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All Journal Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurnal Teknik Mesin, Industri, Elektro dan Informatika Jurnal Penelitian Rumpun Ilmu Teknik Journal Of Informatics And Busisnes Atmosfer: Jurnal Pendidikan, Bahasa, Sastra, Seni, Budaya, Dan Sosial Humaniora JTH: Journal of Technology and Health Modem : Jurnal Informatika dan Sains Teknologi Polygon: Jurnal Ilmu Komputer dan Ilmu Pengetahuan Alam Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Lidia Lali Momo
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Religion Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Nursing

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Journal : Journal Of Informatics And Busisnes

 1 
Prediksi Kelulusan Mahasiswa Tepat Waktu Menggunakan Metode Naïve Bayes Dan Decision Tree Pada Universitas Stella Maris Sumba Sari, Julianti Suwartini Inda; Elfira Umar; Lidia Lali Momo
Journal Of Informatics And Busisnes Vol. 2 No. 3 (2024): Oktober - Desember
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v2i3.1677

Abstract

Timely graduation itself is one of the indicators of the success of students' academic performance. The study period regulations are already set in the provisions of the Minister of Education and Culture of Indonesia. To address this issue, there needs to be a technique to predict graduation. One of the techniques commonly used is data mining. In this study, the authors will compare two data mining methods, namely Naive Bayes Classifier and Decision Tree, to obtain the method with the best accuracy in predicting student graduation. The attributes used for Data Mining Classification consist of 10 attributes: Student ID, Gender, Student Status, Age, Semester 1 Grade Point Average, Semester 2 Grade Point Average, Semester 3 Grade Point Average, Semester 4 Grade Point Average, Cumulative Grade Point Average, and Result attribute. From the test results using RapidMiner tools with two methods that have been conducted, the Decision Tree (C4.5) obtained the accuracy result of 70.18%, and the Naïve Bayes method obtained the highest accuracy result of 71.24%.
Penerapan Algoritma Naive Bayes Untuk Memprediksi Penyakit Malaria Pada Puskesmas Tana Teke Roswita Tanggu; Elfira Umar; Lidia Lali Momo
Journal Of Informatics And Busisnes Vol. 1 No. 1 (2023): April - Juni
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v1i3.205

Abstract

In health care medical records can be used as comparisons and gauges to determine the development of disease in an area.But it's good that the data is being treated as useful data including being able to predict a disease..Malaria cases are infectious and are very dominant in the tropics / subtropics.The puskemas tana teke has the most positive sufferer malaria.The puskemas party doesn't have a system yet to predict malaria., Therefore, to harness information system technology and to prevent malaria earlier, research has been done to predict malaria by means of na ve bayes on tana teke pusemas..The patient's dataset contains 16 attributes and 6 are symptoms of malaria with a total of 118 patients' data.The calculations with na ve bayes show that appropriate symptoms of disease will result in positive predictions..Such predictions can be used for cement conjectures.
Sistem Informasi Pendaftaran Anggota Baru Pada Koperasi Credit Union Mera Ndi Ate Berbasis Web Damaris Sesi Milla; Elfira Umar; Lidia Lali Momo
Journal Of Informatics And Busisnes Vol. 2 No. 3 (2024): Oktober - Desember
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v2i3.1687

Abstract

Koperasi Simpan Pinjam CU Mera Ndi Ate merupakan badan usaha yang dibangun untuk pertumbuhan dan kesejahteraan masyarakat. Namun koperasi ini mempunyai sistem yang tidak efektif dalam proses pendaftaran anggota baru dan pengajuan pinjaman sehingga memakan waktu lebih lama. Dengan permasalahan tersebut maka diperlukan sistem kooperatif berbasis Web untuk menganalisa permasalahan yang terjadi. Sistem kerjasama ini dirancang dengan Unified Modeling Language sebagai metode diimplementasikan ke dalam Database sesuai spesifikasi yang dibutuhkan sehingga sistem yang dibuat lebih mudah, tepat dan cepat bagi petugas administrasi dalam menginput registrasi. anggota baru dan melaporkannya kepada ketua koperasi.
Co-Authors Adelbertus Umbu Janga Andreas Ariyanto Rangga Cecilia D. P. Binti Gabriel Damaris Sesi Milla Desi Yanti Kallu Pare Elfira Umar Gergorius Kopong Pati Herlina Yasinta Duki Indriani Diana Baga Maria Imakulata Ina Talu Maria Liana Bili Maria Wilda Malo Marselina Anjelina Nuhi Marten Sudi Petrus J. Darus Petrus Jois Ghunu Roswita Tanggu Sari, Julianti Suwartini Inda Sartini Poety Serlince Nono Stefanus Dwi Istiavan Mau Stevanus Mau Tarsisius Tamo Ama Vinsensius Aprila Kore Dima Yosua Pati