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All Journal Indonesian Journal on Software Engineering (IJSE) Journal of Technopreneurship and Information System (JTIS) Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Jurnal Sistem Informasi Akuntansi Conten : Computer and Network Technology J-Intech (Journal of Information and Technology)
Wati, Fanny Fatma
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Library & Information Science

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ANALISIS TINGKAT KESEHATAN PERBANKAN MENGGUNAKAN METODE RISK-BASED PADA PT.BANK MUAMALAT INDONESIA Sari, Ratna Kurnia; Wati, Fanny Fatma; Widodo, Andrian Eko; Abidin, Muhammad Ali Zaenal
Jurnal Sistem Informasi Akuntansi (JASIKA) Vol. 2 No. 2 (2022): Oktober 2022
Publisher : LPPM UBSI Kampus Kota Tegal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jasika.v2i2.1510

Abstract

Banking is a financial institution that has great potential and enormous social value to grow and develop in carrying out its role as a source of financing for customers and the business sector, especially in facing the era of globalization in a country, especially Indonesia. Likewise, the soundness of a bank becomes a barometer of the ability to compete in the business world, because a bank is a company. Therefore, it is very important to maintain public trust in its performance. Based on Bank Indonesia regulation, bank soundness assessment will be very useful in implementing Good Corporate Governance and for dealing with future risks. The Risk-Based Bank Rating method is a policy issued by the government as a tool for assessing the soundness of a bank with the scope of the assessment covering the following factors: Risk profile, Good Corporate Governance , Profitability and Capital to produce a composite rating of bank soundness. The purpose of this study was to determine the soundness of the bank on the balance sheet items, profit and loss and cash flow as well as the financial performance of PT. Bank Muamalat Indonesia Tbk uses the Risk-Based Bank Rating method for 3 years. The results of the research generally show that PT Bank Muamalat Indonesia Tbk is in the composite rank 3 with the criteria of "Sufficiently Healthy". This indicates that the bank's condition is generally quite healthy and able to face significant negative effects from changes in business conditions and other external factors.
Perancangan Dashboard Untuk Manajemen Penjualan Produk Pada Perusahaan XYZ Dalam Pengambilan Keputusan Bisnis Nurohim, Galih Setiawan; ahmad fauzi; Akbar, Muhammad Faitullah; Wati, Fanny Fatma
Jurnal Sistem Informasi Akuntansi (JASIKA) Vol. 4 No. 01 (2024): Mei 2024
Publisher : LPPM UBSI Kampus Kota Tegal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jasika.v4i01.3461

Abstract

XYZ is a company engaged in marketing and analytics. To improve sales efficiency and product management, XYZ requires the implementation of a dashboard for visualizing sales data. This dashboard is expected to provide accurate information that is useful for business decision-making and monitoring sales progress. The development method used in the design of this dashboard is prototype, and the tool used for data visualization is Chart.js. The sales data used is real-time data obtained from the previously developed web application. This dashboard allows for the visualization of various aspects of sales, including customer distribution, sales percentages by product, and evaluation of factors influencing repeat purchase decisions
ANALISIS SENTIMEN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR PADA REVIEW APLIKASI SHOPEE Wati, Fanny Fatma; Hidayati, Nadiyah; Maulidah, Mawadatul; Widodo, Andrian Eko; Astuti, Rachmawati Darma
CONTEN : Computer and Network Technology Vol. 5 No. 2 (2025): Desember 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/conten.v5i2.10116

Abstract

E-commerce merupakan media yang memfasilitasi transaksi komersial antara individu dengan individu maupun antara individu dan organisasi melalui sistem daring. Salah satu bentuk implementasi e-commerce adalah aplikasi Shopee. Shopee dikembangkan sebagai aplikasi berbasis perangkat mobile yang memungkinkan pengguna melakukan aktivitas belanja secara online dengan mudah, sehingga transaksi dapat dilaksanakan dimanapun dan kapanpun. Aplikasi tersebut tentunya mempunyai kekurangan dan kelebihan yang dirasa oleh masyarakat. Dari adanya kekurangan dan kelebihan aplikasi shopee tidak sedikit masyarakat yang memberikan ulasan negatif maupun positif terhadap aplikasi tersebut. Pemanfaatan data dalam jumlah besar dapat dilakukan melalui penerapan teknik Data Mining. Penelitian ini bertujuan untuk menganalisis berbagai masalah yang dituju terhadap pengguna terhadap aplikasi Shopee di Google Play Store serta mengukur tingkat akurasi analisis sentimen yang dihasilkan menggunakan algoritma K-Nearest Neighbors (KNN). Menghasilkan bahwa dengan algoritma KNN diperoleh nilai akurasi Pred.Negatif nilainya sebesar 69,59%. Hasil dari Pred.Positif nilainya sebesar 71,70%.  Sedangkan nila accuracy 70,51% dan nilai AUC sebesar  0.804 +/- 0.053 (mikro: 0.804) (positive class: Positif).   E-commerce is a means of commercial transactions between individuals and organizations or a buying and selling transaction conducted online. One example of e-commerce implementation is the Shopee application. Shopee is available in the form of a mobile phone application that makes it easier for users to shop online, allowing access anytime and anywhere. Of course, this application has advantages and disadvantages perceived by the public. Due to the application’s strengths and weaknesses, many users provide both positive and negative reviews of the app. Techniques for utilizing large amounts of data can be applied through Data Mining. The purpose of this research is to analyze issues related to several reviews of the Shopee application on Google Play Store and to determine the accuracy results of sentiment analysis generated using the KNN (K-Nearest Neighbors) algorithm. The result showed that with KNN algorithm obtained the value of Pred. Negative accuracy value of 69.59%. Results from Pred. Positive value of 71.70%.  While accuracy value 70.51% and AUC value of 0804 +/-0053 (Micro: 0804) (positive class: positives). 
Co-Authors Abidin, Muhammad Ali Zaenal Abror, Dzulchan Ahmad Fauzi Akbar, Muhammad Faitullah Andrian Eko Widodo Anggraini, Recha Abriana Aprih Widayanto Astuti, Rachmawati Darma Crisna, Aditia Dany Pratmanto Doni Purnama Alamsyah Fabriyan Fandi Dwi Imaniawan Fauzi, Ahmad Galih Setiawan Nurohim Mawadatul Maulidah Nadiyah Hidayati Rousyati, Rousyati Sari, Ratna Kurnia Sukmawati, Linda Suleman Suleman