (13.06%). System verification showed that the system produced results identical to manual Clarke and Wright Savings calculations. Blackbox Testing indicated that all system functions operated successfully, while User Acceptance Testing (UAT) achieved a score of 91.8%, indicating a very high level of user acceptance. These results demonstrate that the developed system can support more efficient and systematic LPG distribution planning.
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): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.543

Abstract

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.
Analyzing the Level of Anxiety Disorders of Final-Year Students by Applying the Fuzzy Mamdani Method Virdyra Tasril; Muhammad Iqbal; Febby Madonna Yuma
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.v5i3.545

Abstract

Anxiety disorders are included in mental health disorders that are more or less experienced by society. The focus of this study was samples of final-year students who felt this disorder both psychologically and psychologically. Disorders often experienced by the average panic disorder worry from thesis guidance to conducting the final trial due to student unpreparedness and lack of confidence. The purpose of this study is to obtain the results of an analysis of the results of the diagnosis of anxiety disorders in final-year students. The indicators used are three variables, physical, cognitive, and behavioral, each with its symptoms. The fuzzy Mamdani method is used with the help of Matlab software to analyze the results. Based on five samples of students with anxiety disorders experienced by final-year students aged 20-22, the largest was in cognitive disorders, and the lowest was in behavioral variables.
UI/UX Designing of an Indonesian Language Writing Educational Game for Elementary School Students Using a Human Centred Design Method Luthfi Syukriansyah Fitra; 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.v5i3.548

Abstract

Based on previous research conducted on elementary school students, it was found that there are still many errors in the use of EYD or KBBI rules, such as errors in the use of capital letters and the use of words. The lack of learning media outside of school triggers students' lack of understanding. Using technology-based learning media in games is exciting and can help improve students' understanding outside school. Using educational games as out-of-school learning media has several advantages, namely ease of access and higher student interest in playing. In developing games, an attractive appearance is needed and is the need of elementary school students. This is adequate and can increase students' interest in using the game as an out-of-school learning media. Therefore, an appropriate design method is needed to design the appearance to be attractive and in accordance with the needs of students, one of which is Human-Centered Design (HCD). This method involves users directly during the design process. By applying the HCD method, this research aims to design the interface of the "CerdasEYD" educational game that suits the needs and answers the problems that students have. Testing is carried out using the System Usability Scale to measure the success of the interface that has been designed. Through this test, the results obtained in the form of an average score of 95 indicate that the design designed has met the needs and answered the problems that students problems.
Stunting Early Warning Application Using KNN Machine Learning Method Nani Purwati; Gunawan Budi Sulistyo
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.v5i3.550

Abstract

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 quite high, coupled with the COVID-19 pandemic which has had quite an impact on the economic sector. For this reason, research on stunting is still a very important topic. This study aims to classify toddler stunting using the k-Nearest Neighbor classification algorithm, as well as build a website-based early detection application for stunting toddler cases using the CodeIgniter framework with the PHP programming language. The results of the research using the k-Nearest Neighbor Algorithm trial obtained a fairly high accuracy of 92.45%. The implementation of an early detection system for stunting cases has proven to help and facilitate health workers in classifying toddlers as stunted or not. This application is also useful as an archive and facilitates data reporting. In the application there are 8 main menus, namely the Puskesmas data menu, Posyandu data, toddler data, weighing, weighing results, development menu, stunting early warning menu which contains malnourished toddlers, stunted toddlers.
Latent Dirichlet Allocation for Uncovering Fraud Cases on Twitter Sallu Muharomah; 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.v5i3.551

Abstract

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.
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): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.553

Abstract

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 Hybrid Method in Tourism Place Recommendation System Based on Image Features Steven Arwidarasto; Desti Fitriati
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.v5i3.526

Abstract

In the industrial 4.0 era, there is an explosion of unstructured and structured data that produces broad and varied knowledge information that humans cannot process quickly. This issue makes the existence of recommendation systems meaningful. This system studies the existing information and provides suggestions according to the user's will. In the past, many recommendation systems have focused more on content-based filtering methods where recommendation results are similar based on the features of the Content that match the user's personality. This method limits the variety of information that is relevant to users. In addition, in the context of tourist attractions, many studies have not used image data that can contain many objects in one frame as a determining factor in providing recommendations. Therefore, in this study, the authors propose to add image features as one of the parameters of the recommendation system to determine the impact of using image features on the model performance. The best performance obtained is 0.364 RMSE metric using the Hybrid Image method.
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): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.547

Abstract

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.

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