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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 16 Documents
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Search results for , issue "Vol 5 No 1 (2022): Priode of December 2022" : 16 Documents clear
Design of Digital Library Prototype Using The Design Thinking Method Miftahurrohmah Haque; Dwi Rosa Indah
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.442

Abstract

According to UNESCO (United Nations Educational, Scientific and Cultural Organization), Indonesian people's reading literacy interest has a literacy percentage of 0.001%, which means that out of 1.000 people, only one person likes to read. The digital reading movement attracts people's reading interest, especially with a digital library. Lahat District Library Service wants to re-establish a digital library that has been removed. By paying attention to usability and user experience, a digital library prototype design is carried out to develop the application to get user experience results with a good level of success and satisfaction. The method used is Design Thinking, which aims to design usable and valuable solutions by focusing on user needs. The results of the usability testing analysis of the digital library prototype created using the User Experience Questionnaire (UEQ) get "Excellent" in six aspect categories: attractiveness, perspicuity, efficiency, dependability, stimulation, and novelty.
ISO 31000:2018-Based IT Infrastructure Risk Management Study (Case Study: Universitas Mikroskil) Elly Elly; Hanes Hanes; Joosten Joosten
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.448

Abstract

In dealing with risks, organizational stakeholders will need risk management to ensure that risks within the organization have been identified and appropriate controls have been implemented in each implementation of the organization's IT infrastructure. Risk management is a process of identification, analysis, assessment, control, and efforts to avoid, minimize, and even eliminate unacceptable risks. Implementation of risk management with ISO 31000 by risk analysis and the areas that will be the focus of risk management. Mikroskil University requires risk management standards to minimize the risk of using the internet and servers in academic activities required by all academic levels at Mikroskil. The stages of the research method that are by chosen method are collecting the risks faced by the organization, determining the risk scale, and using a risk matrix for risk management priority exposure. The results of the risk management analysis are in the form of the basic principles of implementing risk management with the ISO 31000 standard, which is a recommendation to the organization in managing risk by applicable standards. The result of the risk level is two possible risks with a low level, ten with a high level, and 3 with an extreme level.
Design and Build A Prototype Internet of Things Based On Cooking Oil Distribution at PT. Lion Super Indo Jatibening Steven Steven; Azpha Thoriq Mulyadi; Resha Wisnu Murti; Anggi Oktaviani; Dahlia Sarkawi; Deny Novianti
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.449

Abstract

The scarcity of cooking oil is the main factor for PT LION Superindo Jatibening to make provisions for limiting the purchase of cooking oil. Of course, some people use this to commit fraud in purchasing, namely, buying cooking oil beyond the predetermined limit by repurchasing it after a few hours from the previous purchase. Of course, some use this to cheat on purchasing cooking oil over the predetermined limits of repurchase within a few hours of previous purchases. Thus, the governmental tribunician is disproportionate to other customers, so many are not getting cooking oil and using RFID (radio identification) technology to create an automated system as an authentication medium and security system. The system is a card reading that contains the user or item data. This technology assists in limiting purchases to greater efficiency, safety, and protection of people against the repurchasing of cooking oil. Fry oil distribution systems use IoT devices by applying PHP programming language based on websites that can be accessed and integrated with MySQL databases as data storage. For IoT devices, the primary device uses NodeMCU esp8266 as a microcontroller and rc522 RFID reader as modules to read an RFID card configured using microcontroller software.
Sentiment Analysis of Twitter's Opinion on The Russia and Ukraine War Using Bert Muhammad Fahmi Julianto; Yesni Malau; Wahyutama Fitri Hidayat
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.452

Abstract

News about the war that took place between Russia and Ukraine can not be denied affecting various aspects of life in the world. This affects the writings of every citizen of the world on various social media platforms, one of which is Twitter. Sentiment analysis is a process of identifying and making sentiment categories which is done computationally. Sentiment analysis process is also intended to make computers understand the meaning of sentences written by humans by processing using algorithms. This study uses a deep learning method using a language model, namely BERT (Bidirectional Encoder Representation Form Transformers) as a process of analyzing the sentiments that exist in tweets written about the war in Russia and Ukraine by twetter social media users. These sentiments will be divided into three parts, namely positive, neutral and negative. In this study, the hyperparameters used were 10 epochs, learning rate 2e-5, and batch size 16. The sentiment analysis test used the BERTbase Multilingual-cased-model model and the accuracy value obtained was 97%.
Implementation of Machine Learning Algorithms for Early Detection of Cervical Cancer Based on Behavioral Determinants Duwi Cahya Putri Buani; Indah Suryani
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.453

Abstract

Cervical cancer is a disease that affects women and has the highest mortality rate after breast cancer. Early detection of cervical cancer is critical at this time, so cervical cancer patients are decreasing. Many women, especially in Indonesia, are less concerned about the dangers of cervical cancer, even though if detected earlier, this disease will be easier to treat. One alternative for early detection can use machine learning algorithms. The machine learning algorithms used in this study are Naïve Bayes (NB), Logistic Regression (LR), Decision Tree (DT), SVM, and Random Forest. In this study, a random under-sampling method was employed, which had no uses in any prior research. This technique makes the accuracy of the five algorithms even better. The research results show that NB has an accuracy rate of 91.67%, LR has an accuracy rate of 87.5%, DT has an accuracy rate of 81.81%, SVM has an accuracy rate of 75%, and RF has the highest accuracy rate of 94.45%. This research shows that the best model is RF or Random Forest
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): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.475

Abstract

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.
The Implementation of MOORA Methods to Support the Refinement of Decision Priority System in Information Technology Fanni Rahmah Tsani; Umi Chotijah
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.472

Abstract

Maintenance of information and communications technology scoped on the Lamongan Regency Government is the responsibility of the Lamongan Regency Communications and Information Department. The application of information technology is closely related to the problems that appear, such as Communication Network Interruption/Damage. In this case, the report is provided by the user via WhatsApp message, and no single point of contact is used for delivery, retard the refinement process and making it difficult for technicians to prioritize refinement. In this study, the authors built a decision-supporting to assist technicians in prioritizing refinement. The Multi-Objective Optimization Based Ratio Analysis (MOORA) method is appropriate for this study as it allows us to perform the ranking process based on different weighting attributes. The calculation process of the MOORA method is based on specified criteria and weightings. Criteria are the type of damage, risk of a complaint, duration of the claim, and type of service. In one day, the three regional apparatuses with the highest scores are selected, and recommendations for prioritized refinement are provided. In this study, we found that samples with high criterion weights and scores tended to be prioritized over other samples. The results MOORA calculated show the library service as the best alternative with a value of 0.396 on ten regional apparatus tested.
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): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.481

Abstract

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
Pregnancy Risk Level Classification Using The CRISP-DM Method Reka Dwi Syaputra; Achmad Solichin
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.487

Abstract

Independent midwife practices have the task of 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, haemoglobin, 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.
Texture Feature Extraction of Pathogen Microscopic Image Using Discrete Wavelet Transform Hasan Basri
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.488

Abstract

This study used a case study of Jabon leaves, and the pathogen is one of the causes of disease that attack the leaves of jabon, one of the leaf spots and leaf blight. Discovery of leaf spot disease in different pathogens and leaf blight. The pathogen was obtained from the leaf spot of Curvularia sp. 1 and Pestalotia sp., while the pathogen came from Curvularia sp. 2 and Botrytis sp. Identify the pathogen as soon as possible to minimize its effects. Improper handling can lead to increased virulence and resistance to the pathogen. Improper handling also can cause a disease outbreak (disease epidemic) in a region. This study is the first step in identifying the pathogens responsible for Jabon leaf disease. In this study, the Application of Koch's Postulates method to achieve the purification of pathogens and retrieve the microscopic pathogen image as the data acquisition stage. Furthermore, use of the segmentation stage to separate the object pathogen from the background, and one of the methods used is Otsu Thresholding. The extraction process of pathogen microscopic image using Discrete Wavelet Transform (DWT), DWT extraction results can be obtained using energy and entropy information.

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