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Jurnal Riset Informatika

jri
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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 20 Documents

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Search results for , issue "Vol. 5 No. 1 (2022): December 2022" : 20 Documents clear

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): December 2022
Publisher : Kresnamedia Publisher

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.

Design of Digital Library Prototype Using The Design Thinking Method Miftahurrohmah Haque; Dwi Rosa Indah
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

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 good 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): December 2022
Publisher : Kresnamedia Publisher

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.

Classification of Batu Bara Songket Using Gray-Level Co-Occurrence Matrix and Support Vector Machine Sriani Sriani; Muhammad Siddik Hasibuan; Rizkika Ananda
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

Songket is a traditional woven cloth from the Melayu and Minangkabau tribes. Songket can also be classified from the brocade woven family and woven with gold or silver thread. Songket cloth's beauty is the Indonesian people's wealth and preservation. Batu Bara Regency is one of Indonesia's regions with several Songket motifs characteristics. Public knowledge of Batu Bara Songket motifs is still minimal, and the differences between one motif and another are still unknown. This research provides information about the variety of Songket fabrics by classifying six types of Batu Bara Songket motifs, namely the Bunga Tanjung motif, Pucuk Betikam motif, Pucuk Cempaka motif, Pucuk pandan motif, Tampuk Manggis motif and Tolab Berantai motif based on the extraction of the Gray Level texture feature. The Co-Occurrence Matrix includes four parameters: Contrast, Correlation, Energy, and Homogeneity, as well as a classification method with a Support Vector Machine. The feature extraction values process as input for classification using a Support Vector Machine. The highest accuracy achieved in this study was 57%, using 60 training data and 30 test data.

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): December 2022
Publisher : Kresnamedia Publisher

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. RFID technology (radio identification) to make automated systems as authentication media and security systems. 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 main device uses NodeMCU esp8266 as a microcontroller and rc522 RFID reader as a module to read RFID cards configured using microcontroller software.

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.

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.

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.

Implementation of the Association Method in the Analysis of Sales Data From Manufacturing Companies Fachri Amsury; Nanang Ruhyana; Andry Agung Riyadi; Ihsan Aulia Rahman
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

The company produces sales data every day. Over time, the data increases, and the amount becomes very large, and the data is only stored without understanding the benefits that exist from these data due to limitations in proper knowledge in analyzing the data, especially transaction data. Sale. In order to overcome these problems, a study focused on reprocessing sales transaction data in 2018 with a data mining technique approach using the Knowledge Discovery in Database concept using the association method and apriori algorithm and a supporting application, namely RapidMiner. This study aims to help companies find customer buying habits or patterns based on 2018 sales transaction data. The results of this study produce 316 association rules where the best rules are generated on record 309 with PRO 889 & PRO 868 PRO 869 rules.

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): December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.169

News about the war between Russia and Ukraine can not be denied affecting various aspects of life worldwide. It affects the writings of every world citizen on various social media platforms, one of which is Twitter. Sentiment analysis is a process of identifying and making sentiment categories computationally. The sentiment analysis process is also intended to make computers understand the meaning of human sentences by processing algorithms. This research uses the deep learning method of the BERT (Bidirectional Encoder Representation Form Transform) model language to analyze the sentiments in the tweets written about the wars between Russia and Ukraine by Twitter social media users. The sentiment will be divided into positive, neutral, and hostile. The hyperparameters in this study used ten epochs, with a learning rate of 2e-5 and a batch size of 16. The test used in sentiment analysis was the BERTbase Multilingual-cased-model model, and the accuracy was 97%. Suggestions for further research are the need for a more balanced dataset between positive, neutral, and negative sentiments. They reward the dataset before training so that better results are expected.

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Contact Name Tati Mardiana

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Location Kota banjar, Jawa barat INDONESIA

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Contact Name
Tati Mardiana

Contact Email
jurnal.jri@kresnamediapublisher.com

Phone
-

Journal Mail Official
jurnal.jri@kresnamediapublisher.com

Editorial Address
-

Location
Kota banjar,

Jawa barat

INDONESIA