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E-Voting Optimization For Head Of Community Unit (RW) Election with WAPT Testing Samudi, Samudi; Brawijaya, Herlambang; Widodo, Slamet
Sinkron : Jurnal dan Penelitian Teknik Informatika Vol 3 No 2 (2019): SinkrOn Volume 3 Number 2, April 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (424.581 KB) | DOI: 10.33395/sinkron.v3i2.10057

Abstract

This conventional election has several weaknesses, including difficulties in determining the validity of ballots, the process of counting ballots is slow. From the above problems, the authors propose to design and build a system to carry out elections using information technology called Electronic Voting. The method in this study uses the waterfall method which consists of the stages of needs Communication, Planning, Modeling, Construction, dan Deployment. The results of this study are to produce elections held with the District E-Voting.
SISTEM INFORMASI GUNA MENINGKATKAN PENJUALAN REPTIL BERBASIS WEB PADA TOKO 68 REPTILES SURABAYA Brawijaya, Herlambang
Jurnal Sistem Informasi Vol 4 No 1 (2015)
Publisher : STMIK ANTAR BANGSA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (360.742 KB)

Abstract

Abstract— Trade in this era of internet technology or better known by the term e-commerce (electronic commerce) lately has been rife with the emergence of thousands of companies offering goods kept in the website. These companies seemed to be racing to peddle goods, wares on the internet due to market opportunities. Intense competition is certainly making its businessmen vying for various facilities and provides ease to invite consumers to enter their website in order to buy the last course. The facilities offered are of course easy for consumers to explore data on goods and means of the transaction. The purpose of this research is conducted to identify the problems that exist in the system of sale of reptiles manually at 68 Reptiles Surabaya. Methods used in collecting data and information for supporting information systems this is to do the analysis in a shop, 68 reptiles direct observation an interview with the owner and study of literature in collecting data. The results of research done and the process of making the web, then the authors conclude by designing an information system web-based reptiles sales can reduce the constraints faced by the admin in the process of animal data, as well as make it easier for consumers and consumers in obtaining information regarding the sale of reptiles.Intisari— Perdagangan di era teknologi internet atau yang lebih dikenal dengan istilah e-commerce (electronic commerce) akhir-akhir ini telah marak dengan munculnya ribuan perusahaan yang menawarkan barang dagangannya di dalam website. Perusahaan-perusahaan ini seakan-akan berlomba untuk menjajakan barang dagangannya di internet karena adanya peluang pasar. Persaingan yang ketat tentunya membuat para pelaku usaha berlomba-lomba untuk menyediakan berbagai fasilitas dan kemudahan untuk mengundang konsumen memasuki websitenya dengan tujuan terakhir agar membeli tentunya. Fasilitas yang ditawarkan tentunya adalah kemudahan bagi konsumen untuk menyusuri data-data barang dan cara pemesanannya. Tujuan penelitian ini dilakukan adalah untuk mengidentifikasi masalah-masalah yang ada pada sistem penjualan hewan reptil secara manual pada toko 68 Reptiles Surabaya. Metode yang digunakan dalam pengumpulan data dan informasi untuk mendukung sistem informasi ini adalah dengan melakukan analisa pada Toko 68 Reptiles, observasi secara langsung, wawancara dengan pemilik dan studi pustaka dalam pengumpulan dataDari hasil riset yang dilakukan dan proses pembuatan web, maka penulis menyimpulkan dengan merancang suatu sistem informasi penjualan hewan reptil berbasis web dapat mengurangi kendala-kendala yang dihadapi admin dalam mengolah data-data hewan dan konsumen, serta memudahkan konsumen dalam memperoleh informasi mengenai penjualan hewan reptil.Kata Kunci: Sistem Informasi, Penjualan Reptil, Web 
The K-Medoids Clustering Method for Learning Applications during the COVID-19 Pandemic Samudi, Samudi; Widodo, Slamet; Brawijaya, Herlambang
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 1 (2020): Article Research, October 2020
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v5i1.10649

Abstract

A disease that is currently widespread today is caused by the spread of the coronavirus disease or what is commonly called COVID 19. This virus is very dangerous to health because it attacks organs in the human body from various sources, either from the air or direct touch. With the existence of COVID 19, it has an impact on all countries, especially the State of Indonesia, which consists of various islands, which are also affected by the COVID 19 virus. So that the central government takes a policy to carry out social distancing to every one to break the chain of spreading this virus, with this social distancing it has an impact on all activities that occur every day. As an impact on the learning process that usually takes place in class, it turns into online learning that uses several supporting applications in the learning process during the COVID 19 pandemic. With online learning from various applications, it attracts researchers to research with the K-Medoid Clustering Algorithm in using applications during the pandemic COVID 19.
Clustering Kanker Serviks Berdasarkan Perbandingan Euclidean dan Manhattan Menggunakan Metode K-Means Widodo, Slamet; Brawijaya, Herlambang; Samudi, Samudi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 2 (2021): April 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i2.2947

Abstract

K-means a fairly simple and commonly used cluster of clusters to partition datasets into multiple clusters. Distance calculations are used to find similar data objects that lead to developing powerful algorithms for datamining such as classification and grouping. Some studies apply k-means algorithms using distance calculations such as Euclidean, Manhattan and Minkowski. The study used datasets from gynecological patients with a total of 401 patients examined and as many as 205 patients detected cervical cancer, while 196 other patients did not have cervical cancer. The results were shown with the help of confusion matrix and ROC curve, accuracy value obtained by 79.30% with ROC 79.17% on K-Means Euclidean Metric while K-Means Manhattan Metric by 67.83% with ROC 65.94%. Thus it can be concluded that the Euclidean method is the best method to be applied in the K-Means Clustering algorithm on cervical cancer datasets.