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All Journal JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Komputer AMIK BSI Jurnal Khatulistiwa Informatika JIKO (Jurnal Informatika dan Komputer) Informatics for Educators and Professional : Journal of Informatics Jurnal Sains dan Informatika Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Manajemen Informatika Jurnal Riset Informatika EVOLUSI : Jurnal Sains dan Manajemen Jurnal AbdiMas Nusa Mandiri BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Jurnal Pengabdian Kreatif Cemerlang Indonesia Jurnal Aruna Mengabdi (ARMI)

Siti Ernawati

Universitas Nusa Mandiri

Author-ID : 3404753

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Physics Public Health Social Sciences Other

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SELECTION OF THE BEST PREWEDDING PHOTO LOCATION USING THE AHP METHOD Muhammad Noval Alfarizi; Mariah Nur Azizah; Wikara Dwi Saputra; Siti Ernawati
Jurnal Riset Informatika Vol 3 No 4 (2021): Period of September 2021
Publisher : Kresnamedia Publisher

The location of the photo prewedding is a place that can describe the happiness of the bride and groom. In these conditions sometimes the general public especially prospective bride and groom and the photographer have difficulty in choosing the location of the photo prewedding best. Then the resulting decision-makers will get the location of the photo prewedding which is not in accordance with what is expected. In this study utilizes the Method of Analytical Hierarchy Process (AHP) to help the bride and groom and the photographer in choosing the location of the photo prewedding best, especially in the area of Jakarta. This study using six criteria such as distance, number of spots, transportation, time, cost, location, and theme. From the Results of the analysis and processing of the data obtained that the Ancol with superior value 0,224047721 (22%) berbandingan to cafe batavia with a value of 0,195494507 (20%), sunda kelapa harbor to the value 0,187335550 (19%), taman wisata mangrove angke kapuk with a value of 0,171584976 (17%), old city, with the value of 0,162696386 (16%), and glodok, with a value of 0,058840858 (6%).

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

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

ANDROID-BASED QURAN APPLICATION ON THE FLUTTER FRAMEWORK BY USING THE FOUNTAIN MODEL Siti Ernawati; Risa Wati
Jurnal Riset Informatika Vol. 3 No. 2 (2021): March 2021 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v3i2.64

Abstract With the development of technology, smartphones have become one of the communication tools and can be used as a tool entertainer. But smartphones have an impact on the declining interest in reading the Quran. It would be a good smartphone that can be used to remember the creator is to create a Quran application on android so that users do not need to carry the mushaf Quran while on the go. The purpose of the construction of the application is to always remember to the god that is by the way can read Quran whenever and wherever are. The Model used to build the application Model is the Fountain where at the time of building the application can be done in overlap by the needs. Quran application built using. net framework flutter with the programming language dart. To install the application at least the Android version used is version 5.0 Lollipop. Testing the application of the Quran using black-box testing. Give the questionnaire to potential users of the application to assess the feasibility of the application of the Quran. From the results of the questionnaire can be concluded that the application of the Quran is very user friendly and with the audio playing over and over can help the user to memorize the Quran.

SELECTION OF THE BEST PREWEDDING PHOTO LOCATION USING THE AHP METHOD Muhammad Noval Alfarizi; Mariah Nur Azizah; Wikara Dwi Saputra; Siti Ernawati
Jurnal Riset Informatika Vol. 3 No. 4 (2021): September 2021 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v3i4.100

SENTIMENT ANALYSIS OF THREE-PERIOD POLEMICS USING K-NEAREST NEIGHBOR WITH TF-IDF WEIGHTING Siti Ernawati; Risa Wati
Jurnal Riset Informatika Vol. 4 No. 3 (2022): June 2022
Publisher : Kresnamedia Publisher

The issue of changing the presidential term which was originally 2 periods of government into 3 periods raises pros and cons in the community. Many 3-period hashtags have sprung up on social media twitter. So that conducted research on sentiment analysis of presidential election polemics 3 period. The purpose of the study was to produce the value of classification on the issue of presidential election change discourse into 3 periods using the K-NN method and whether the k-NN method proved to be well used for classifying text in the review of presidential election polemics 3 periods. Dataset totaling 1152 data, data is processed using Python and Jupyter Notebook as a text editor. The data is classified into positive reviews and negative reviews, then the data is divided into training data and test data with a ratio of 90:10. Weighting words using TF-IDF and sentiment classification using K-NN method. From the results of classification using the K-NN method obtained the highest accuracy when the value of k=17 and k = 18 with an accuracy of 85.3%. The results of the analysis of public sentiment to review the issue of discourse on the change of presidential term into 3 periods tend to be negative with a percentage of 21.26% positive sentiment and 78.74% negative sentiment.

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.

Co-Authors Agam Satya Muhammad Aisyah Putri Faisal Dian Ambar Wasesha Dody Firmansyah Dwi Andini Putri Eka Rini Yulia Farid Shofli Wahnin Hieronimus Emilianus Deska Feby Ujianta Hilda Rachmi Hylenarti Hertyana Indah Purnamasari Lestari Yusuf Lilyani Asri Utami, Lilyani Asri Lisda Widiastuti Mariah Nur Azizah Muhamad Ryansyah Muhammad Noval Alfarizi Muhammad Ryansyah Novi Kusumawati Nuzuliarini Nuris Raden Bagus Dimas Putra Risa Wati Risa Wati Risa Wati - AMIK BSI Tasikmalaya Risa Wati - AMIK BSI Tasikmalaya Ronny Setiawan Wardah Ramadhanty Wikara Dwi Saputra

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