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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.

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.

Prediction Of Flight Delays Using Feature Engineering, Catboost, And Bayesian Optimization To Improve Model Performance Ilham Maulana; Siti Ernawati; Risa Wati
Jurnal Riset Informatika Vol. 7 No. 2 (2025): Maret 2025
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v7i2.346

Flight delays have become a major issue in the aviation industry, impacting operational efficiency and customer satisfaction. This study proposes a CatBoostClassifier-based approach combined with Feature Engineering, Bayesian Optimization, and Random Over Sampling techniques to improve the accuracy of flight delay predictions. Based on model evaluation results, the use of Feature Engineering and Bayesian Optimization enhances performance compared to the baseline CatBoost model. The CatBoost+FE+Bayes combination achieves an accuracy of 83.32%, higher than the unmodified CatBoost model, which only reaches 82.95%. However, applying the Random Over Sampling technique in the CatBoost+FE+Bayes+ROS combination decreases model performance, reducing accuracy to 81.44%. Regarding other metrics, the CatBoost+FE+Bayes model demonstrates the highest F1-score of 0.62, indicating a balance between precision and recall. Additionally, the Area Under Curve (AUC) analysis reveals that CatBoost+FE+Bayes has the highest AUC value of 0.7793, followed by CatBoost+FE at 0.7768, and the unmodified CatBoost model at 0.7643. Meanwhile, the application of ROS leads to a decrease in AUC value to 0.6787. These findings suggest that utilizing Feature Engineering and Bayesian Optimization significantly enhances flight delay predictions. However, resampling techniques such as ROS do not always positively impact the tested model and can even degrade classification performance. The objective of this research is to develop a more accurate flight delay prediction model through the application of appropriate optimization techniques. The resulting model is expected to improve prediction quality and benefit the aviation industry by optimizing operational efficiency and minimizing the negative impact of delays on passengers.

IMPROVING IMAGE CLASSIFICATION ACCURACY WITH OVERSAMPLING AND DATA AUGMENTATION USING DEEP LEARNING: A CASE STUDY ON THE SIMPSONS CHARACTERS DATASET Ilham Maulana; Siti Ernawati; Muhammad Indra
Jurnal Riset Informatika Vol. 6 No. 4 (2024): September 2024
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v6i4.348

The issue of data imbalance in image classification often hinders deep learning models from making accurate predictions, especially for minority classes. This study introduces AugOS-CNN (Augmentation and Over Sampling with CNN), a novel approach that combines oversampling and data augmentation techniques to address data imbalance. The The Simpsons Characters dataset is used in this study, featuring five main character classes: Bart, Homer, Agnes, Carl, and Apu. The number of samples in each class is balanced to 2,067 using an augmentation method based on Augmentor. The proposed model integrates oversampling and augmentation steps with a Convolutional Neural Network (CNN) architecture to improve classification accuracy. Evaluation results show that the AugOS-CNN model achieves the highest accuracy of 96%, outperforming the baseline CNN approach without data balancing techniques, which only reaches 91%. These findings demonstrate that the AugOS-CNN model effectively enhances image classification performance on datasets with imbalanced class distributions, contributing to the development of more robust deep learning methods for addressing data imbalance issues.

Digitalization Of Survey And Mapping Service Processes Through The Development Of A Web-Based System Siti Ernawati; Deni Hermawan
Jurnal Riset Informatika Vol. 7 No. 1 (2024): December 2024
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v7i1.352

PT. Cakrawala Pilar Nusantara is a private company engaged in survey and mapping consultancy services. Several challenges have been identified in its business processes, one of which is that service delivery for collaboration is still conducted manually. This study adopts a Design Science Research (DSR) approach, focusing on the development of an artifact in the form of a web-based service system for PT. Cakrawala Pilar Nusantara, in accordance with the objectives of the research. The DSR methodology consists of the following stages: Problem Identification and Research Motivation, Definition of Solution Objectives, Design and Development of the Artifact, Demonstration, Evaluation, and Communication. Data collection was carried out through observation and interviews with relevant parties. System design visualization was conducted using UML, represented by use case diagrams and activity diagrams. The programming language used is PHP, implementing the CodeIgniter framework. System testing was performed using the black-box testing method.The result of this research is a web-based information system that facilitates data entry, quotation submissions, reporting, and improves service processes by transforming manual record-keeping into a computerized system. The presence of this information system provides greater convenience for the company in managing its operational activities.

Co-Authors Agam Satya Muhammad Aisyah Putri Faisal Deni Hermawan Dian Ambar Wasesha Dody Firmansyah Dwi Andini Putri Eka Rini Yulia Farid Shofli Wahnin Hieronimus Emilianus Deska Feby Ujianta Hilda Rachmi Hylenarti Hertyana Ilham Maulana Indah Purnamasari Lestari Yusuf Lilyani Asri Utami, Lilyani Asri Lisda Widiastuti Mariah Nur Azizah Muhamad Ryansyah Muhammad Indra 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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