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All Journal Jurnal Informatika dan Teknologi Komputer ( J-ICOM)
Vika Vitaloka Pramansah
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Sistem Informasi Pengingat Jadwal Imunisasi Pada Anak Usia Dini Menggunakan Metode Scrum Berbasis Android Di Bidan Hana Suroyyah, Am.Keb Vika Vitaloka Pramansah
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 3 No 1 (2022): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : E-Jurnal Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/j-icom.v3i1.4948

Abstract

Immunization is an effort by the Indonesian government to achieve the Millennium Development Goals (MDGs) which are the focus of reducing the volume of child mortality. The mortality index in children under five is the main parameter to determine the health status of the community, especially children under five. For this reason, the health service program in Indonesia focuses on reducing infant mortality through immunization. However, sometimes parents forget the schedule for the implementation of immunization in the following month so that it is very detrimental to parents, especially the health of toddlers. This study aims to build an information system on the application as a reminder of the immunization schedule for the midwife Hana Suroyyah, Android-based Am.Keb. This research was conducted by going through several stages, namely identifying existing problems, literature study with previous journals, collecting the required data, and developing an immunization schedule reminder information system with SMS Gateway using the scrum method. The information generated in this application is an Immunization Schedule which is equipped with a notification as a reminder of the Immunization schedule before D-1 using an SMS Gateway.
Analisis Perbandingan Algoritma SVM Dan KNN Untuk Klasifikasi Anime Bergenre Drama Vika Vitaloka Pramansah
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 3 No 1 (2022): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : E-Jurnal Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/j-icom.v3i1.4950

Abstract

There are many genres of anime such as drama, action, romance, comedy, and so on. However, because there are so many anime genres, it is quite difficult for viewers to find anime whose genre they like, such as the drama genre which tells about everyday human life which is quite light in nature. From these problems, a classification method is needed to classify anime that belongs to the drama genre. Classification is a common method in data mining, an object whose class/label is unknown can go through the classification method so that its class can be estimated [7]. Classification has several algorithms including Support Vector Machine (SVM) and K-Nearest Neighbors (KNN). SVM and KNN algorithms have been widely used and have a good level of accuracy. In this study, a comparative analysis will be carried out between the two algorithms, the dataset used is 12,294 data and 2 genre classes, namely drama and non-drama, the attribute of the anime dataset is 7. The results obtained in this study indicate that the K-Nearest Neighbors Algorithm (KNN) ) get a training accuracy value of 100% and a test accuracy value of 84%. And also the Support Vector Machine (SVM) algorithm gets a training accuracy value of 83% and a test accuracy value of 82%. The results of the accuracy values ​​of the two algorithms indicate that the K-Nearest Neighbors (KNN) algorithm has a better testing accuracy than the Support Vector Machine (SVM) with a fairly thin difference between the two algorithms.
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