Article Per Year (5 Year)
p-Index From 2021 - 2026
2.338
P-Index
This Author published in this journals
All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Sistim Informasi dan Teknologi Community Development Journal: Jurnal Pengabdian Masyarakat JOURNAL OF LANGUAGE Jurnal Sistim Informasi dan Teknologi Journal of Software Engineering and Information System (SEIS) Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK)
Wardana, Bendra
Politeknik Unggulan Cipta Mandiri
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Health Professions Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences

Published : 13 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 13 Documents
Search

 1   2 
Digital Ethics in Anime: A Critical Analysis of Light Yagami in Death Note for English Learning Lika Silvia Batubara; Bendra Wardana
JOURNAL OF LANGUAGE Vol 8, No 1: May 2026
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/jol.v8i1.13291

Abstract

The rapid advancement of digital technology has significantly transformed how individuals interact, make decisions, and engage with ethical issues, particularly within technology-driven environments. In educational settings, digital media has been widely utilized to support English language learning; however, its implementation has largely emphasized linguistic competence, often overlooking the development of students’ ethical awareness. Despite the growing integration of digital tools in English language teaching, their potential role in fostering ethical reasoning remains insufficiently explored, especially among students in computer-related disciplines. This gap underscores the need for a more integrative pedagogical approach that connects language acquisition with critical ethical reflection. This study aims to investigate how digital ethics is represented through the character Light Yagami in the anime Death Note and to examine its potential as a pedagogical resource in English language teaching. Employing a qualitative descriptive approach, the study applies literary analysis, digital ethics frameworks, and principles of English for Specific Purposes (ESP). The findings indicate that the character embodies central ethical issues such as power, justice, and responsibility, while illustrating how the misuse of authority can result in significant moral consequences. Furthermore, the analysis demonstrates that anime narratives can serve as an effective medium for engaging students with complex ethical dilemmas in technology-oriented contexts. The use of anime also provides meaningful and relatable contexts that enhance language comprehension and stimulate critical thinking. This study contributes to the intersection of digital ethics and ESP by positioning anime as an innovative pedagogical tool for promoting ethical engagement in English language learning.
IDENTIFICATION OF DENTAL AND ORAL DISEASES IN HUMANS USING BAYES THEOREM METHOD Nopi Purnomo; Bendra Wardana; Devi Yuliana; M. Rasyid
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 1 (2025): February 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i1.2591

Abstract

Abstract: Teeth are part of the chewing apparatus in the digestive system in the human body, so they indirectly play a role in the health status of individuals. The mouth is an ideal place for bacteria to multiply due to temperature and humidity. There are several tooth fissures in the mouth so that food residues are easily left behind. Teeth and mouth are very important organs of the body because all diseases will start from diseases in this organ will cause several dangerous diseases that attack other organs of the body. This system was built with the aim of making it easier to identify Dental and Oral Cavity Diseases and producing the highest accuracy in diagnosing these diseases. The expert system was built using the Bayesian theorem method which is the main technique in the process of detecting dental and oral cavity diseases based on the knowledge of an expert. Diagnostic test results with an accuracy level of 61%, Therefore, the research conducted can be said to be successful in diagnosing dental and oral cavity diseases. Keywords: Expert Systems, Identification, Teeth and Oral Cavity, Bayes Theorem. Abstrak: Gigi merupakan bagian dari alat pengunyahan pada sistem pencernaan dalam tubuh manusia, sehingga secara tidak langsung berperan dalam status kesehatan perorangan. Mulut merupakan suatu tempat yang sangat ideal bagi perkembangbiakan bakteri karena temperatur dan kelembaban. Terdapat beberapa fisur gigi di mulut sehingga sisa makanan mudah tertinggal. Gigi dan mulut adalah organ-organ tubuh yang sangat penting karena semua penyakit akan berawal dari penyakit pada organ ini akan menimbulkan beberapa penyakit-penyakit membahayakan yang menyerang organ tubuh lainnya. Sistem ini dibangun dengan tujuan untuk mempermudah mengidentifikasi Penyakit Gigi dan Rongga Mulut serta menghasilkan keakuratan tertinggi dalam diagnosis penyakit tersebut. Sistem pakar yang dibangun menggunakan metode teorema bayes yang merupakan teknik utama dalam proses mendeteksi penyakit Gigi dan Rongga Mulut berdasarkan pengetahuan dari seorang pakar. Hasil pengujian diagnosis dengan tingkat akurasi sebesar 61%, maka dari itu penelitian yang dilakukan ini dapat dikatakan berhasil dalam mendiagnosa penyakit Gigi dan Rongga Mulut. Kata kunci: Sistem Pakar, Identifikasi, Gigi dan Rongga Mulut, Teorema Bayes.
PENERAPAN METODE TEOREMA BAYES DALAM IDENTIFIKASI DAN PENANGANAN PENYAKIT KANDUNGAN Nopi Purnomo; Bendra Wardana; Devi Yuliana; M. Rasyid; Riska Ardilla Hasibuan
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.3734

Abstract

Abstract: Expert systems, a branch of Artificial Intelligence (AI), are designed to represent expert knowledge within a computer system, allowing users to receive solutions as if consulting a human expert. In developing expert systems, an appropriate method is required, one of which is the Bayes Theorem. This method is used to calculate the probability of an event based on available observational data, enabling more accurate disease diagnosis based on patient symptoms. This study applies the Bayesian approach to address uncertainty in identifying gynecological diseases through conditional probability calculations. The data processing results show the probability distribution of various gynecological conditions, including: Anemia (75.38%), Hypertension (14.77%), Placenta Previa (5.00%), Premature Birth (3.00%), Hypotension (0.92%), Hyperemesis Gravidarum (0.63%), Ectopic Pregnancy (0.17%), Ovarian Cyst (0.12%), Uterine Cancer (0.002%), and Endometriosis (0.001%). Based on the findings, anemia is the most commonly experienced condition among pregnant women. Anemia can lead to fatigue, dizziness, fetal developmental disorders, and even premature labor. Therefore, it is recommended to consume iron-rich foods and undergo regular prenatal check-ups to monitor hemoglobin levels and prevent further complications. Keywords: Expert Systems, Identification, obstetric disease, Bayes Theorem. Abstrak: Sistem pakar, yang merupakan bagian dari cabang kecerdasan buatan (Artificial Intelligence), dirancang untuk merepresentasikan pengetahuan seorang pakar ke dalam sistem komputer sehingga pengguna dapat memperoleh solusi seolah-olah berkonsultasi langsung dengan pakar. Dalam pengembangan sistem pakar, dibutuhkan metode yang tepat, salah satunya adalah metode Teorema Bayes. Metode ini digunakan untuk menghitung probabilitas suatu kejadian berdasarkan data observasi yang tersedia, sehingga proses diagnosis penyakit dapat dilakukan secara lebih akurat berdasarkan gejala yang dialami pasien. Penelitian ini menerapkan pendekatan Teorema Bayes untuk menangani ketidakpastian dalam proses identifikasi penyakit kandungan melalui perhitungan probabilitas bersyarat. Hasil pengolahan data menunjukkan distribusi probabilitas beberapa jenis penyakit kandungan, di antaranya: Anemia (75,38%), Hipertensi (14,77%), Plasenta Previa (5,00%), Prematur (3,00%), Hipotensi (0,92%), Hyperemesis Gravidarum (0,63%), Kehamilan Ektopik (0,17%), Kista Ovarium (0,12%), Kanker Rahim (0,002%), dan Endometriosis (0,001%). Dari hasil tersebut, anemia merupakan kondisi paling dominan yang dialami ibu hamil. Anemia berisiko menyebabkan kelelahan, pusing, hambatan perkembangan janin, hingga kelahiran prematur. Oleh karena itu, penanganan yang disarankan meliputi konsumsi makanan kaya zat besi serta pemeriksaan kehamilan secara rutin untuk memantau kadar hemoglobin dan mencegah komplikasi lebih lanjut. Kata kunci: Sistem Pakar, Identifikasi, Penyakit Kandungan, Teorema Bayes.
Co-Authors Devi Yuliana Devi Yuliana, Devi Ginting, Jimmy Nganta Gurning, Lenny Hasibuan, Riska Ardilla Hermanto Hermanto Lika Silvia Batubara M. Rasyid M. Rasyid Nduru, Sastra Wandy Purnomo, Nopi Riska Ardilla Hasibuan Silvia Batubara, Lika Sitompul, Pretty Naomi Sumijan Sumijan, S