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INDONESIA
JOURNAL OF APPLIED INFORMATICS AND COMPUTING
Published by Politeknik Negeri Batam
ISSN : -     EISSN : 25486861     DOI : 10.3087
Core Subject : Science,
Computer Science & IT
Journal of Applied Informatics and Computing (JAIC) Volume 2, Nomor 1, Juli 2018. Berisi tulisan yang diangkat dari hasil penelitian di bidang Teknologi Informatika dan Komputer Terapan dengan e-ISSN: 2548-9828. Terdapat 3 artikel yang telah ditelaah secara substansial oleh tim editorial dan reviewer.
Arjuna Subject : -
Articles 695 Documents
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Perbandingan Algoritma K-Means dan K-Medoids Untuk Pengelompokkan Data Obat dengan Silhouette Coefficient di Puskesmas Karangsambung Riva Arsyad Farissa; Rini Mayasari; Yuyun Umaidah
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i1.3237

Abstract

Puskesmas merupakan unit pelaksana fungsional yang berperan sebagai pusat pembangunan kesehatan, pusat partisipasi masyarakat bidang kesehatan dan pusat pelayanan kesehatan primer. Masalah yang dialami puskesmas ini adalah perecanaan kebutuhan obat yang tidak efektif dan efisien. Penggunaan data mining ini dapat mengendalikan stok obat agar tidak terjadi penumpukan stok serta kehabisan stok obat. Clustering adalah teknik pengelompokan record dalam database berdasarkan kondisi tertentu. Metode yang akan digunakan untuk clustering data obat-obatan adalah algoritma K-Means dan K-Medoids yang merupakan metode clustering non hirarki yang mempartisi data ke dalam cluster sehingga data yang memiliki karakteristik yang sama akan dikelompokkan ke dalam cluster yang sama. Tujuan dari penelitian ini adalah untuk mengelompokkan data obat-obatan di Puskesmas Karangsambung yang dapat digunakan sebagai referensi untuk perencanaan obat yang akan datang di puskesmas tersebut. Pengelompokkan data dibagi menjadi tiga yaitu lambat, sedang dan cepat. Hasil yang didapatkan yaitu kedua algoritma tersebut menunjukan bahwa algoritma K-Means mendapatkan hasil Silhouette Coefficient lebih tinggi yaitu sebesar 0,627 sedangkan K-Medoids sebesar 0,536.
Klasifikasi K-NN dalam Identifikasi Penyakit COVID-19 Menggunakan Ekstraksi Fitur GLCM Nisa Nafisah; Riza Ibnu Adam; Carudin Carudin
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3258

Abstract

Covid-19 is a disease that is endemic in various parts of the world including Indonesia, this disease infects the respiratory tract caused by a new type of corona virus. To find out the presence of this virus in the body, medical examinations such as blood tests, radiological examinations can be carried out X-rays (x-rays) and swabs. Therefore, in this study, identification covid-19 disease based on the rongen image from which the image was extracted using the GLCM feature extraction method, namely contrast, correlation, energy, and homogeneity, after obtaining the value from the extraction and then classified using data mining classification method, namely k-nearest neighbor by doing 3 modeling the input value of k. The results obtained from the classification obtained an accuracy of 80% in model 3 with a value of k = 5 and in models 1 and 2 obtained an accuracy of 90% with a value of k = 1 and k = 3.
Klasifikasi Kinerja Asisten Laboratorium Selama Pandemi Covid-19 Menggunakan Algoritma Naive Bayes Rahmayadi, Andhika Putra Utama; Enri, Ultach; Purwantoro, Purwantoro
Journal of Applied Informatics and Computing Vol. 5 No. 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3261

Abstract

Asisten laboratorium merupakan mahasiswa berprestrasi pilihan yang memiliki tugas untuk mendampingi dosen dalam proses mengajar mata kuliah praktikum. Karena wabah covid-19 di Indonesia sesuai dengan surat edaran yang dikeluarkan oleh menteri pendidikan tentang pelaksanaan belajar secara daring, hal ini menyebabkan proses praktikum beralih menjadi daring. Selama praktikum daring asisten laboratorium kesulitan untuk memonitor mahasiswa dalam proses pengajaran, maka diperlukan sebuah evaluasi apakah metode yang dibawakan oleh asisten laboratorium sudah tepat. Proses evaluasi ini dilakukan dengan menggunakan data mining dan algoritma Naive Bayes. Model yang dihasilkan dapat memprediksi label puas dan tidak puas dengan evaluasi model k-fold cross validasi dan confusion matrix yang menghasilkan akurasi sebesar 87%, recall sebesar 96%, dan presisi sebesar 88%.
Komparasi Algoritma K-Means dan K-Medoids Untuk Pengelompokkan Penyebaran Covid-19 di Indonesia Anisa Fira; Chaerur Rozikin; Garno Garno
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3286

Abstract

COVID-19 merupakan bagian dari keluarga virus penyebab Severe Acute Respiratory Syndrome (SARS) dan Middle East Respiratory Syndrome (MERS), beberapa gejala yang dialami apabila terinfeksi virus ini antara lain batuk, demam, letih, sesak nafas, dan mengalami penurunan nafsu makan. Pada Penelitian ini data yang digunakan tahun 2019 - Februari 2021 yang bersumber pada website resmi www.covid19.go.id. Dalam upaya menemukan daerah yang memiliki kasus penyakit Covid-19 dapat menggunakan Data Mining. Negara indonesia merupakan salah satu dari negara di dunia yang cukup tinggi terkena virus covid-19. Tujuan penelitian ini yaitu untuk mengelompokan provinsi yang memiliki penyakit covid-19 dengan tingkat tinggi dan rendah di indonesia dan melakukan perbandingan dengan metode algoritma yang digunakan yaitu K-Means dan K-Medoids. hasil yang didapatkan pada penelitian ini adalah memiliki cluster optimal sebanyak 2 cluster, dengan menggunakan algoritma K-Means dimana cluster 1 beranggotakan 2 wilayah dan dikategorikan tinggi, sedangkan untuk cluster 2 sebanyak 32 wilayah dan dikategorikan rendah. Sedangkan menggunakan algoritma K-Medoids yaitu untuk cluster 1 beranggotakan 4 wilayah dan dikategorikan tinggi, sedangkan untuk cluster 2 sebanyak 30 wilayah dan dikategorikan rendah. Dari kedua perbandingan tersebut menghasilkan nilai Silhouette Coefficient dengan metode K-Means adalah sebesar 0,207. Sedangkan Nilai Silhouette Coefficient dengan metode K-Medoids adalah sebesar 0,347.
Evaluasi Usability Website Shopee Menggunakan System Usability Scale (SUS) Firman Galuh Sembodo; Gita Fadila Fitriana; Novian Adi Prasetyo
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3293

Abstract

The progress of information technology is currently growing rapidly. Technology related to the internet is often a solution to most of the problems in existing needs, especially those related to the effectiveness and efficiency of activities and procedures. In this final project, the author discusses websites in the business field, namely e-commerce websites. In this study, the authors chose one of the most popular e-commerce websites in Indonesia this year, namely the shopee website, a website that not only offers products but also puts forward the appearance of the Shopee website which must always be considered because it is the main factor to increase customer purchases. In this study, the quality of the web that will be measured by users, especially for consumers, is based on measuring the quality of the website using the System Usability Scale (SUS). Evaluation of the shopee website is the first step to measure the level of usability on the website. Usability evaluation on the website is carried out to collect opinions from various respondents regarding the functionality of the website. In this study, the results obtained from the calculation of the average usability of the shopee website of 67.08 so that it can be said that the usability of the shopee website on product purchases has entered the OK category.
Deteksi Microaneurysm Pada Mata Sebagai Langkah Awal Untuk Penentuan Diabetic Retinophaty Menggunakan Pengolahan Citra Digital Anisa Habsari; Tri Harsono; Heny Yuniarti; Rita Tjandra
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3302

Abstract

Diabetic Retinopathy is a microvascular complication of diabetes mellitus. According to WHO (World Health Organization), there are more than 347 billion people who suffer from diabetes. This disease will become the seventh leading cause of death in the world in 2030. Based on research in Indonesia, it is estimated that there are 42.6% of diabetic retinopathy. Therefore, this final project plans a system to assist doctors in identifying diabetic retinopathy through its characteristics, namely microaneurysm. This system begins with an input retinal image from the fundus camera. Then the input will be processed in preprocessing to increase the contrast using the green channel. The next stage is segmentation. This is used to detect candidates from blood vessels and microaneurysms that use morphology operations. The next step is feature extraction, where it uses the features of glcm and white pixels detected in the image resulting from segmentation. The value of the white pixels and the values in the glcm feature are used as parameters in determining whether the classification process will be used as a determination of a Diabetic Retinopathy image or not. The success rate of the system using the SVM (Support Vector Machine) method is 88.4%.
Penerapan Metode SUMI Pada Pengujian Usability Aplikasi E-Learning Berbasis Website Puja Hanifah; Machrija Wahyuni Siregar
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3349

Abstract

Pandemi COVID19 telah mengubah gaya hidup semua orang. Untuk menekan penyebaran dilakukan lockdown atau ppkm yang berpengaruh terhadap aktivitas masyarakat, salah satu sektor yang terkena dampak adalah dunia Pendidikan. Aktivitas belajar mengajar dilakukan secara daring (online) dengan bantuan E-Learning. Salah satunya ada SMAIT Al-Fityan School Medan melakukan proses belajar mengajar menggunakan e-learning. Untuk mengetahui kualitas dari penggunaan perangkat lunak dapat menggunakan salah satu metode adalah SUMI, yang mengukur kualitas penggunaan perangkat lunak berdasarkan perasaan pengguna saat menggunakan perangkat lunak. Dari hasi pengujian didapatkan bahwa sangat efisien dan dapat membantu proses belajar mengajar antar guru dan siswa. Hal ini diperoleh dari nilai skala efficiency dan helpfulness.
Klasifikasi Nilai Kepuasan Masyarakat Terhadap Pelayanan E-KTP Menggunakan Algoritma C4.5 (Studi Kasus : Kantor Kecamatan Rengasdengklok ) Amelia Pratiwi; Aries Suharso; Hannie Hannie
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3264

Abstract

The e-KTP service is very important for the community as an identification or identity card for Indonesian citizens. So it is necessary to do this research to find out the value of community satisfaction with e-KTP services, so that later it becomes a reference for e-KTP operators to be even better. Data on the value of community satisfaction At the Rengasdengklok District office, there is a lot of data. This study aims to classify the value of community satisfaction with e-KTP services using. The method used is KDD (Knowledge Discovery in Database) classification by going through the process of data selection, preprocessing, transformation, data mining and evaluation. The algorithm used in this study is the C4.5 algorithm, which is the result of the classification process in the form of rules that can be used to predict the value of the discrete type attribute of a new record. In evaluating the performance of the C4.5 algorithm in the classification of the value of community satisfaction with e-KTP services using Rapidminer tools. Evaluation of the model using kappa. Then it was obtained that the accuracy value was 94.67%. With a kappa value of 0.914% that has been obtained, it falls into the range of values ​​from 0.81 to 1.00, the results of this study have a value of the level of satisfaction with the e-KTP service in the very strong classification category.
Klasifikasi Kadar Kolesterol Menggunakan Ekstraksi Ciri Moment Invariant dan Algoritma K-Nearest Neighbor (KNN) Sekar Arum Nurhusni; Riza Ibnu Adam; Carudin Carudin
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3273

Abstract

Cholesterol is a fat that is mostly formed by the body itself, especially in the liver. Cholesterol is very useful for the body but will be very dangerous if it has excessive levels. The impact of excessive cholesterol is the emergence of deadly diseases such as heart disease, stroke and poor blood circulation. In this study, one of the medical sciences that can be used to detect cholesterol levels is Iridology. This iridology itself can be applied in computer science which is often referred to as Digital Image Processing. In this case, the feature recognition method will be used using Moment Invariant feature extraction and the K-Nearest Neighbor Algorithm. Where the data used is the Dataset from Ubiris V1. With the resulting accuracy of 84,8485%.
Penerapan Metode TOPSIS sebagai Rekomendasi Pemilihan Wisata (Studi Kasus: Kabupaten Cilacap) Tri Mega Anggraeni; Gita Fadila Fitriana; Cepi Ramdani
Journal of Applied Informatics and Computing Vol 5 No 2 (2021): December 2021
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v5i2.3280

Abstract

Indonesian people have made vacation activities a primary need so that vacations are not just travelling. Now people are starting to travel longer, farther, and more often. When making tourist visits, domestic tourists are faced with many choices of destinations in the city. Cilacap City is one of the cities with many tourist attractions, in this city requires the selection of tourist objects according to the interests and interests of each tourist. So, it takes a recommendation system for the user to achieve the goal. The user can choose the desired tourist destination more effectively. The application of tourist recommendations in Cilacap City aims to overcome the problems that occur to tourists. This application uses a Decision Support System using the TOPSIS method with the development of the Agile methodology. The result implementingon of the topstopicshod in Cilacap City are the recommendation for Mount Srandil tourism by 78%, Momongan Island by 77%, Soesilo Soedarman Museum by 74%, Karang Bolong Fort by 71% and Widarapayung Beach by 63%. So, the recommended result is Srandil Mountain tourism. This application also tests the function software's functionality Blackbox method with 100% results, where users, namely tourists, can understand the application's functionality.

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