Article Per Year (5 Year)
p-Index From 2021 - 2026
0.888
P-Index
This Author published in this journals
All Journal PROJECT (Professional Journal of English Education) Prosiding University Research Colloquium Journal of Intelligent Software Systems AT-TAKLIM: Jurnal Pendidikan Multidisiplin
Anisa Nur Azizah
Unknown Affiliation
Humanities Computer Science & IT Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Other

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
AN ANALYSIS OF ILLOCUTIONARY ACTS PERFORMED IN DONALD TRUMP’S VICTORY SPEECH IN THE UNITED STATES ELECTION 2016 Anisa Nur Azizah; Dinar Alpiah
PROJECT (Professional Journal of English Education) Vol 1, No 3 (2018): Volume 1 Number 3, May 2018
Publisher : IKIP Siliwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (605.842 KB) | DOI: 10.22460/project.v1i3.p241-248

Abstract

This study deals with an analysis of illocutionary act in Donald Trump’s utterances in his Victory Speech in the United States election 2016. The objectives of this study are to identify types of illocutionary act used by Donald Trump and to identify the most dominant type of illocutionary act. The data was taken from www.youtube.com.In this study, the researchers applieddocumentation technique in collecting the dataand the descriptive qualitative method was used to analyze the data. The researchers used Yule’s theory forthe types of illocutionary acts.The findings showed that there are five types of illocutionary acts found in this study including declarative (DC) occurs (2), representative (RP) occurs (46), expressive (EV) occurs (38), directive (DR) occurs (7), and commissive (CM) occurs (24).The researchers also find mostly performs in Donald Trump’s utterances in Victory Speech is, and informing his victory and his plan as the new representative act which is refers tostating, asserting, predicting, retelling president of United States to the audience. Keywords:speech acts, illocutionary acts, victory speech.
Upaya Meningkatkan Hasil Belajar IPS Dengan Model Pembelajaran Kooperatif Tipe STAD Pada Kelas IV MI Terpadu Al Muttaqin Sawangan Anisa Nur Azizah
Prosiding University Research Colloquium Proceeding of The 14th University Research Colloquium 2021: Bidang Pendidikan
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (407.486 KB)

Abstract

This study aims to improve social studies learning outcomes by using the STAD typecooperative learning model for the fourth grade students of MI Terpadu Al Muttaqin,Sawangan District, Magelang Regency. The research subjects were 4th grade students ofthe Integrated MI Al Muttaqin, Sawangan District, Magelang Regency which consisted of14 boys and 4 girls. Data collection techniques are documentation, observation, and tests.The analytical technique used is comparative descriptive. The results showed that theSTAD model could improve the social studies learning outcomes of the 4th grade studentsof MI Terpadu Al Muttaqin Sawangan District, Magelang Regency. an increase in cycle 1to 89% of students who completed, then in cycle 2 it increased to 94%. Learning with theSTAD type cooperative model needs to be implemented in social studies learning in theclassroom, because the learning model can improve student learning outcomes. Teachersmust be able to motivate students to be more active in learning by conducting intensiveguidance.
Analisis Faktor-Faktor yang Mempengaruhi Kepuasan dan Motivasi Kerja Karyawan pada Perusahaan Ritel Rifqy Hafizh Priandy; Anisa Nur Azizah; Putri Rahayu; Wahidin; Dwi Andryansyah; Muhamad Kosim
AT-TAKLIM: Jurnal Pendidikan Multidisiplin Vol. 2 No. 7 (2025): At-Taklim: Jurnal Pendidikan Multidisiplin (Edisi Juli)
Publisher : PT. Hasba Edukasi Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.71282/at-taklim.v2i7.787

Abstract

This study aims to identify and analyze the factors influencing employee job satisfaction in retail companies. A qualitative descriptive approach was employed, with data collected through in-depth interviews with employees from various departments within a retail company. The findings reveal several key factors affecting job satisfaction, including a conducive work environment, harmonious relationships between colleagues and supervisors, recognition and appreciation for performance, and a healthy work-life balance. These findings indicate that retail companies need to pay attention to non-financial aspects that directly impact employee motivation and comfort. By understanding these factors, companies can enhance employee performance and reduce turnover rates. This study is expected to serve as a reference for retail management in formulating policies that support employee well-being and productivity.
Classification of Cancer Based on RNA Data Using Elman Recurrent Neural Network Eka Alifia Kusnanti; Anisa Nur Azizah; Alven Safik Ritonga
Journal of Intelligent Software Systems Vol 5, No 1 (2026): July 2026
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v5i1.2754

Abstract

Cancer is one of the deadliest diseases whose number of sufferers continues to increaseevery year. The development of cancer cells can quickly spread to all parts of the bodythrough the bloodstream or from the lymphatic system so that it can cause death. Thiscan happen because there is a disorder that exists in the gene. The basic thing in geneticsis the monitoring of gene expression itself, namely by measuring from mRNA not fromprotein because the sequence of mRNA will hybridize with complementary DNA and RNA.The purpose of this study is to classify cancer based on RNA data using the ElmanRecurrent Neural Network method. In the recurrent network there are two inputs, namelythe actual input and the contextual input. The iteration process is much faster due tofeedback, so parameter updates and convergence are also faster. The data used are RNAdata with four classes, namely BRCA or breast adenocarcinoma (breast cancer), KIRC orkidney renal clear cell carcinoma (kidney cancer), UCEC or uterine corpus endometrialcarcinoma (uterine cancer), and LUAD or lung adenocarcinoma (lung cancer). The datawill be preprocessed using a minmax scaler then classified using ERNN with trials ofdata sharing, learning rate, and the number of hidden layers. The best combinationof parameters was obtained at 20 nodes hidden layer I, 50 nodes hidden layer II, andlearning rate 0.1. In this model, the accuracy reached 99.19 %, sensitivity of 99.03 %and specificity of 99.72 %. The time required for the model is 19 seconds.
Co-Authors Alven Safik Ritonga Dinar Alpiah Dwi Andryansyah Eka Alifia Kusnanti Fitrianingtyas, Anjar Muhamad Kosim Putri Rahayu Rifqy Hafizh Priandy Siti Wahyuningsih Wahidin