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All Journal Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Jurnal Informatika dan Rekayasa Perangkat Lunak
Diana Dwi Aulia
Universitas darwan ali
Computer Science & IT Education Engineering

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Perancangan Prototype Tampilan Antarmuka Berbasis Web Mobile Pada Toko Amira Kosmetik Diana Dwi Aulia; Siti Aminah; Deny Sundari
Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Vol 5, No 1 (2022): Januari
Publisher : Akademi Ilmu Komputer Ternate

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47324/ilkominfo.v5i1.134

Abstract

Abstrak: Dalam penelitian ini merupakan perancangan Prototype sebagai desain suatu sistem jual beli berbasis Web Mobile pada Toko Amira, dimana penilitian ini dilakukan pada Toko Penjualan Kosmetik yang ada di kota Sampit. Metode dalam Pengumpulan data yang dilakukan adalah wawancara dan observasi pada toko serta melakukan Analisa desain system agar mudah digunakan bagi pengguna. Desain ini dibangun menggunakan Figma yang mana aplikasi didesain khusus untuk desain prototype. Dengan adanya desain antarmuka yang sudah dibuat diharap memudahkan programmer dalam pengembangan sistem yang akan dibangun nantinya, dan tujuan lainnya adalah untuk memberikan kemudahan kepada pengguna dengan tampilan yang userfriendly. Adapun hasil dari penelitian ini berupa desain tampilan  berbasis web mobile pada toko amira kosmetikKata kunci: Perancangan Sistem Antarmuka, Penjualan Online, Web MobileAbstract: This research is a prototype design as the design of a mobile Web-based buying and selling system at the Amira Store, where this research was carried out at the Cosmetic Sales Store in Sampit. Methods in collecting data are interviews and observations at the store and analyzing the system design so that it is easy to use for users. This design was built using Figma, where the application was designed specifically for prototype design. With the interface design that has been made, it is hoped that it will make it easier for programmers to develop the system built later. Another goal is to provide convenience to users with a user-friendly appearance. The results of this study are in the form of a mobile web-based display design at the Amira Cosmetics shop.Keywords: Interface System Design, Online Sales, Web Mobile
ALGORITMA K-MEANS UNTUK MELIHAT PENULARAN TERTINGGI VIRUS COVID-19 DISELURUH PROVINSI INDONESIA Nurahman Nurahman; Diana Dwi Aulia
JURNAL ILMIAH BETRIK : Besemah Teknologi Informasi dan Komputer Vol 12 No 2 (2021): JURNAL ILMIAH BETRIK : Besemah Teknologi Informasi dan Komputer
Publisher : LPPM Sekolah Tinggi Teknologi Pagar Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36050/betrik.v12i2.331

Abstract

Abstract: The Corona virus or Covid-19 disease began to occur in 2019 until now in 2021. Where the cause of this infectious disease is the Corona Virus. One of the symptoms caused by this viral infection is respiratory problems. The virus in the spread or transmission is classified as very fast. This makes every country, especially Indonesia, where every region has been exposed to Covid-19, which has caused many cases of death, and several impacts, such as the impact on the economy, work, education, and other impacts. With the large spread of the Corona virus in regions or regions in Indonesia, it is necessary to group several parts of Indonesia. Therefore, to make it easier to group a region in Indonesia, in this study a data mining system was used to process large amounts of data by implementing the Clustering Algorithm using the K-Means method. The datasets obtained by researchers without class labels will be processed with the K-Means Algorithm to facilitate data processing to produce the desired goals. The purpose of this research is to see which province has the highest transmission of Covid-19 in Indonesia.
Klasterisasi Pendidikan Masyarakat Untuk Mengetahui Daerah Dengan Pendidikan Terendah Menggunakan Algoritma K-Means Nurahman Nurahman; Diana Dwi Aulia
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 5, No 1 (2023): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v5i1.7510

Abstract

Education is a basic need for every human being who plays an important role in the future of the nation, because a nation that is said to be advanced can be seen from its good learning system. Successful education is measured by the average number of graduates at various levels of education in various regions. But not all regions are good in the quality of education. One of them is the area in Indonesia, such as the Kapuas district, Central Kalimantan. It is known that in previous years this area lacked improvement in education, causing several areas where people did not go to school or dropped out of school. Many of the problems are caused by economic factors, laziness, lack of motivation about the importance of education, and so on. The previous Covid-19 pandemic was also the reason for the increase in the number of children dropping out of school due to a declining family economy. The number of areas in Kapuas district requires grouping the number of existing villages. The grouping aims to make it easier for the government to pay special attention to areas where education is considered lacking and other purposes are to find out which villages have low levels of education. In grouping, the system applied is data mining using the K-Means Algorithm Clustering method which is processed using rapidminer software. The groupings formed on the education level data of 229 records are 8 clusters where the lowest education villages are stated in (C1) with a total of 33 villages.
Comparison Performance of K-Medoids and K-Means Algorithms In Clustering Community Education Levels Diana Dwi Aulia; Nurahman Nurahman
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 12 No. 2 (2023)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v12i2.59789

Abstract

Education is a mandatory right of all citizens and the key to the nation's superiority in global competition that must get top priority to be examined critically and comprehensively. It is known that compulsory education is at least 12 years, but not all people can do it because of minimal economic conditions. In past years, COVID-19 has also had an impact on the economy, school dropout rates, and falling academic achievement, for example in Central Kalimantan. The size of Central Kalimantan, however, makes it difficult for the government to identify the areas with the worst levels of education. To determine which regions fall into the low and high education categories, it is required to group the province's educational levels. This study also compares two algorithms by measuring their accuracy. By looking at which algorithm has the lowest Davies Bouldin Index (DBI) value, the best degree of performance can be ascertained. To process the data from as many as 1,565 sources, data mining techniques, including the clustering method, were used. K-Means and K-Medoids algorithms were employed in this work as clustering techniques. Based on the outcomes of the cluster created, both algorithms are also put to the test for performance. The results of this study obtained 6 clusters in K-Means with the lowest DBI value of -0.439, while the results in K-Medoids were in 3 clusters with the lowest DBI of -0.866. Based on accuracy testing using DBI, it is known that K-Means results are more optimal with the lowest DBI value in the grouping of education levels compared to K-Medoids. It is also known from the formation of 6 clusters of the K-Means algorithm that the low education level is in cluster_0 which is 1484 villages and the higher education level is as many as 3 villages in cluster_3.
Co-Authors Deny Sundari Nurahman Siti Aminah