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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 432 Documents

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Implementation of the K-Means Clustering for Teacher Performance Assessment Grouping (PKG) at MI Bani Hasyim Cerme Bagus Firmansyah; Umi Chotijah
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

Evaluation of teacher performance at MI Bani Hasyim Cerme still uses the manual method. Using office applications such as excel and word results in a significant accumulation of data that makes it difficult for school principals to calculate scores and evaluate the results of clustering or teacher performance scores, so it is wasteful of energy, time, and cost. The k-Means clustering method is expected to facilitate the clustering process of teacher performance values as a source of information and make it easy for school principals to classify teacher performance results. This research aims to obtain clustering values on teacher performance assessment data and to replace the teacher performance assessment system at MI Bani Hasyim, which was previously carried out conventionally into a web-based system. The results of this study are the clustering values of teacher performance assessment and a web-based teacher performance appraisal system. It is expected to facilitate the process of evaluating teacher performance in the Bani Hasyim primary school in the future.

BANDWIDTH MODELING ON SMART CAMPUS BASED ON ENGINEERING METHOD – STATISTICS Ewi Ismaredah; Hasdi Radiles
Jurnal Riset Informatika Vol. 4 No. 3 (2022): June 2022
Publisher : Kresnamedia Publisher

The importance of generating internet traffic as one of the basic considerations in bandwidth allocation policies between faculties is increasing due to the number of students who complain about connection services on campus. This study proposes internet traffic generation based on the statistical - engineering method. The population is calculated based on class capacity in each faculty, as the main alibi of student attendance on campus where traffic arrivals are generated based on the arrival model through information on possible scheduling variations. Although internet services have different characteristics, they are physically determined by the bitrate and idle mode in the traffic time series. The results show recommendations in three application bitrate categories, namely 200kbps, 400kbps, and 800kbps Traffic Shaping. Keywords: , , ,

COMPARATIVE ANALYSIS OF PATHFINDING ARTIFICIAL INTELLIGENCE USING DIJKSTRA AND A* ALGORITHMS BASED ON RPG MAKER MV Riska Nurtantyo Sarbini; Irdam Ahmad; Romie Oktovianus Bura; Luhut Simbolon
Jurnal Riset Informatika Vol. 4 No. 3 (2022): June 2022
Publisher : Kresnamedia Publisher

In most games, an artificial pathfinding intelligence is required for traversing the fastest discovery. It is essential for many video games, particularly Role Playing Games (RPGs). The algorithm pathfindings implemented in this game are A* and Dijkstra Algorithms. This study aims to test an artificial intelligence system for discovering routes using the A* and Dijkstra algorithms based on RPG Maker MV. The result showed that from the time obtained, in the experiment on eight nodes using the Pathfinding mechanism of A* algorithm has faster result in discovering the nearest route with the time 08:15:23 with format (mm:ss: ms) whereas Dijkstra Algorithm has a 34:47:43 time result. The time record needed represents the distance between the search nodes. It indicates that the multiple weighting in the impassable nodes caused the cost calculation process becomes faster and more efficient.

COMPARISON OF CLASSIFICATION ALGORITHMS FOR ANALYSIS SENTIMENT OF FORMULA E IMPLEMENTATION IN INDONESIA Fachri Amsury; Nanang Ruhyana; Tati Mardiana
Jurnal Riset Informatika Vol. 4 No. 3 (2022): June 2022
Publisher : Kresnamedia Publisher

The Formula E racing series has become one of the world's most prestigious competitions. In 2022, Indonesia hosted the famous Formula E race. The event possesses the potential for economic benefits for Indonesia worth 78 million euros through the arrival of 35,000 spectators. Indonesians are enthusiastic about Formula E since it allows their nation to encourage tourists and gain international prominence. However, some people do not support this event. Since they regard that amid the COVID-19 pandemic, it is preferable for the government to focus on people affected by the pandemic rather than support a Formula E event. This study compares the Support Vector Machine and Naive Bayes algorithms in classifying public opinion in the Formula E race. This study gets its information from user comments on social media platforms, especially Twitter. The stages start with text preprocessing and include cleaning, case folding, tokenization, filtering, and stemming. Proceed with weighting using the TF-IDF approach. Data testing uses a confusion matrix to evaluate the classification results by testing accuracy, precision, and recall. Categorizing public opinion using the SVM algorithm has an accuracy of 82 percent, a precision of 97.86 percent, and a recall of 77.90 percent. On the other hand, the accuracy of the Naive Bayes technique is more limited, at 87.54 percent. Society's opinion on Twitter shows positive sentiment towards implementing Formula E.

IMPLEMENTATION OF K-MEANS ALGORITHM FOR CLUSTERING OF COVID-19 VACCINATION IN EAST JAVA WITH ORANGE Michael Sitorus; Cornelia Antonieta DC; Cyntia Larasati
Jurnal Riset Informatika Vol. 4 No. 3 (2022): June 2022
Publisher : Kresnamedia Publisher

Entering the era of the Covid-19 pandemic, the government has intensively implemented a vaccination program until now. Covid-19 vaccination programs are implemented to strengthen the immune system, reduce the risk of infection, reduce the severe effects of the virus, and achieve herd immunity. In the implementation, the Covid-19 vaccination is regulated by the regional government in each province with a policy that requires vaccinating Covid-19 twice for everyone with specific criteria supported by movements to wear masks, use hand sanitizers, and diligently wash hands and contact tracing of positive cases. This study aims to demographically cluster the implementation of vaccinations in all areas of East Java province in 2021. The method used in conducting this clustering is the K-Means algorithm using tools, namely Orange. From the results of the study, the results of the division or clustering of regions into three clusters were C1 for the area with the lowest vaccination, namely Pasuruan Regency, C2 for the area with moderate vaccination, namely Kediri City, and C3 for the highest vaccination area, namely Surabaya City.

Support Vector Classification with Hyperparameters for Analysis of Public Sentiment on Data Security in Indonesia Siti Ernawati; Risa Wati; Nuzuliarini Nuris
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

The development of Information Technology makes increasing use of the internet. This raises the vulnerability of data security. Cyber attacks in Indonesia caused many tweets on social media Twitter. Some are positive, and some are negative. The problem of this study is to determine the public sentiment towards data security in Indonesia, while the purpose of this study is how the response or evaluation of the government of Indonesia to the many perceptions of people who lack confidence in data security in Indonesia. Data obtained from twitter with as much as 706 data was processed using python with a percentage of 10% test data and 90% training data. Weighting is done using TF-IDF, and then the data is processed using the Support Vector Machine algorithm using the SVC (Support Vector Classification) library. Support Vector Classification with RBF kernel classifies Text well to obtain AUC value with good classification category. Utilizing one of the hyperparameter techniques, which is a grid search technique that can compare the accuracy of test results. The test results using SVC with RBF kernel obtained an accuracy value of 0.87, Precision of 0.82, recall of 0.94, and F1_Score of 0.87. This study is expected to be used by decision-makers related to public confidence in data security in Indonesia.

DESIGNING AN INFORMATION SYSTEM SIMULATION OF PSYCHOLOGICAL TEST QUESTIONS USING THE C4.5 METHOD AT THE WEB-BASED HRC LAVANDA PSYCHOLOGY BUREAU Rini Wulandari; Charles Jhony Mantho Sianturi
Jurnal Riset Informatika Vol. 4 No. 3 (2022): June 2022
Publisher : Kresnamedia Publisher

Abstract Psychological tests or psychological tests are a diagnostic effort with specific measuring tools created by psychologists to reveal a picture of a person's potential or to distinguish a person's behaviour from others through particular problems. Not all psychological tests can be easily computerized, and an accounting application can be easily modelled mathematically. At the very least, it must be admitted that at this time, there are very few psychological tests in Indonesia that are well computerized. It will be troublesome if the test is intended for recruitment purposes, especially if the company concerned needs the test results as quickly and accurately as possible. Seeing this background, the author wants to help and provide easy solutions by utilizing the internet media, a field of information and media that is very useful for everyone. The C4.5 method is applied to classify personality test questions, interest aptitude tests, SPM tests, and arithmetic tests to produce accurate calculations for the classification of psychological test questions. With the information system for the psychological test questions using the C4.5 method, it is hoped that the public can more easily access the simulated psychological test questions easily and quickly.

FORECASTING OYSTER MUSHROOM SALES USING THE DOUBLE EXPONENTIAL SMOOTHING METHOD AT KUB RUMAH MUSHROOM BERSAMA Winda Wulandari; Havid Syafwan; Muhammad Ihsan
Jurnal Riset Informatika Vol. 4 No. 4 (2022): September 2022
Publisher : Kresnamedia Publisher

The amount of oyster mushroom production is often not by consumer orders due to a lack of attention to the mushroom stock in the Mushroom House KUB. The purpose of this study is to apply double exponential smoothing (DES) to predict future sales of oyster mushrooms so that consumer needs are met. This research method uses quantitative methods. The data source comes from data on sales of oyster mushrooms from June 2021-May to 2022. The data is analyzed using double exponential smoothing based on alpha and MAPE values. The results showed that an alpha of 0.6 with a MAPE value of 6.23% was the alpha with the smallest MAPE. This study concluded that the double exponential smoothing method could accurately predict future oyster mushroom sales.

DETERMINATION OF PRIORITIES OF ELEMENTARY SCHOOL REHABILITATION AT ASAHAN USING SIMPLE ADDICTIVE WEIGHT Dian Aprillia; William Ramdhan; Wan Mariatul Kifti
Jurnal Riset Informatika Vol. 4 No. 4 (2022): September 2022
Publisher : Kresnamedia Publisher

In the budgeting process for school building rehabilitation activities in Asahan Regency, there are still inaccuracies in selecting prioritized primary schools for rehabilitation. This study aimed to apply the Simple Additive Weighting (SAW) method to determine five primary schools that were prioritized for repair. This research method uses quantitative methods. The data source comes from the East Kisaran and West Kisaran Elementary Schools. The data were analyzed using the SAW method based on the criteria weight depending on the matrix value and normalization. The results showed the 5 largest criteria weights, namely UPTD SDN 010097 Selawan (0.940), UPTD SDN 014689 Lestari (0.884), UPTD SDN 010039 Sentang (0.880), SD Taman Kasih Karunia (0.847), and UPTD SDN 018453 Siumbut-Umbut (0.820). ). This study concluded that the double exponential smoothing method could make it easier to determine which primary school decisions are prioritized for rehabilitation.

Pregnancy Risk Level Classification using the Crisp-DM Method Reka Dwi Syaputra; Achmad Solichin
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

Independent midwife practices are tasked with reminding and maintaining the quality of standardized reproductive health services for pregnant women. Independent midwife practices have had patient visits since the COVID-19 pandemic from 2020 to 2021, especially at the Yetti puranama midwife, which consists of 320 pregnancy examinations, 130 delivery care, and 50 referrals. The COVID-19 pandemic has impacted maternal mortality rates because there are still many restrictions on all services. Maternal health services include pregnant women who are routinely unable to go to the puskesmas or other healthcare facilities due to fear of contracting COVID-19, which delays the examination of pregnancy gravida, abortion, temperature, pregnancy distance, hemoglobin, blood pressure, ideal weight, and decisions. So that the problem that occurs is an increase in the risk of pregnancy, resulting in death and increased maternal mortality. In solving this problem, the research takes a machine-learning approach. The research aims to build a classification of pregnancy risk levels that can predict early treatment in this study using the random forest method with cross-validation 2. This study obtained the results of an accuracy value of 98%, precision of 94%, and recalled 100% in the random forest method.

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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