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All Journal Jurnal sistem informasi, Teknologi informasi dan komputer Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Ilmiah FIFO Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Riset Informatika Coverage: Journal of Strategic Communication Journal of Informatics and Advanced Computing
Desti Fitriati
Universitas Pancasila
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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SENTIMENT ANALYSIS OF TWITTER DATA ON DISTANCE LEARNING USING NAÏVE BAYES ALGORITHM Putri Rana Khairina; Desti Fitriati
Jurnal Riset Informatika Vol. 3 No. 3 (2021): June 2021 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (831.098 KB) | DOI: 10.34288/jri.v3i3.68

Abstract

Covid-19 is widespread, resulting in a global pandemic. Distance Learning System (DLS) is considered as a solution but, the reality of the implementation of DLS is not in accordance with the expectations of the community. Many twitter users wrote their opinions on DLS. The tendency of public sentiment can be used as a way to improve the existing education system in Indonesia and can be an input for the government in improving the DLS method that is being implemented. Thus, this study produced a system that can analyze tweet sentiment towards DLS. The tweet was obtained using the Twitter API. The method used is Naïve Bayes for the process of classification of positive, negative and neutral sentiments using 600 data. Then, data sharing is done 80% data training and 20% data testing that will be in the text preprocessing first. The accuracy of sentiment analysis of DLS using Naïve Bayes method using 3-fold Cross Validation produces an average of 93%.
DECISION SUPPORT SYSTEM TO ELECT THE BEST USTADZ USING SIMPLE ADDITIVE WEIGHTING METHOD Muhammad Abdan Syakuro; Desti Fitriati
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.v3i4.95

Abstract

Pesantren is a place for students to live and learn religious education. In Pesantren there are human resources that very helpful for learning in boarding school, namely ustadz. In the process of successful education, sometimes pesantren needs to make an assessment to improve the quality of education, one of it is conducting the best selection of ustadz adequate and exceeding the average. The number of ustadz that exist causes difficult decision making of the best ustadz elections quickly, accurately and has not been able to give maximum results and takes a very long time in calculation. In addition, the selection of the best ustadz in Pesantren Qur'an Al Hikmah Bogor is still not objective because the selection of the best ustadz is still appointed directly without using calculations. Based on the problems described above, a Decision Support System (DSS) application is needed using simple additive weighting method to help in making the best ustadz decision in pesantren. This system is a dynamic system where users can set the parameters of criteria and weights themselves. Besides, From the making of the Decision Support System produced accuracy of 90% of 30 samples according to which are 27 samples.
APPLICATION OF PROFILE MATCHING ALGORITHM IN SELECTION OF THE BEST EMPLOYEES IN PROPERTY COMPANY Laeli Nurchasanah; Annisa Cintakami Firdaus; Desti Fitriati
Jurnal Riset Informatika Vol. 4 No. 2 (2022): March 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v4i2.150

Abstract

Giving awards to employees who have advantages and good work performance is one way to increase positive competitiveness among employees in a company. This study aims to find the advantages of each employee to find out which employees excel. Through achievements in the world of work, it can be a benchmark for finding the best employees who deserve awards. Analysis of the data used in this study is sourced from data on sales of property companies for the last three months. This study uses the Profile Matching Method to determine the best employees in property companies. This research was conducted by comparing one employee with another employee candidate based on predetermined criteria. The results of this study are in the form of rankings that show the order of the best employees who are entitled to an award from the company.
Comparison of SAW, WP, and TOPSIS Methods in Determining the Best Journalists N.I.S. Baldanullah; Febrianti Adhania; Desti Fitriati
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.v5i4.199

Abstract

Journalists are human resources that have a significant influence on journalistic companies. A system is needed to support the company's decision to select and measure its reporters. PT. Inipasti Communika is one of the journalistic companies that has never previously measured and assessed its journalists, so it has difficulty assessing and measuring its journalists. This study aims to provide a solution using the Decision Support System in decision-making using the SAW, WP, and TOPSIS methods and provide the final decision results based on comparing these methods. This study uses criteria and criteria values from these companies. The company's data related to its journalists is the privacy of PT. It is a Community, so the alternative value used is dummy data that is still by the original standards of the company's data. This study concludes that the three methods can provide the best alternatives with the same results.
Implementation of Hybrid Method in Tourism Place Recommendation System Based on Image Features Steven Christ Pinantyo Arwidarasto; Desti Fitriati
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.235

Abstract

In the industrial 4.0 era, there is an explosion of unstructured and structured data that produces broad and varied knowledge information that humans cannot process quickly. This issue makes the existence of recommendation systems meaningful. This system studies the existing information and provides suggestions according to the user's will. In the past, many recommendation systems have focused more on content-based filtering methods where recommendation results are similar based on the features of the Content that match the user's personality. This method limits the variety of information that is relevant to users. In addition, in the context of tourist attractions, many studies have not used image data that can contain many objects in one frame as a determining factor in providing recommendations. Therefore, in this study, the authors propose to add image features as one of the parameters of the recommendation system to determine the impact of using image features on the model performance. The best performance obtained is 0.364 RMSE metric using the Hybrid Image method.
KLASIFIKASI RIMPANG MENGGUNAKAN CONVOLUTION NEURAL NETWORK Yuvan Feberian; Desti Fitriati
Journal of Informatics and Advanced Computing (JIAC) Vol 3 No 1 (2022): Journal of Informatics and Advanced Computing
Publisher : Teknik Informatika Universitas Pancasila

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Abstract

Rimpang dalam ilmu botani dapat didefinisikan sebagai tanaman yang tumbuh di bawah permukaan tanah seperti jahe, kencur, kunyit, lengkuas dan temulawak. Rimpang dapat digunakan sebagai pengobatan tradisional di Indonesia untuk mengobati beberapa penyakit seperti karminativa, diaforetika, stimulansia, kolagoga dan lain-lain. Peneliti membuat survei dalam bentuk kuisioner untuk mengetahui apakah orang dapat membedakan rimpang dengan responden sebanyak 56 orang dan hasil dari kuisioner tersebut menunjukan bahwa 12 orang menjawab dengan benar, 16 orang menjawab ragu-ragu, 28 orang menjawab tidak benar. Peneliti membuat sebuah aplikasi untuk membantu orang-orang dalam kebingungan menyebutkan nama tanaman rimpang atau membedakan tanaman rimpang dengan menggunakan metode CNN. Keseluruhan jumlah data rimpang yang digunakan adalah 250 data dengan setiap kelas 50 data jahe, kencur, kunyit, lengkuas dan temulawak. Hasil menunjukkan akurasi sebesar 0.9 atau 90%.
Sistem Informasi Manajemen Inventori Berbasis Website Untuk Proses Operasional PT Bumi Bara Sakti Faeqal Hafidh Muhammad Asfian; Desti Fitriati
Journal of Informatics and Advanced Computing (JIAC) Vol 5 No 1 (2024): Journal of Informatics and Advanced Computing (JIAC)
Publisher : Teknik Informatika Universitas Pancasila

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Abstract

Inventory plays a crucial role in the operational management of companies, ensuring smooth supply chains and business continuity. Bumi Bara Sakti (BBS), a coal trading company, relies on accurate inventory management. But, BBS faces difficulties in managing inventory data due to a high volume of transactions, leading to heavy workloads and information delays. Additionally, limited Excel proficiency among BBS executives and employees deepens these issues. This study aims to create a web-based Inventory Management Information System using the waterfall method, MySQL for database management, and CodeIgniter4 as the framework. The research mainly focuses on recording coal sales and purchases, total stock, and truck movements to stockpiles based on data obtained from BBS. The system is expected to facilitate real-time recording of purchases, sales, and stock updates while maintaining information accuracy. Furthermore, it provides data visualization and easily understandable reports. Evaluation results indicate that the Inventory Management Information System simplifies inventory data management and data interpretation for BBS executives and employees.
Co-Authors Agung Arya Adi Nugraha Annisa Cintakami Firdaus Audrey Raihannisa Elvina Lathifa Faeqal Hafidh Muhammad Asfian Fairuz Astari Devianty Febri Maspiyanti Febrianti Adhania Iqbal Gibran Laeli Nurchasanah Muhamad Rosit Muhammad Abdan Syakuro N.I.S. Baldanullah Nadiah Nadiah Nur Yulianti Hidayah, Nur Yulianti Nura Meutia Nessrayasa Putri Rana Khairina Riza Darma Putra Steven Arwidarasto Steven Christ Pinantyo Arwidarasto Wina Finka Yuvan Feberian Zyhan Faradilla Daldiri