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All Journal Worksheet : Jurnal Akuntansi Jurnal Sains dan Teknologi Informasi
Tarigan, Devanta Abraham
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering

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KINERJA KEUANGAN PERBANKAN DALAM PERSPEKTIF CAMEL: EVALUASI EMPIRIS TERHADAP PT BANK NATIONAL NOBU TBK Anshor, Khairi; Soraya, Nurhaflah; Ginting, Rika Githamala; Arifyanto, Gatot Teguh; Tarigan, Devanta Abraham
Worksheet : Jurnal Akuntansi Vol 4, No 2 (2025)
Publisher : UNIVERSITAS DHARMAWANGSA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/wjs.v4i2.6413

Abstract

Penelitian ini bertujuan untuk menganalisis tingkat kesehatan keuangan PT. Bank Nationalnobu Tbk selama periode 2020 hingga 2023 berdasarkan pendekatan rasio keuangan yang mencakup Capital Adequacy Ratio (CAR), Non-Performing Loan (NPL), Return on Assets (ROA), Net Profit Margin (NPM), dan Loan to Deposit Ratio (LDR). Metode analisis yang digunakan bersifat deskriptif kuantitatif dengan mengacu pada standar penilaian kesehatan bank yang ditetapkan oleh Bank Indonesia. Hasil penelitian menunjukkan bahwa bank berada dalam kategori cukup sehat pada tahun 2020 hingga 2022, ditandai oleh rasio CAR dan NPL yang stabil dan tinggi. Namun, pada tahun 2023, terjadi penurunan peringkat kesehatan bank menjadi kurang sehat yang disebabkan oleh peningkatan signifikan pada rasio LDR hingga 99,67%, yang mencerminkan potensi risiko likuiditas. Dengan demikian, meskipun kinerja permodalan dan kualitas aset cukup baik, bank perlu meningkatkan efisiensi operasional dan pengelolaan likuiditas untuk menjaga kestabilan keuangannya secara berkelanjutan.
Review Produk Iphone dengan Analasis Sentimen menggunakan Algoritma Text Mining TF-IDF Tarigan, Devanta Abraham
Jurnal Sains dan Teknologi Informasi Vol 4 No 2 (2025): Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v4i2.7799

Abstract

The iPhone is a product that has become a major concern in society and has become one of the main needs in everyday life. However, sometimes the iPhone often faces several problems that need attention. One problem that is often the main focus is the fairly high price. Therefore, we need a system that can determine the public's view of the iPhone product. This research uses text mining and TF-IDF to determine people's views on iPhone products. Text mining can be defined as the discovery of new, previously unknown information and the automatic extraction of valuable information from text from different sources. Meanwhile, TF-IDF is used to determine the frequency value of words in a document. In this research, sentiment refers to people's views on iPhone products, whether positive or negative. The final result of this sentiment analysis is that the positive sentiment value is 68.65% while the negative sentiment value is 31.35%. This is expected to provide information about the extent to which iPhone products are accepted by the public. By understanding people's sentiments, Apple company can take necessary actions to improve product quality and user satisfaction. Apart from that, this research also introduces the concept of Text Mining and the TF-IDF algorithm as a powerful tool for analyzing text data in the context of sentiment analysis.
Co-Authors Anshor, Khairi Arifyanto, Gatot Teguh Ginting, Rika Githamala Soraya, Nurhaflah