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All Journal Information Technology and Telematics Dinamik Elkom: Jurnal Elektronika dan Komputer Jurnal Pekommas CESS (Journal of Computer Engineering, System and Science) Proceeding SENDI_U Jurnal Inspiration SemanTIK : Teknik Informasi Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Teknik Informatika UNIKA Santo Thomas IKRA-ITH ABDIMAS JURTEKSI Informatika : Jurnal Informatika, Manajemen dan Komputer Jurnal Tekno Kompak Progresif: Jurnal Ilmiah Komputer Dinamika Informatika: Jurnal Ilmiah Teknologi Informasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Journal of Telecommunication, Electronics and Control Engineering (JTECE) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Pengabdian Masyarakat Intimas (Jurnal INTIMAS): Inovasi Teknologi Informasi Dan Komputer Untuk Masyarakat Jurnal Ilmu Multidisplin Eduvest - Journal of Universal Studies Jurnal Pengabdian Sosial Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Arief Jananto
Universitas Stikubank
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Journal : Jurnal Teknik Informatika UNIKA Santo Thomas

 1 
Rancang Bangun Sistem Informasi Prediksi Penyakit Jantung Berbasis Algoritma Naive Bayes Wijoyo, Agung Suko; Jananto, Arief
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 8 No. 2 : Tahun 2023
Publisher : LPPM UNIKA Santo Thomas

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Abstract

Heart disease causes death in the world / year. High mortality from heart disease can be prevented and risk factors reduced if people have information about symptoms of heart disease. The number of factors collected to determine whether a person has cardiovascular disease or does not require a large enough data processing system is the heart of the data mining application with the Naive Bayes Classifier (NBC) method. Based on testing of the distribution of training data 80%, 85% and 90% the best accuracy was obtained using the method, namely at 90% training with an accuracy of 84%. The more training data used, the better the accuracy of the resulting NBC method.
Sistem Informasi Pengelolaan Update RME RSUP Dr. Kariadi Berbasis Web Hadinata, Nova Oktaviani; Jananto, Arief
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 9 No. 1 : Tahun 2024
Publisher : LPPM UNIKA Santo Thomas

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Abstract

Electronic Medical Records (RME) at Dr. Kariadi Central Hospital have been used since 2019. As technology develops and the use of RME applications increases, it has resulted in complaints and suggestions from users, to update the RME application to make it better in the future. But currently there is no information system to accommodate these problems. From these problems, a study was conducted to create an information system with the aim that users can document and manage the RME update process through the information system provided. This research uses the waterfall system development method, with the analysis system in the form of interviews and literature studies. As for the system design or modeling language using UML, and the programming language using PHP and MySql as storage / database. From the research conducted, an information system was produced that can document any complaints or suggestions from users, as well as monitoring for any related follow-up related to the RME application update.
Implementasi Algoritma C4.5 Untuk Klasifikasi Data Tracer Study Alumni Di Politeknik Negeri Semarang Dalila, Nisa Aulia; Jananto, Arief
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 9 No. 2 : Tahun 2024
Publisher : LPPM UNIKA Santo Thomas

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Penelitian ini memfokuskan pada analisis klasifikasi data instansi tempat bekerja alumni Politeknik Negeri Semarang menggunakan algoritma C4.5. Sumber data utama adalah data tracer study alumni yang diunduh dari sistem informasi tracer study Politeknik Negeri Semarang mulai tahun kelulusan 2018 sampai dengan 2023. Pemodelan dengan algoritma C4.5 untuk menghasilkan pohon keputusan. Data sample sebanyak 100 record digunakan untuk menghitung nilai entropy dan gain dari masing-masing atribut, di mana atribut program studi memiliki nilai gain tertinggi sebesar 0,8951 dan menjadi akar pertama dari pohon keputusan. Uji coba lebih lanjut dilakukan dengan 2000 record data preprocessing menggunakan berbagai proporsi data training dan testing. Nilai akurasi tertinggi sebesar 73,3% didapatkan dari prosentase 70% data training dan 30% data testing yang menandakan model ini berhasil menangkap pola data dengan akurasi yang cukup memadai. Dari penelitian ini diharapkan memberikan wawasan tentang faktor-faktor yang mempengaruhi jenis instansi tempat alumni bekerja dan menunjukkan efektivitas algoritma C4.5 dalam klasifikasi data tracer study alumni.
Co-Authors - Yanuardi . Narwati Achmad Naufal Luqmanul Khakim ACHWAL, SAEFUL Afandi Afandi Afianti, Dwi Sekar Agus Prasetyo Utomo Alexander Radityo Wibowo Anjani, Nabila Antania Putri BEKRI MURDIANTO Budi Hartono Dalila, Nisa Aulia Desy Exasanti Dewi Handayani Untari Ningsih Dhimas Hernandi Diartonor, Dwi Agus Dwi Agus Diartono Eddy Nurraharjo Edy Winarno Ekasetya, Vada Annisa Eko Nur Wahyudi ellang putro priambodo Eri Zuliarso Fadhila Putri Utami Fadhilah, Annisa Nur Fatkhul Huda, Alfian Hadinata, Nova Oktaviani Hafizhannia Rahma Hardya Hekmatiar, Altida Heribertus Yuliaton Herny Februariyanti Herny Februariyanti Herny Februariyanti Huda, Alfian Fatkhul Ifa Musdalifah Jeffri Alfa Razaq Kharisma, Ema Titania Laila, Tsurayya Nur Lailil ‘ Izzah Maulidiya, Hita Mohammad Dwi Arianto Muji Sukur Muji Syukur MURDIANTO, BEKRI Nabila, Alicia Ayu Nanda Ayu Rahmalinda Novita Mariana Putra, Yuan Anggara R. Mochammad Armand Giri Seno Raka W, Arnandia Rara Sri Artati Redjeki Rieke Reza Andarista Rizky Robby Setiawan S.Pd. M Kes I Ketut Sudiana . Saufika Sukmawati Setiyorini, Akhdiyan Setyawan Wibisono Solechati, Riska Grahastika Sri Eniyati Sugiyamta Sugiyamta Sulastri Sulastri Sulastri Sunardi . Sunardi Sunardi Taufiq Dwi Cahyono Teguh Khristianto Widodo, Rizky Andaru Wijaya, Arnandia Raka Wijoyo, Agung Suko Wiwien Hadikurniawati Yahya, Noerzam Yohanes Suhari Yunus Anis, Yunus