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All Journal Jurnal Ilmu Manajemen (JIM) International Journal of Scientific and Professional
Ahmad, Fadhil
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Health Professions Medicine & Pharmacology Nursing Public Health Other

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Analisis Pengaruh Makroekonomi, Komoditas Dunia, dan Indeks Dunia terhadap Indeks Harga Saham Gabungan (IHSG) pada Periode 2014-2019 Ahmad, Fadhil
Jurnal Ilmu Manajemen Vol 9, No 1 (2021)
Publisher : UNESA In Collaboration With APSMBI (Aliansi Program Studi dan Bisnis Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (529.25 KB) | DOI: 10.26740/jim.v9n1.p295-310

Abstract

This research explains the influence of inflation, Exchange Rate, BI Rate, GDP, World Gold Price, Crude Oil Price, Dow Jones Industrial Average (DJIA), and Nikkei 225 toward Jakarta Composite Index (JCI). Type of research used in causality research with a quantitative approach. The sample was based on daily time series data from 1 January 2014 until 31 December 2019, using a complete sampling method that consists of 2190 samples. This research used a generalized autoregressive conditional heteroskedasticity (GARCH) method. The result of hypothesis testing by the GARCH method shows that the World Gold Price and Dow Jones Industrial Average significant have a positive effect, Then the Nikkei 225 significant have a negative effect, and then the Inflation, Exchange Rate, BI Rate, and GDP have not significant to the Jakarta Composite Index (JCI). The implication of this research provides information to investors who must pay attention to World Gold Price, Dow Jones Industrial Average, and Nikkei225 if they want to invest in Indonesian.
Implementing Conditional Random Fields on English Text Grammar Analysis Ahmad, Fadhil; Sutabri, Tata
International Journal Scientific and Professional Vol. 4 No. 2 (2025): March-May 2025
Publisher : Yayasan Rumah Ilmu Professor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56988/chiprof.v4i2.81

Abstract

This study explores the implementaion of the Conditional Random Fields (CRF) algorithm in the grammatical analysis of English texts, specifically in the task of Part of Speech (POS) tagging. CRF is a statistical model effective in classifying words into grammatical categories such as nouns, verbs, adjectives, and others. The research methodology includes a literature review and experimental implementation using labeled datasets, integrated into a web-based application. The implementation results demonstrate that the CRF model provides accurate tagging results and can be utilized for sentence structure analysis in English texts. The application is developed using the Python programming language, supported by the NLTK and sklearn-crfsuite libraries, and uses the Flask framework for the user interface. This research is expected to contribute to the development of technology-based tools for English language learning.
Co-Authors Tata Sutabri