Article Per Year (5 Year)
p-Index From 2021 - 2026
5.893
P-Index
This Author published in this journals
All Journal Syntax Jurnal Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA Conference on Innovation and Application of Science and Technology (CIASTECH) Jambura Journal of Informatics CCIT (Creative Communication and Innovative Technology) Journal Building of Informatics, Technology and Science Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Buana Ilmu JISA (Jurnal Informatika dan Sains) Jurnal Sisfotek Global JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Teknik Informatika (JUTIF) Jurnal Pendidikan dan Teknologi Indonesia Jumat Informatika: Jurnal Pengabdian Masyarakat Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Jurnal Sisfotek Global Jurnal Sosial dan Abdimas Scientific Student Journal for Information, Technology and Science Jurnal Algoritma Jurnal Buana Pengabdian Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Innovative: Journal Of Social Science Research Jurnal Informatika: Jurnal Pengembangan IT TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Juwita, Ayu Ratna
Universitas Buana Perjuangan
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Public Health Social Sciences Other

Published : 46 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 46 Documents
Search

 1   2   3   4   5 
Penerapan Metode Naive Bayes Dalam Klasifikasi Spam SMS Menggunakan Fitur Teks Untuk Mengatasi Ancaman Pada Pengguna Azzahra, Fathimah Noer; Rohana, Tatang; Rahmat, Rahmat; Juwita, Ayu Ratna
Journal of Information System Research (JOSH) Vol 5 No 3 (2024): April 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i3.5070

Abstract

One of the negative impacts of current digital advances is the increasing number of SMS spam. Spam SMS poses a security risk to users because they can contain malicious links or requests for personal information that are used for malware, smishing, or fraud attacks. However, with the various protection measures available, not all spam SMS can be classified and prevented effectively. However, this problem can be minimized by creating an anti-spam SMS model which aims to classify SMS types. So this research aims to classify types of SMS that contain spam and spam by applying the Naïve Bayes algorithm. In this study, the dataset consisted of 5572 records consisting of 2 categories, namely spam and ham. This algorithm is able to show satisfactory performance in differentiating spam and spam messages because, according to the diversity of literature, the Naïve Bayes algorithm is suitable for use in English language datasets. The evaluation model displays good results with accuracy reaching 93.2%, precision 93.7%, recall 93.2%, and F1-score 91.6%. In addition, analysis in the research using the Receiver Operating Characteristic (ROC) curve shows an accuracy rate of 97.3%, indicating that the model has very good performance in classifying spam in SMS messages. However, there is still room for improvement through the use of new methods and larger and more diverse data sets. This research has an important involvement in working on communication security and user experience in using short message services.
Analisis Sentimen Pemboikotan Produk dengan Pendekatan Algoritma Naïve Bayes Media Sosial X Rifaldi, Rizky; Indra, Jamaludin; Pratama, Adi Rizky; Juwita, Ayu Ratna
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5420

Abstract

This research aims to analyze sentiment regarding the problem of product boycotting by the public using the Naive Bayes algorithm. 1426 data were collected from social media x to study consumer behavior towards certain products. Through the application of the Naive Bayes algorithm, sentiment analysis was carried out to identify patterns in consumer opinions regarding boycotting the products studied. Experimental results show that the Naive Bayes algorithm succeeded in achieving 81% accuracy in classifying sentiment towards products. This shows the algorithm's ability to analyze consumer sentiment effectively, which can provide valuable insights for companies in understanding public perception and managing the reputation of their products. The practical implication of this research is the importance of utilizing sentiment analysis techniques in marketing strategy and brand management to increase product competitiveness in a competitive market.
Penerapan Metode Regresi Logistik Untuk Memprediksi Peristiwa Biner Pasien Pasca Operasi Kanker Payudara Sujana, Sylvia; Juwita, Ayu Ratna; Rahmat, Rahmat; Faisal, Sutan
Journal of Information System Research (JOSH) Vol 5 No 4 (2024): Juli 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i4.5521

Abstract

Breast cancer is the second leading cause of death in women worldwide. To overcome this growing problem, this study designed a model that can predict breast cancer by utilizing datasets and then processed using the Logistic Regression Prediction method. This method is appropriate for predicting the data used because of its ability to handle dependent variables that are categorical and provide outups in the form of probabilities. This study uses a dataset of 306 samples with 4 attributes. Data used Research steps include data collection, preprocessing, modeling with logistic regression and evaluating results using matrices such as confusion matrix, MAE, MSE, and R-Square. The results showed a prediction accuracy of 86%, with an MSE value of 0.137 and R-Square of 0.309. This study shows the effectiveness of logistic regression in predicting the survival of patients after breast cancer surgery. However, by applying different algorithms, this study can select the best set of significant attributes to increase the prediction accuracy value in postoperative breast cancer patients.
Air Quality Classification Using Naive Bayes Algorithm With SMOTE Technique Based on ISPU Data Fadhilah, Alya Febriyanti; Juwita, Ayu Ratna; Wicaksana, Yusuf Eka; Mudzakir, Tohirin Al
JISA(Jurnal Informatika dan Sains) Vol 8, No 1 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i1.2181

Abstract

Air pollution in DKI Jakarta is an important issue and has a negative impact on public health. This study applies the naive Bayes algorithm to classify air quality, Utilizing the SMOTE technique effectively addresses the issue of data imbalance. The data analyzed came from air pollution index data from 2022 to 2024, taken from five air monitoring stations in Jakarta. The analysis process was carried out following the CRISP-DM stages, starting from understanding the problem to evaluating the model. The results showed that SMOTE succeeded in increasing prediction accuracy in fewer classes. Without SMOTE, the model accuracy reached 90% but appeared biased towards fewer classes, with a recall value of only 0.75 and a precision of 0.62. While SMOTE, the model accuracy became 88%, with a precision value of 0.86, recall 0.87, and f1-score 0.87, which showed more balanced results across classes.
Analisis sentimen twitter terhadap steam menggunakan algoritma logistic regression dan support vector machine Edo Ridho Lidinillah; Tatang Rohana; Ayu Ratna Juwita
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 10 No 2 (2023): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v10i2.440

Abstract

Games online yakni hal yang sudah menempel di masyarakat saat ini. Dalam beberapa tahun terakhir, ekspansi internet dan perangkat yang cepat telah mempercepat munculnya games online. Motivasi utama pemain untuk terus bermain games online adalah ketersediaan kemampuan games online multi-pengguna yang dapat diakses di mana saja. Seiring perkembangan teknologi saat ini banyak platform penjualan games online seperti Steam, Epic Games Store, Origin dan sebagainya, opini masyarakat terkadang sulit dikomunikasikan secara eksklusif kepada pengelola khususnya develover Steam sebagai platform penjualan games, Ini mendorong individu untuk mengirimkan komentar, penilaian, dan konten serupa melalui media sosial, salah satu jejaring sosial yang paling terkenal saat ini ialah Twitter. Deretan tweet atau opini asal pengguna Twitter terkait platform Steam yang mana dapat dipergunakan menjadi analisis sentimen. Dalam penelitian ini data yang terkait menggunakan platform Steam dikumpulkan sampai 4363 data ulasan positif dan negatif terhadap platform steam dalam twitter, memakai TextBlob Library yang menyediakan API sederhana buat menyelam ke pada tugas Natural Language Processing (NLP) kemudian diproses menggunakan metode penambangan data (data mining), termasuk penambangan teks, cleaning, case folding, tokenization, filtering stopword, serta wordcloud. Untuk menghitung menggunakan metode Confusion Matrix dalam 2 algoritma yang berbeda buat perbandingan, algoritma yang digunakan adalah Logistic Regression dan Support Vector Machine. Dari percobaan perhitungan 2 metode itu diketahui bahwa algoritma Super Vector Machine mendapatkan nilai yang optimal dengan accuracy 0.81, precision 0.85 serta recall 0.77
Optimalisasi Keterampilan Desain Grafis Siswa Dengan Pemanfaatan Aplikasi Digital untuk Meningkatkan Daya Cipta Hemdani Rahendra Herlianto; Antika Zahrotul Kamalia; Ayu Ratna Juwita; Komara; Nur Alyah Agustin
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 1 (2026): Juli 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i1.1438

Abstract

Kegiatan Pengabdian kepada Masyarakat ini bertujuan meningkatkan keterampilan desain grafis dan daya cipta siswa SMAN 1 Cikarang Timur melalui pemanfaatan aplikasi digital. Pelaksanaan kegiatan menggunakan pendekatan partisipatif dan Project-Based Learning melalui tahap asesmen awal, penyampaian prinsip desain, pelatihan Canva, praktik proyek, pendampingan, showcase, dan evaluasi. Evaluasi dilakukan menggunakan pre-test, post-test, serta penilaian portofolio. Hasil menunjukkan peningkatan rata-rata kemampuan siswa dari 47,4% menjadi 87,0%. Peningkatan mencakup pemahaman prinsip desain, penguasaan aplikasi, komposisi visual, kreativitas, serta etika dan hak cipta digital. Kegiatan ini membuktikan bahwa pelatihan berbasis praktik dan proyek efektif meningkatkan kemampuan siswa dalam menghasilkan karya visual yang kreatif, komunikatif, orisinal, dan bertanggung jawab.
Co-Authors AA Sudharmawan, AA Adi Rizky Pratama Adi Rizky Pratama Adi Rizky Pratma Agustina Mardeka Raya Ahmad Fauzi Alganiu, Ajeng Shalwa Amansyah, Ilham Amril Mutoi Siregar Antika Zahrotul Kamalia ARIF, SITI NOVIANTI NURAINI Awal, Elsa Elvira Azzahra, Fathimah Noer Baharuddin Risyad Carudin, Carudin Cici Emilia Sukmawati Cici Emilia Sukmawati Dina Wulan Nurjanah Edo Ridho Lidinillah Fadhilah, Alya Febriyanti Faisal, Muhamad Agus Faisal, Sutan Fauzi, Farras Ahmad Fitri Nur Masruriyah, Anis Fransiskus Panca Juniawan Hanny Hikmayanti Handayani Hemdani Rahendra Herlianto Heryana, Nono Indra, Jamaludin Irawan, Muhamad Anggi Khairani, Nova Pustita Komara Kukuh Ardy Nugroho Lestari, Santi Arum Puspita Lusiana Rahmatiani Mayasari, Rini Mudzakir, Tohirin Al Mulyana, Assyifa Alif Rahayu Novalia, Elfina Nugraha, Bagja Nugraha, Najmi Cahaya Nur Alyah Agustin Nurlaelasari, Euis Nurmayanti, Trisya nurul latifah Permana, Tedi Pratama, Adi Rizky Pratama, Adi Rizky Purwani Husodo Rahmat Rahmat Rahmat Sulaiman Rahmat Sulaiman Rifaldi, Rizky Riyandi Aditya Fitrah Rizki Mohamad Eka Marsa Sadjat rizky pratama, adi Rohana, Tatang Saefulloh, Nandang Siregar, Amril Mutoi Siti Silvia Arifin Sujana, Sylvia Sukmawati, Cici Emilia Tatang Rohana Tatang Rohana Tejayanda, Rigger Damaiarta Tohirin Al Mudzakir Tohirin Al Mudzakir Tohirn Al Mudzakir Tri Sugihartono Triono Triono Triono Triono Wahiddin, Deden Wenda Adi Kusnaya Wicaksana, Yusuf Eka Yaman, Nuurul Izzati Yana Cahyana Yudi Firmansyah