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All Journal Jurnal Ilmiah Informatika Komputer InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Informatics for Educators and Professional : Journal of Informatics Information Management For Educators And Professionals (IMBI) KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer JURNAL MANAJEMEN INFORMATIKA (JUMIKA) Jurnal Teknologi Informasi dan Multimedia Jurnal Accounting Information System (AIMS) E-Link: Jurnal Teknik Elektro dan Informatika REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer AMMA : Jurnal Pengabdian Masyarakat Jurnal Informatika: Jurnal Pengembangan IT Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal)
Irfan Ali
STMIK IKMI Cirebon
Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Other

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Rancang Bangun Sistem Informasi Ticketing Berbasis Website pada STF Muhammadiyah Cirebon Deffan Febrian Dirmanthara; Ega Salsa Nugraha; Tio Prasetya; Irfan Ali; Kaslani
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 6 No. 4 (2022): Volume 6 No 4 Oktober 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v6i4.11780

Abstract

Sistem Informasi Helpdesk Ticketing dapat memastikan dan mengevaluasi kualitas terkait teknologi informasi. Saat melakukan kegiatan yang memanfaaatkan teknologi informasi, terdapat permasalahan yang muncul, seperti pada STF Muhammadiyah Cirebon. STF Muhammadiyah Cirebon adalah Sekolah Tinggi Farmasi yang beralamatkan di Jl. Cideng Indah No. 3 Kertawinangun Kedawung Kabupaten Cirebon. Dalam merancang sistem informasi ini, peneliti melakukan tahap observasi dan wawancara terlebih dahulu. Peneliti merancang sistem informasi ticketing berbasis web menggunakan Software Development Life Cycle (SDLC) dengan metode waterfall agar sistem yang dirancang dapat digunakan oleh staff bagian IT dalam memecahkan masalah dengan cepat dan dapat menyimpan informasi  dari setiap masalah dalam pengaduan yang diterima, sehingga dapat meminimalkan kesalahan komunikasi.
Klasifikasi Status Stunting Balita Di Desa Slangit Menggunakan Metode K-Nearest Neighbor Irfan Ali; Dian Ade Kurnia; Muhammad Aji Pratama; Farids Al Ma’ruf
KOPERTIP : Jurnal Ilmiah Manajemen Informatika dan Komputer Vol. 5 No. 3 (2021): KOPERTIP : Jurnal Ilmiah Manajemen Informatika dan Komputer
Publisher : Puslitbang Kopertip Indonesia

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Abstract

Stunting pada balita merupakan salah satu permasalahan yang sedang dialami dunia kesehatan. Kejadian ini ditandai dengan berat badan dan tinggi badan yang tidak sesuai dengan umur. Selain itu juga dipengaruhi oleh pola konsumsi makanan dan penggunaan nutrisi yang tidak disesuaikan dengan kebutuhan tubuh. Dalam mencegah kejadian Stunting kegiatan yang rutin dilakukan adalah dengan memantau perkembangan status gizi dan status tumbuh kembang balita yang dilakukan melalui kegiatan posyandu yang berlangsung pada setiap bulan. Penelitian ini menggunakan pendekatan data mining dengan algoritma K-Nearest Neighbor yaitu menggunakan perhitungan jarak euclidean, adalah sebuah metode untuk mengelompokan atau mengklasifikasikan sebuah data dari uji kelas latih pada beberapa tetangga paing dekat dengan menggunakan rumus perhitungan jarak euclidean. parameter yang dipakai pada penelitian ini didasarkan pada data antropometrik atau data pengukuran tubuh manusia, yaitu Umur, Berat Badan dan Tinggi Badan. Pengujian dilakukan dengan perhitungan manual kemudian dibuat perankingan serta implementasikan kedalam aplikasi RapidMiner.
Transformasi Strategi Penjualan Batik Cirebon Dengan Pendekatan Analisis Pengelompokan K-Means Mulyawan .; Agus Bahtiar; Irfan Ali
KOPERTIP : Scientific Journal of Informatics Management and Computer Vol. 7 No. 1 (2023): KOPERTIP : Jurnal Ilmiah Manajemen Informatika dan Komputer
Publisher : Puslitbang Kopertip Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32485/kopertip.v7i1.309

Abstract

Batik adalah seni tradisional Indonesia yang mengombinasikan seni dan teknologi untuk menciptakan kain yang indah dan unik. Batik Indonesia memiliki desain dan proses yang tak tertandingi, dan ragam coraknya mengandung makna dan filosofi dari berbagai adat dan budaya di Indonesia. Batik Cirebon memiliki banyak motif batik seperti Mega Mendung, Singa Barong, dan Paksinaga Liman. Untuk mengoptimalkan penjualan, diperlukan teknik data mining untuk mengubah data menjadi informasi baru. Metode K-Means adalah cara yang tepat untuk mengelompokkan data penjualan produk batik karena dapat mengolah data tanpa mengetahui kelas label. Tujuan dari penelitian ini adalah untuk menerapkan algoritma K-Means dalam pengelompokan data penjualan dan menemukan hasil KOptimum dengan menggunakan aplikasi Orange. Hasil dari penelitian menunjukkan bahwa terdapat enam kelompok yang sesuai dengan data penjualan batik dan hasil kluster yang optimal terdapat pada k=6.
PENERAPAN METODE K-MEANS CLUSTERING PADA PENJUALAN BARANG DI SPORTS STATION Nadia Putri Gantara; Irfan Ali
E-Link: Jurnal Teknik Elektro dan Informatika Vol 18 No 1 (2023): Mei 2023
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/e-link.v18i1.5339

Abstract

Penjualan adalah kegiatan menjual barang dan jasa, apabila manajemen penjualan pada perusahaan kurang baik maka akan mempengaruhi keuntungan. Sehingga, membuat perusahaan tidak mencapai tujuannya. Jenis usaha yang ada di indonesia sangat beragam, salah satunya Sports Station merupakan perusahaan retail yang menjual perlengkapan olahraga. Sports Station sering mengalami permasalahan dengan ketidakakuratan dan tidak terstrukturnya data penjualan. Sehingga, berdampak dalam kesulitan mengelompokkan produk. Maka, diperlukan sistem yang dapat menentukan pola atau trend dalam penjualan. Algoritma K-Means digunakan untuk mengelompokkan produk berdasarkan pola penjualan yang serupa, yaitu dengan membagi data menjadi dua klaster yang dikategorikan sebagai laris dan kurang laris. Tahapan yang diterapkan yaitu retrieve, untuk mengambil dataset, kemudian menggunakan K-Means Clustering untuk memodelkan dataset dan Cluster distance performance untuk mengevaluasi hasil pengelompokan. Validasi hasil klasterisasi dapat dilakukan menggunakan Davies Bouldin Index (DBI). Algoritma ini menghasilkan pengelompokkan menjadi 2 yaitu cluster 0 dengan nilai 995 sebanyak 121 produk dengan kategori laris dan cluster 1 dengan nilai 327 sebanyak 2.279 produk dengan kategori kurang laris. Serta hasil DBI yang paling mendekati 0 adalah K 2 menghasilkan nilai 0,10.
Pelatihan Aplikasi E-Commerce Desa Cisantana Kuningan Guna Meningkatkan Potensi Ekonomi Arif Rinaldi Dikananda; Nining Rahaningsih; Irfan Ali
AMMA : Jurnal Pengabdian Masyarakat Vol. 2 No. 8 : September (2023): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Cisantana Kuningan Village, in carrying out its entrepreneurship, has used the internet, but the use of this technology has not been optimal. The problem faced by partners is that the use of information technology is still not optimal as a promotional medium for their entrepreneurial products. Partners' limited knowledge and ability to use internet media and e-commerce media is limited to using the WhatsApp application. The solution offered by the PM team is to solve the problems faced by partners by holding training on the use of e-commerce media literacy technology as a product promotion medium. The PM implementation method consists of field surveys, permits, problem analysis, problem solutions, implementation, evaluation and reporting. The output results that will be achieved in this activity are increasing the ability of partners in utilizing information technology and the ability of partners in creating promotional media.
Pemberdayaan UMKM Desa Babakan Mulya Kuningan Melalui Pelatihan Pemanfaatan Teknologi Informasi Irfan Ali; Nining Rahaningsih; Iin
AMMA : Jurnal Pengabdian Masyarakat Vol. 1 No. 09 (2022): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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Abstract

Babakan Mulya Village in Kuningan Regency is a location that has significant economic potential in the Micro, Small and Medium Enterprises MSME sector. However, this potential has not been fully exploited due to the challenges faced by MSMEs in adopting Information Technology (IT) as a tool to develop their business. Therefore, IT utilization training for MSMEs in Babakan Mulya Village is an important initiative to increase the competitiveness of the local economy. Babakan Mulya Village is located in Kuningan Regency, West Java, Indonesia. This village has a number of MSMEs covering various sectors, such as agriculture, crafts and traditional culinary delights. However, most of these MSMEs face obstacles in adopting. Cases that often occur are the inability to utilize online platforms to market their products, lack of understanding of the importance of IT in business management, and limited access to digital technology. The results of MSME empowerment activities in Babakan Mulya Village, Kuningan through training in the use of information technology, it can be concluded that the implementation Information technology has had a real positive impact on MSMEs and communities in the village. First, the adoption of information technology has increased the operational efficiency of MSMEs. Production processes and inventory management become more structured and efficient, allowing them to meet market demand in a more timely and quality manner. Second, the use of information technology expands market reach. With the ability to market products online, Babakan Mulya Village MSMEs can reach customers in various regions, even at the national level. This opens up new opportunities for business growth and increased revenue.
Prediksi Tingkat Kelulusan Mahasiswa Menggunakan Machine Learning dengan Teknik Deep Learning Martanto Martanto; Irfan Ali; Mulyawan Mulyawan
Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 2-2 (2019): Special Issue on Seminar Nasional - Inovasi Dalam Teknologi Informasi & Teknol
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v4i2-2.1877

Abstract

The graduation rate of students on time at the Informatics Engineering study program STMIK IKMI Cirebon greatly affects the accreditation assessment. Graduation prediction is difficult to do, but many have done predictions using a variety of methods. Graduation prediction is needed in order to determine preventive policies for students who graduate not on time. The method used in this research is Machine learning with deep learning techniques. The data set used as many as 405 data of students who graduated on time or who were not on time. The research attributes used are the Nim attribute, the GPA value of students who have graduated and the status of graduating or not graduating. The results of this study are the level of accuracy using Machine Learning by 72.84%.
Aplikasi Pemesanan Online Barbershop Berbasis Android untuk Meningkatkan Layanan Cep Lukman Rohmat; Irfan Ali; Mulyawan Mulyawan; Tati Suprapti; Utami Aryanti
Jurnal Accounting Information System (AIMS) Vol. 4 No. 2 (2021)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/aims.v4i2.237

Abstract

The development of information and technology is a development that can be felt in everyday life, almost all activities already use digital. The problem in the barbershop business is the length of the queue which causes customers to feel bored or there are also busy customers. Therefore, technology is needed in the barbershop business. Based on these problems, it can be concluded that there is a need to build an android-based ordering application. The purpose of this research is to increase productivity, creativity, revenue and customer satisfaction. This study uses the stages of the Waterfall method. The Waterfall method is used as a reference in the process of making the online ordering application. The results of this study are an android-based online ordering application, this application is enough to help customers so they don't have to bother waiting in line at the barbershop because customers can set schedules on the application, especially during a pandemic like today. This application displays information about available time slots and those that have been booked by other customers so that customers can adjust their free time. The barbershop also does not need to register customers who place orders manually. This online booking application has passed trials with white box testing and black box testing methods. The result is that all the components contained in this online booking application system work as expected.
Implementasi Algoritma K-Nearest Neighbor dalam Menentukan Buku Berdasarkan Peminatan Faujatun Hasanah; Tati Suprapti; Nining Rahaningsih; Irfan Ali
Jurnal Accounting Information System (AIMS) Vol. 5 No. 1 (2022)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/aims.v5i1.467

Abstract

The use of computer technology helps a lot in human performance in various data and information management. Therefore, researchers use computers to make analyzes that can predict favorite books based on data from book borrowing records in the library. Researchers use is data mining. Data mining is a term used to describe the discovery of knowledge in databases, using statistical techniques, mathematics, artificial intelligence, and machine learning to extract and identify information that is useful for science. The use of data mining requires a method that can manage book borrowing data so that it gets the predictions of favorite books. The method used is K-Nearest Neighbor (KNN). The results of the accuracy in this study are 98.75%, Prediction of Disinterest with true Not Interest is 28 data, Prediction of Disinterest with true Interest is 1 data, Prediction of Interest with true No Interest is 0 data, Interest Prediction with true Interest is 54 data.
Cluster Barang Elektronik Mengguanakan Algoritma Fuzzy C-Means dengan Optimize Parameter Grid Lutfi Hakim; Irfan Ali; Martanto Martanto
Jurnal Accounting Information System (AIMS) Vol. 6 No. 1 (2023)
Publisher : Ma'soem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/aims.v6i1.695

Abstract

Electronic products are goods that are really needed at this time, because electronic goods really help humans in carrying out various daily activities, such as television, computers, cellphones, etc. The problem is how to apply the Fuzzy C-means method with Optimize Parameter Grid in the form of grouping electronic goods data for the needs of consumers used, and how to determine the optimum number of clusters from the use of the method used in grouping electronic goods data sets to find the best accuracy value. The purpose of this study was to apply the use of the fuzzy c-means algorithm in the case of grouping electronic data and produce an output to find out the best value of the electronic data used. While this research uses one method, namely the fuzzy cmeans algorithm with Optimize grid parameters which are included in the grouping rules in data mining. The research results are expected to be able to find the best electronic data set grouping based on the Davies Bouldin Index value resulting from the analysis of the fuzzy c-means algorithm at measure_type : NumericalMeasure, Dbi = 0.516 and measure_type : MixedMeasure, Dbi = 0.627.
Co-Authors Ade Irma Purnamasari Ade Rizki Rinaldi Agus Surip Agus Surip Anwar Pauji Aria Pratama Arif Rinaldi Dikananda Candi Prabowo Cep Lukman Rohmat Cep Lukman Rohmat Cep Lukman Rohmat Deffan Febrian Dirmanthara Dian Ade Kurnia Dita Rizki Amalia Edi Tohidi Ega Salsa Nugraha Farid Ali Ma'ruf Farids Al Ma’ruf Faujatun Hasanah Gifthera Dwilestari Hegarmanah Muhabatin Heliyanti Susana Iin Iqbal Agis Junizar Kaslani Kokom Komariah Lian Siliayani Lutfi Hakim Martanto . Muhamad Aji Pratama Muhammad Abdurohman Muhammad Aji Pratama Muhammad Fadhilah Mulyawan Mulyawan . Nadia Putri Gantara Nana Suarna Nining Rahaningsih Odi Nurdiawan Raditya Danar Dana Ranu Husna Riko Saputra Siti Aisyah Syaeful Annas Tati Suprapti Tio Prasetiya Tio Prasetya Utami Aryanti Uyu Nuraeni Yuniar Niar