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COMPARISON OF CLASSIFICATION ALGORITHMS FOR ANALYSIS SENTIMENT OF FORMULA E IMPLEMENTATION IN INDONESIA Fachri Amsury; Nanang Ruhyana; Tati Mardiana
Jurnal Riset Informatika Vol 4 No 3 (2022): Period of June 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (934.443 KB) | DOI: 10.34288/jri.v4i3.400

Abstract

The Formula E racing series has become one of the world's most prestigious competitions. In 2022, Indonesia hosted the famous Formula E race. The event possesses the potential for economic benefits for Indonesia worth 78 million euros through the arrival of 35,000 spectators. Indonesians are enthusiastic about Formula E since it allows their nation to encourage tourists and gain international prominence. However, some people do not support this event. Since they regard that amid the COVID-19 pandemic, it is preferable for the government to focus on people affected by the pandemic rather than support a Formula E event. This study compares the Support Vector Machine and Naive Bayes algorithms in classifying public opinion in the Formula E race. This study gets its information from user comments on social media platforms, especially Twitter. The stages start with text preprocessing and include cleaning, case folding, tokenization, filtering, and stemming. Proceed with weighting using the TF-IDF approach. Data testing uses a confusion matrix to evaluate the classification results by testing accuracy, precision, and recall. Categorizing public opinion using the SVM algorithm has an accuracy of 82 percent, a precision of 97.86 percent, and a recall of 77.90 percent. On the other hand, the accuracy of the Naive Bayes technique is more limited, at 87.54 percent. Society's opinion on Twitter shows positive sentiment towards implementing Formula E.
Pelatihan Mengolah Data Survey Dengan Microsoft Excel Pada Lembaga Muslimah Wahdah Islamiyah Setiaji Setiaji; Tati Mardiana; Ani Oktarini Sari; Muhammad Ifan Rifani Ihsan
Jurnal Pengabdian Kreatif Cemerlang Indonesia Vol 1 No 1 (2022): Periode Mei
Publisher : Yayasan Kreatif Cemerlang Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (882.351 KB)

Abstract

Lembaga Muslimah Wahdah Islamiyah merupakan bagian dari DPP Wahdah Islamiyah Jakarta. Yang lingkup program kerjanya fokus pada pengembangan diri para muslimah dan penyelenggaraan kegiatan sosial bagi masyarakat umum. Untuk membuat pemetaan jadwal dan kegiatan atau untuk mengetahui tingkat keberhasilan pendidikan yang dilakukan oleh lembaga muslimah WI masih belum terbiasa menggunakan kuesioner ataupun pembuatan dan pengolahan data survey mengenai kegiatan yang telah dilakukan. Untuk itu kegiatan pengabdian masyarakat yang dilakukan oleh Dosen Fakultas Teknologi Informasi memberikan Pelatihan Mengolah Data Survey Dengan Microsoft Excel Pada Lembaga Muslimah Wahdah Islamiyah. Metode yang digunakan dalam kegiatan pengabdian masyarakat ini berupa pelatihan interaktif dalam penyampaian teori, sedangkan untuk metode praktikumnya menggunakan metode simulasi dengan menggunakan fungsi statistik microsoft excel dan tanya jawab. Pelatihan ini diharapkan dapat meningkatkan anggota Wahdah Islamiyah dalam mengelola data, pemanfaatan data dan memanfaatkan fitur Microsoft Excel yang telah disediakan sehingga akan terbentuk pemuda dan pengurus yang mahir dilingkungan organisasi
Pelatihan Pengolahan Data dan Penyajian Data Dengan Media Infografis Pada JPRMI Jakarta Selatan Ani Oktarini Sari; Setiaji Setiaji; Tati Mardiana; M. Ifan Rifani Ihsan
Jurnal Pengabdian Kreatif Cemerlang Indonesia Vol 1 No 2 (2022): Periode November
Publisher : Yayasan Kreatif Cemerlang Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (813.271 KB)

Abstract

Tren penyajian data dengan menyajikan tampilan data yang menarik belum diterapkan di Jaringan Pemuda dan Remaja Masjid (JPRMI) DKI Jakarta. Padahal penyajian data yang baik secara visual dapat memberikan pemahaman bagi audience. Oleh karena itu Universitas Nusa Mandiri melaksanakan Pengabdian Masyarakat berupa Pelatihan Pengolahan dan Penyajian data dengan media Infografis di Pemuda dan Remaja Masjid (JPRMI) DKI Jakarta. Metode yang digunakan dalam kegiatan pengabdian masyarakat ini berupa pelatihan interaktif dalam penyampaian teori, sedangkan untuk metode praktikumnya menggunakan metode simulasi dan tanya jawab. Dengan pelatihan tersebut, dapat membantu para Pemuda dan Remaja Masjid (JPRMI) DKI Jakarta dalam mengolah dan menampilkan data secara visual.
Pemanfaatan Google Form Sebagai Media Pengumpulan dan Pengolahan Data pada Kader PKK Kelurahan Ragunan Jakarta Ani Oktarini Sari; Setiaji Setiaji; Muhammad Ifan Rifani; Tati Mardiana
Jurnal Aruna Mengabdi Vol. 1 No. 1 (2023): Periode Mei 2023
Publisher : Lotus Aruna Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61398/armi.v1i1.10

Abstract

Google Form adalah platform unik yang dikembangkan oleh Google yang dimaksudkan untuk menyediakan layanan formulir melalui internet. Anda dapat mengelola dan menganalisis survei dengan benar dan mendapatkan hasil instan yang tepat dengan menggunakan Google Form. Teknik pengumpulan dan pengelolaan data dengan menggunakan Google Form belum diterapkan di Kader Pemberdayaan Kesejahteraan Keluarga (PKK) Kelurahan Ragunan Jakarta Selatan. Padahal pengumpulan dan pengelolaan data yang baik dapat memberikan hasil evaluasi dan penilaian yang baik pula. Kegiatan pengabdian masyarakat ini menggunakan pelatihan interaktif dalam penyampaian teori; metode praktikumnya menggunakan simulasi dan tanya jawab. Diharapkan dengan adanya pelatihan ini dapat menambah wawasan para kader untuk penggunaan Google Form dalam kegiatan PKK di kelurahan Ragunan.
Implementation of the Saw Method to Discover the Optimum Internet Service Recommendations for Online Gaming Gunawan Gunawan; Ita Yulianti; Ami Rahmawati; Tati Mardiana; Nanang Ruhyana
Jurnal Riset Informatika Vol 5 No 3 (2023): Priode of June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i3.547

Abstract

Currently, the development and use of the Internet have a more complex function so that it can change the paradigm of people's lives, including in aspects of entertainment, especially games. With the rise of numerous ISPs in Indonesia, different internet service packages are now available, particularly for gamers, such as Indihome, Biznet, First Media, and My Republic. The variety of services makes it difficult for users to choose an internet package that suits their needs. Therefore, this research aims to build a decision support system that can facilitate users in choosing the ideal internet service for gamers based on five criteria: quota, network speed, connection, cost, and the number of users using the SAW method. The data collection methods used are observation, questionnaires, and interviews. The research results obtained from data processing using the SAW method through Microsoft Excel are then implemented into a website-based program. With this program, it is hoped that it can be a tool for users in determining the service package to be purchased.
Implementation of the Saw Method to Discover the Optimum Internet Service Recommendations for Online Gaming Gunawan Gunawan; Ita Yulianti; Ami Rahmawati; Tati Mardiana; Nanang Ruhyana
Jurnal Riset Informatika Vol. 5 No. 3 (2023): June 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (759.546 KB) | DOI: 10.34288/jri.v5i3.232

Abstract

Currently, the development and use of the Internet have a more complex function so that it can change the paradigm of people's lives, including in aspects of entertainment, especially games. With the rise of numerous ISPs in Indonesia, different internet service packages are now available, particularly for gamers, such as Indihome, Biznet, First Media, and My Republic. The variety of services makes it difficult for users to choose an internet package that suits their needs. Therefore, this research aims to build a decision support system that can facilitate users in choosing the ideal internet service for gamers based on five criteria: quota, network speed, connection, cost, and the number of users using the SAW method. The data collection methods used are observation, questionnaires, and interviews. The research results obtained from data processing using the SAW method through Microsoft Excel are then implemented into a website-based program. With this program, it is hoped that it can be a tool for users in determining the service package to be purchased.
SENTIMENT ANALYSIS OF USER REVIEWS BRI MOBILE APPLICATION WITH GRADIENT BOOST METHOD Nanang Ruhyana; Kanita Salsabila; Andri Agung; Tati Mardiana
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.v7i2.342

Abstract

BRI Mobile application is a digital banking service launched in 2019 by Bank Rakyat Indonesia, which provides facilities such as mobile banking, internet banking, and electronic money. The presence of this application aims to facilitate customers in accessing and managing financial services efficiently through mobile devices. Reviews have become a very important sourceĀ on platforms such as Google Playstore become a very important source of information to evaluate and improve service quality. However, manually identifying sentiment representations from thousands of reviews is a time-consuming and inefficient process. This research aims to perform sentiment analysis automatically on BRI Mobile application user reviews by utilizing text mining methods. The sentiment classification process is carried out using the Gradient Boosting algorithm approach and initial analysis using the VADER Sentiment method to provide initial data labelling. Based on the classification results, 344 data with positive sentiment, 333 data with negative sentiment, and 333 data with neutral sentiment were obtained. The model built was then evaluated using the accuracy metric, and an accuracy value of 97% was obtained. The results of this research are expected to be a strategic input for application developers in understanding user perceptions more objectively and efficiently.