Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Jurnal Ilmu Manajemen Terapan (JIMT) Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Salsabila Dwi Fitri
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Digital Marketing Dalam Meningkatkan Citra Bank (Studi Pada Bank 9 Jambi) Eko Suprapto; Ifan Sadewa; Salsabila Dwi Fitri
Jurnal Ilmu Manajemen Terapan Vol. 5 No. 4 (2024): Jurnal Ilmu Manajemen Terapan (Maret - April 2024)
Publisher : Dinasti Review Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jimt.v5i4.2725

Abstract

Penelitian ini bertujuan untuk menganalisis peran digital marketing dalam meningkatkan citra bank melalui dimensinya fulfillment/reliability¸ website design, customer service, dan secutity/privacy. Populasi dalam penelitian ini adalah nasabah Bank Jambi Kantor Cabang Pembantu Singkut, sampel yang diambil sebanyak 100 orang. Sumber data yaitu data primer dan data sekunder. Metode pengumpulan data menggunakan observasi, wawancara dan kuesioner. Analisis data dilakukan dengan metode kuantitatif dengan bantuan Smart-PLS. Hasil penelitian menyimpulkan bahwa digital marketing melalui dimensi fulfillment/reliability¸ website design, customer service, dan secutity/privacy memiliki pengaruh yang signifikan terhadap citra bank dengan dimensi likeability, competence, quality, performance, dan responsibility. Hal ini menjelaskan bahwasanya jika kegiatan digital marketing dapat dimaksimalkan dengan baik oleh manajemen perusahaan, maka hal ini akan membentuk citra perusahaan yang semakin baik.
Implementasi Model Support Vector Machine Dalam Analisa Sentimen Masyarakat Mengenai Kebijakan Penerapan Aplikasi Mypertamina Salsabila Dwi Fitri; Dewi Lestari; Rizqa Raaiqa Bintana; Reni Aryani; Mohamad Ilhami; Yolla Noverina
Bridge : Jurnal Publikasi Sistem Informasi dan Telekomunikasi Vol. 2 No. 2 (2024): Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/bridge.v2i3.180

Abstract

The policy for using the MyPertamina application issued does not rule out the possibility of differences of opinion due to changes in the policy. There are many positive, neutral, and negative responses to the MyPertamina application implementation policy. To see the public's reaction to the MyPertamina application implementation policy, it can be seen through various media, including social media. Twitter is a social network that is widely used by people in Indonesia. The number of Twitter users in Indonesia reached 18.45 million in 2022, making Indonesia the fifth largest Twitter user country in the world. Researchers conducted a sentiment analysis of the search results for tweets containing the keyword "MyPertamina" using the support vector machine algorithm. 382 tweet data were obtained and classified using the support vector machine algorithm. Support vector machine is a supervised learning algorithm for data classification. SVM is very fast and effective in solving text data problems. Text data is suitable for classification with the SVM algorithm because the basic nature of text tends to be high-dimensional. Of the 382 data analyzed, the support vector machine classification using the RBF kernel with parameter C=2 gave the highest accuracy value of 80.51%, precision value of 81%, recall value of 81%, and F1 score value of 80%.
Co-Authors Aryani, Reni Dewi Lestari Eko Suprapto Ifan Sadewa Mohamad Ilhami Rizqa Raaiqa Bintana Yolla Noverina