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All Journal Asian Journal of Management Analytics Jurnal Sains, Teknologi dan Komputer
Mutiara Akbar Nasution
Universitas Negeri Medan
Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Analysis of Financial Statements to Measure the Financial Performance of PT. Unilever Indonesia Tbk. Period 2020-2022 Mutiara Akbar Nasution; Lukas Destria Putra Ginting; Anisa Fitri; Nurdina Safitri
Asian Journal of Management Analytics Vol. 2 No. 2 (2023): April 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ajma.v2i2.3896

Abstract

Analyzing financial statements is not only to find out whether a company's financial performance is good or bad; it can also be used to determine or build a strategy for future company planning. The type of research we use is descriptive-quantitative. The population and sample used in this study are the company's financial statements from PT. Unilever Indonesia Tbk. for the period 2020–2022. By using data analysis techniques that use indicators on each finance, it can be compared between one period and another. Finance PT. Unilever Indonesia Tbk. appears to fluctuate towards worsening due to the difficulty in paying both short-term and long-term liabilities.
Implementasi NLP Dalam Pembuatan Chatbot Customer Service Publisher Jurnal Studi Kasus LARISMA Mutiara Akbar Nasution; Anisa Fitri; Khesya Sabilah Rizwinie; Vetryc Styphen Silaban; Fihi Khoirani
Jurnal Sains, Teknologi & Komputer Vol. 1 No. 1 (2024): Jurnal Sains, Teknologi & Komputer (SAINTEK)
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/saintek.v1i1.451

Abstract

This research aims to develop a Customer Service Chatbot for Larisma Journal Publisher that can effectively answer questions and reduce response time to questions that are often similar. This research will design a Chatbot system that can facilitate users in interacting and finding information related to journal publishing, by applying Natural Language Processing. This chatbot system uses training data collected from various questions commonly asked by authors to produce accurate information, with data analysis methods involving preprocessing, training and model building. Testing the accuracy of this chatbot was carried out by the designer through a terminal in Google Colab by viewing and assessing the suitability between the questions and the answers generated. The test results state that this chatbot is able to provide effective responses by evaluating answers based on keywords in the chatbot, so as to provide the right answers.
Co-Authors Anisa Fitri Fihi Khoirani Khesya Sabilah Rizwinie Lukas Destria Putra Ginting Nurdina Safitri Vetryc Styphen Silaban