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Correlated Naïve Bayes Algorithm to Determine Healing Rate of Hepatitis Patients Yulhendri, Yulhendri; Malabay, Malabay; Kartini, Kartini
International Journal of Science, Technology & Management Vol. 4 No. 2 (2023): March 2023
Publisher : Publisher Cv. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46729/ijstm.v4i2.776

Abstract

The Correlated Naïve Bayes Algorithm is a statistical learning method that has shown promise in predicting the healing rate of hepatitis patients. Hepatitis is a liver disease that can be chronic or acute and affects millions of people worldwide. The healing rate of patients with hepatitis can vary widely depending on various factors such as age, gender, and medical history. The Correlated Naïve Bayes Algorithm takes into account the correlations between the different attributes of patients and their healing rates, unlike the traditional Naïve Bayes Algorithm. This approach has been shown to improve the accuracy of predictions significantly. In this study, the Correlated Naïve Bayes Algorithm was applied to a dataset of hepatitis patients. The dataset contained information about patients' age, gender, medical history, and other attributes that might affect their healing rates. The algorithm was trained on this dataset to predict the healing rate of new patients. The results showed that the Correlated Naïve Bayes Algorithm achieved higher accuracy in predicting the healing rate of hepatitis patients compared to the traditional Naïve Bayes Algorithm. This suggests that the Correlated Naïve Bayes Algorithm could be a useful tool for healthcare professionals in predicting the healing rate of hepatitis patients, and ultimately improving their treatment and care. Furthermore, the study also investigated the importance of different attributes in predicting the healing rate of hepatitis patients. The results showed that age and medical history were the most important factors, followed by gender and other attributes. The findings of this study have significant implications for the medical community, as accurate prediction of healing rates can inform treatment decisions and improve patient outcomes. The Correlated Naïve Bayes Algorithm provides a powerful tool for healthcare professionals in predicting the healing rate of hepatitis patients, and could be extended to other medical conditions. However, it is important to note that the Correlated Naïve Bayes Algorithm has limitations, such as the assumption of independence between attributes. Therefore, future research should investigate alternative methods that can overcome these limitations and improve the accuracy of predictions further.
BRIDGING LANGUAGE BARRIERS IN RURAL TOURISM: A STRATEGIC COMMUNICATION MODEL FOR KADUGENEP VILLAGE Saraswati, Ria; Malabay, Malabay; Yulianti, Yulianti
Getsempena English Education Journal Vol. 12 No. 2 (2025)
Publisher : Universitas Bina Bangsa Getsempena

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46244/geej.v12i2.3456

Abstract

This study aims to develop a strategic communication model for Kadugenep Village to enhance cross-language interactions between local residents and tourists. Employing a mixed-method approach, the research collected qualitative data through interviews and focus group discussions with villagers, tourism stakeholders, and language educators, while a quantitative survey assessed the current linguistic capabilities and communication barriers. The data were also analyzed using using thematic analysis to summarize the villagers’ linguistic abilities and identify the most common communication barriers. The findings revealed that villagers express enthusiasm for engaging with tourists, limited access to formal language education and a lack of practical communication tools pose significant challenges. The proposed model incorporates a combination of basic language training, non-verbal communication strategies, and mobile translation applications to facilitate more effective interactions. The study concludes that a structured yet flexible approach to language learning, adapted to local needs and resources, can significantly improve rural communities’ participation in the tourism economy. Implementing this model in Kadugenep Village has the potential to not only enhance visitor experiences but also promote sustainable tourism development. Future research should explore how similar models can be adapted to other rural tourism destinations with varying linguistic and cultural contexts.
Pengembangan Aplikasi Paket Trip Wisata Terbuka Berbasis Android dengan Metode MADLC Pada PT. Denar Pesona Pieters, Edward; Malabay
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 2 (2026): IKRAITH-INFORMATIKA Vol 10 No 2 Juli 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i2.5724

Abstract

manual, baik dengan mengunjungi perusahaan atau melalui WhatsApp, yang seringmenyebabkan keterlambatan informasi dan kesulitan bagi pelanggan. Penelitian inibertujuan merancang dan mengembangkan aplikasi mobile untuk memudahkanpelanggan dalam memilih paket wisata sesuai kriteria. Aplikasi dibangun menggunakanframework Flutter untuk Android, dengan backend berbasis PHP yang dikelola olehadmin. Sistem ini terintegrasi dengan payment gateway Midtrans untuk memastikantransaksi praktis dan aman. Menggunakan metode pengembangan Mobile ApplicationDevelopment Life Cycle (MADLC), mencakup analisis kebutuhan hingga evaluasisistem. Hasil penelitian menunjukkan bahwa aplikasi ini mempercepat pemilihan paketwisata, meningkatkan pengalaman pengguna, memperbaiki koordinasi antara pelanggandan penyedia jasa, serta menyederhanakan proses transaksi yang sebelumnya manual.
Implementasi Natural Language Processing (NLP) pada Sistem Informasi Layanan Desain Interior dan Evaluasi User Acceptance Test (UAT) Studi Kasus: PT. Astha Tunggal Makmur Sarwoadji, Katon; Komul, Theodora Maria Putri; Malabay, Malabay; Hermansyah, Hermansyah
IKRA-ITH Informatika : Jurnal Komputer dan Informatika Vol. 10 No. 1 (2026): IKRAITH-INFORMATIKA Vol 10 No 1 Maret 2026
Publisher : Fakultas Teknik Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikraith-informatika.v10i1.6309

Abstract

PT. Astha Tunggal Makmur menghadapi tantangan signifikan dalam pengelolaan proyek desain interior yang masih mengandalkan proses manual, sehingga menyebabkan inefisiensi komunikasi dan kesulitan pemantauan progres secara real-time. Penelitian ini bertujuan untuk merancang bangun sistem informasi layanan desain interior berbasis website yang terintegrasi dengan fitur analisis risiko otomatis menggunakan Natural Language Processing (NLP). Metode pengembangan sistem yang digunakan adalah Extreme Programming (XP) yang mencakup tahapan perencanaan, perancangan, pengkodean, dan pengujian. Fitur NLP diterapkan untuk memindai kata kunci negatif dalam laporan progres harian guna mendeteksi potensi kendala proyek sejak dini. Berdasarkan pengujian fungsional menggunakan Black Box Testing, seluruh fitur berjalan sesuai harapan. Selanjutnya, evaluasi User Acceptance Test (UAT) yang melibatkan 15 responden menghasilkan skor rata-rata 88%, yang mengindikasikan bahwa sistem diterima dengan kategori "Sangat Baik" dan efektif dalam meningkatkan transparansi serta efisiensi operasional perusahaan.
Co-Authors A.A. Ketut Agung Cahyawan W Adikara, Fransiscus Agus Herwanto Agus Prasetyo AHMAD FUAD Ahmad Fuad Ahmad Syaukani Albi Rudiawan Saputra Andrew Pratama Andrew Yehezkiel Patasik Andrias Andrias Ari Anggarani, Ari Budi Tjahjono Cipto Dwi Prabowo Dhini Febrasari Diah Aryani, Diah Djunaedi, Bagas Dudung Angkasa Erwan Baharudin Febrianto, Haris Firdaus, M. Dzulfiqar Gamal, Geggy Gamal, Geggy Gihon Lim Hani Dewi Ariessanti Hermansyah Hermansyah Imam Sutanto Immanuel Pierre Luigi Sitorus Irdanuraprida Idris Jhon Viter M Kartini Kartini Kartini kartini, kartini Komul, Theodora Maria Putri Lasmaida Gurning Lazuardi, Maulana Fajar Maratis, Jerry Mega Budiwansyah Muhammad Bagaskara Muhammad Darfiansyah Muhammad Hilmyansyah Mulyo Wiharto Mulyo Wiharto Niko Prasetyawan Aji Nugroho, Kevin Teguh Nur Ichsan, Muhammad Adhe Nurchaerani, Meiyanti Oka Irvian Sinaga Pieters, Edward Popong Setyawati Putra, Syahrizal Dwi R M Salahudin Rafih, Muhammad Raul Irawan Hermanto Rayhan Achmad Riya Widayanti Sadikin, Irma Savitri SARASWATI, RIA Sari, Yumelda Sarwoadji, Katon Simorangkir, Holder Sophiyanto wuryan Syahrizal Dwi Putra Syahrizal Dwi Putra Tiolina Evi Trisia Lusiana Amir Ummanah Ummanah, Ummanah Wahyu Utomo Wahyu, Sawali Yosua Yulhendri Yulhendri Yulianti Yulianti Yuliati -