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Journal : Jurnal Pepadun

Pembangunan Peta Virtual 3D untuk Gedung K, Gedung H, Gedung I, dan Gedung R di Fakultas Pertanian Universitas Lampung Admi Syarif; Sintiya Paramitha; Aristoteles; Favorisen Rosyking Lumbanraja
Jurnal Pepadun Vol. 4 No. 1 (2023): April
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v4i1.145

Abstract

The University of Lampung conducts routine activities of Introduction to New Student Campus Life (PKKMB) to introduce every building and public facility within the Faculty of Agriculture as well as every building and room inside. New Students and the general public every year. The current state of the COVID-19 pandemic has forced the University of Lampung to carry out learning activities online. Thus making every student activity impossible to do directly. So we need a method of presenting 3D visualization information. By using Multimedia Development Life Cycle (MDLC) system development method, the developed 3D virtual map application can display building layouts and facilities in 3D so that PKKMB activities related to the introduction of existing buildings and public facilities can still be delivered effectively and efficiently. This research was developed through 2 types of testing, namely testing by developers (Alpha) and customer satisfaction (Betha). Alpha testing provides test results. These Applications can operate on various Android with 7.1 to 12 of operating system and also on smartphone with 5.0 to 6.5 inches of screen. These applications can also be operated on smartphones with RAM range in 3GB to 8GB. Respondents stated that the 3D Virtual Map Application for Building K, Building H, Building I , and Building R, Faculty of Agriculture, University of Lampung, had good results with index percentages ranging from 87.5% to 95%.e basics.
Penerapan Metode Support Vector Machine (SVM) dalam Klasifikasi Penderita Diabetes Mellitus Fanni Lufiana; Favorisen Rosyking Lumbanraja; Yunda Heningtyas; Kurnia Muludi
Jurnal Pepadun Vol. 4 No. 1 (2023): April
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v4i1.150

Abstract

Diabetes Mellitus (DM) is a chronic disease characterized by the body's inability to metabolize carbohydrates, fats, and proteins, resulting in increased blood sugar (hyperglycemia) due to low insulin levels. Diabetes is due to a combination of heredity (genetics) and unhealthy lifestyles. Hemoglobin A1c is a blood test used to diagnose and manage diabetes patients when measuring blood sugar levels. This study aims to analyze predictive models for the classification of people with diabetes using R Shiny and evaluate the results of the support vector machine method's classification performance. There are many ways to diagnose diabetes, and the support vector machine is one of the machine learning algorithms used in this study's classification case (SVM). This study uses data from Diabetes 130-US Hospital For Years 1999-2008, which was sourced from the UCI Machine Learning Repository and consists of 34 variables and 84900 records, with dataset distribution and testing techniques using the 10-fold cross-validation method and three kernels in modeling using SVM, namely linear, Gaussian, and polynomial. The results obtained are a simple predictive model analysis system for classifying people with diabetes with shiny, making it easier for users to find out the prediction results and obtain the highest accuracy result, which is 82.76 percent of the gaussian kernel.
Co-Authors - Damayanti Adawiyah, Laila Admi Syarif Aflaha Asri Ahyarudin Akbar, Mohammed Raihan Akmal Junaidi Amelia Jasmine Andrian, Rico Annisa Rizqiana Ardiansyah Ardiansyah Aristoteles, Aristoteles Asmiati Asmiati Astria Hijriani Astria Hijriani Aulia Putri Ariqa Ayu Amalia Bambang Hermanto Damayanti Damayanti Danu Sasmita Desti Fatmalasari Destian ade anggi Sukma Dian Kurniasari Didik Kurniawan Dwi Kartini, Dwi Dwi Sakethi Dwi Sakethi, Dwi Eliza Fitri Elly Lestari Rusitati Erdi Suroso Fanni Lufiana Fanni Lufiana Farida Ariyani Febi Eka Febriansyah Fitriyana, Silfia Hadi, Normi Abdul Hamim Sudarsono . Hdiana, Yazid Zinedine Heningtyas, Yunda Ilman, Igit Sabda Indah Pasaribu Ira Hariati Br Sitepu Irawati, Anie Rose Jasmine, Amelia Jihan Aferiansyah Junaidi Junaidi Junaidi Junaidi Kristina Ademariana Kurnia Muludi Kurnia Muludi Kurnia Muludi Lilies Handayani M. Juandhika Rizky Machudor Yusman Manurung, Yunita Rosalina Megawaty, Dyah Ayu Meria Nensi Muhammad Reza Faisal, Muhammad Reza Muhammad Rizki Muhaqiqin, Muhaqiqin Muliadi Mustofa Usman Nadila Rizqi Muttaqina Naurah Nazhifah Nirwana Hendrastuty Nova Ayu Lestari Siahaan Nugroho Susanto, Gregorius Nuning Nurcahyani Nurdin, Muhaymi Nurhasanah Nurhasanah Parabi, M. Iqbal Parjito , Parjito Prabowo, Rizky Pratama, Rinaldo Adi Priyambodo Priyambodo Priyambodo Priyambodo Qory Aprilarita Rahmat Safe'i Rangga Agustiantino Reza Aji Saputra RM Sulaiman Sani Rosdiana, Siti Rudy Herteno Rudy Herteno Rusitati, Elly Lestari Saragih, Triando Hamonangan Shofiana, Dewi Asiah Sholehurrohman, Ridho Sintiya Paramitha Siti Aisyah Solechah Siti Rosdiana Su'admaji, Arif Susanto, Gregorius Nugroho Sutyarso Sutyarso Sutyarso, - Syangap Diningrat Sitompul TANJUNG, AKBAR RISMAWAN Tiyara Saghira Tristiyanto Tristiyanto Wamiliana Wamiliana Wamiliana Warsono Warsono Warsono Warsono Warsono YOHANA TRI UTAMI, YOHANA TRI Zaenal Abidin Zuliana Nurfadlilah