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All Journal Jurnal Penelitian Fisika dan Aplikasinya (JPFA) JURNAL RECTUM: Tinjauan Yuridis Penanganan Tindak Pidana Jambura Arena Sport
Triana, Devi
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Humanities Astronomy Earth & Planetary Sciences Education Health Professions Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Physics Public Health Social Sciences Other

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Identification of COVID-19 Based on Features Texture Histogram and Gray Level Co-Occurrence Matrix (GLCM) Using K-Means Clustering Methods in Chest X-Ray Digital Images Sumarti, Heni; Sabrina, Qolby; Triana, Devi; Septiani, Fahira; Rahmani, Tara Puri Ducha
Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Vol. 13 No. 1 (2023)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jpfa.v13n1.p51-66

Abstract

Since the last five years of the COVID-19 outbreak, radiological images, such as CT-Scan and Chest X-Ray (CXR), have become essential in diagnosing this disease. However, limited access to facilities such as CT-Scanners and RT-PCR makes CXR images the primary method for COVID-19 testing. This research aims to improve the accuracy of CXR images in identifying COVID-19 patients based on the texture features: histogram and Gray Level Co-occurrence Matrix (GLCM), using the K-Means Clustering method. This study utilized 150 CXR images, including 75 COVID-19 patients confirmed by RT-PCR tests, and 75 patients with negative cases. The method used were consisted of pre-processing, and texture feature extraction with the seven most influential attributes based on gained information (histogram: standard deviation, entropy, skewness, kurtosis, and GLCM: correlation, energy, homogeneity), as well as classification using K-Means clustering methods. The results showed that the classification’s accuracy, sensitivity, and specification are 92%, 91%, and 93%, respectively. This image processing technique is a promising as well as a complementary tool in diagnosing COVID-19 cases, based on CXR images with lower costs and more reliable results.
AN ANALYSIS ACTIVE VOICE AND PASSIVE VOICE USED ON INSTAGRAM CAPTIONS WRITTEN BY K-POPERS Triana, Devi; Simorangkir, Tessaria; Sidabalok, Anzelly Hernita
JURNAL RECTUM: Tinjauan Yuridis Penanganan Tindak Pidana Vol 4 No 2 (2024): EDISI 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Universitas Darma Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46930/jurnalrectum.v4i2.5111

Abstract

This study aimed to analyze active voice and passive voice used on Instagram captions written by K-Popers. The existence of social media has become common communication among K-Popers national and internasional boundries. Instagram is the most social media platform as a mobile application for sharing photos, video and stories. K-Popers usually upload their idols' photos ot videos on Instagram, and they usually use English as their caption put on their post. Through the English captions on Instagram, active voice and passive voice appears in their English. This study used library research design. The writers chose the accounts from hastag #Kpop. The writers had figured out the data which were posted on Januari to July 2024 from two K-Popers which have been choosen in the form of sentences on Instagram captions. Two K-Popers in different accounts which have been choosen by writers, they are @sunghoonsfav and @syaquilla.1. The writers analyzed 20 Captions from two K-Popers accounts. Based on the analysis result by screenshot the K-Popers post with #Kpop, Active voice in the form of simple present tense was the most appears in this study, especially on Instagram accounts of @sunghoonsfav and @syaquilla.1. It appears 13 times from both K-Popers account. It can be concluded that Active voice in form of simple present tense was the most common appear used on Instagram captions written by K-Popers.
A COMPARATIVE STUDY ON THE ACCURACY OF THE TRANSLATION OF ENGLISH NARRATIVE TEXT INTO INDONESIAN USING GOOGLE TRANSLATE AND CHAT GPT AI Triana, Devi; Sembiring, Yena Jorena; Lumbantobing, Nessa Tri Fanny; Sihaloho, Angel Lamtama; Sinurat, Bloner
JURNAL RECTUM: Tinjauan Yuridis Penanganan Tindak Pidana Vol 4 No 2 (2024): EDISI 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Universitas Darma Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46930/jurnalrectum.v4i2.5438

Abstract

This study employs a descriptive qualitative method to compare the accuracy of translating two narrative texts from English into Indonesian using Google Translate and ChatGPT. The narrative texts were sourced from Detik.com and translated using both tools. The goal of this study is to evaluate grammatical precision, contextual consistency, and fluency in the translations. The findings reveal that ChatGPT excels in maintaining context and coherence, delivering more accurate and natural translations compared to Google Translate. Google Translate tends to be less accurate, particularly when handling more complex contexts. These findings suggest that ChatGPT can provide more reliable and relevant translations, particularly for communication and language learning purposes.
Analisis Gerak Tendangan Kuda Pencak Silat Kategori Tunggal Triana, Devi; Said, Hariadi; Kadir, Sulasikin Sahdi
Jambura Arena Sport Vol 2, No 1: Maret 2025
Publisher : Gorontalo State University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jas.v2i1.25283

Abstract

Penelitian ini bertujuan untuk menganalisis gerak tendangan kuda pada kategori tunggal siswa SMK Negeri 1 Gorontalo dalam pencak silat. Metode penelitian yang digunakan adalah analisis gerak dengan menggunakan teknik pengukuran sudut dan observasi gerakan tubuh pada dua sampel siswa. Hasil penelitian menunjukkan bahwa persilangan kaki pada sikap awal sampel 1 membentuk sudut 109°, sedangkan sampel 2 membentuk sudut -33°. Pada tahap berbalik arah, kedua sampel menunjukkan posisi tangan di depan dada. Tahap bersiap menunjukkan tumpuan pada kedua tangan dan ujung kaki. Pada tahap angkat tungkai, sudut horizontal yang terbentuk pada sampel 1 adalah 64,5°, dan pada sampel 2 adalah 53°. Pada tahap eksistensi maksimal lutut, sampel 1 memiliki sudut 68,1°, sementara sampel 2 sebesar 42,4°. Pada sikap akhir, sudut tungkai kiri dan badan sampel 1 adalah 64,3°, sedangkan sampel 2 adalah 72°. Analisis gerakan menunjukkan adanya perbedaan sudut tubuh dan gerakan antara kedua sampel, yang memberikan wawasan tentang teknik tendangan kuda dalam pencak silat kategori tunggal.
Co-Authors Hariadi Said Kadir, Sulasikin Sahdi Lumbantobing, Nessa Tri Fanny Qolby Sabrina, Qolby Rahmani, Tara Puri Ducha Sembiring, Yena Jorena Septiani, Fahira Sidabalok, Anzelly Hernita Sihaloho, Angel Lamtama Simorangkir, Tessaria Sinurat, Bloner Sumarti, Heni