Article Per Year (5 Year)
p-Index From 2019 - 2024
3.11
P-Index
This Author published in this journals
All Journal PROTON WIDYA TEKNIKA Journal of Information Technology and Computer Science (JOINTECS) JIKO (Jurnal Informatika dan Komputer) Turbo : Jurnal Program Studi Teknik Mesin Resona : Jurnal Ilmiah Pengabdian Masyarakat Conference on Innovation and Application of Science and Technology (CIASTECH) Jurnal Masyarakat Merdeka (JMM) Jurnal Aplikasi Dan Inovasi Ipteks SOLIDITAS
Arie Restu Wardhani
Program Studi Teknik Industri, Fakultas Teknik, Universitas Widyagama, Malang
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

Published : 26 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : JIKO (Jurnal Informatika dan Komputer)

 1 
PEMETAAN DAN ANALISIS PERKEMBANGAN BIDANG GAMIFICATION BERBASIS METODE KOMBINASI OPEN KNOWLEDGE MAP DAN VOS VIEWER Fitri Marisa; Arie Restu Wardhani; Wiwin Purnomowati; Anastasia L Maukar
JURNAL INFORMATIKA DAN KOMPUTER Vol 6, No 2 (2022): ReBorn -- September 2022
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1597.494 KB) | DOI: 10.26798/jiko.v6i2.606

Abstract

Artikel ini melaporkan tentang kajian penelusuran mengenai perkembangan bidang gamification dalam 10 tahun terakhir. Sumber data diperoleh dari meta data publikasi jurnal ilmiah, tesis, dan disertasi dalam rentang tahun 2012 hingga 2022. Kajian ini menggunakan metode penelusuran literature review yang mengkombinasikan aplikasi Open Knowledge Map (OKM) dan Vos Viewer (VV) dimana data diolah dengan mengikuti prosedur aplikasi yang digunakan kemudiaan dianalisis. Hasil kajian ini menyajikan pemetaan dan analisis peluang-peluang riset masa depan terkait gamification dan bagaimana keterkaitan antar penelitian dalam membentuk state of the art penelitian. OKM digunakan untuk memetakan kluster-kluster bidang gamification, sedangkan VV berperan untuk melihat kluster gamifikasi dengan analisis dan sumber yang berbeda. Berdasarkan hasil analisis, terdapat kecenderungan sub bidang gamification design menjadi topik yang memiliki literatur terbanyak, terkini dan te relasi dengan beberapa sub topik. Untuk itu peluang penelitian di sub bidang ini masih terbuka luas dan masih perlu untuk dikembangkan. 
POTENTIAL CUSTOMER ANALYSIS USING K-MEANS WITH ELBOW METHOD Fitri Marisa; Arie Restu Wardhani; Wiwin Purnomowati; Anik Vega Vitianingsih; Anastasia L Maukar; Erri Wahyu Puspitarini
JURNAL INFORMATIKA DAN KOMPUTER Vol 7, No 2 (2023): SEPTEMBER 2023
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiko.v7i2.911

Abstract

This study aims to obtain cluster data of potential customers using the K-Means clustering approach supported by the elbow method to determine the correct number of clusters. The data sample that was processed was 100 customer data from a minimarket containing three criteria (gender, age, and purchase retention). The number of initial clusters is determined as 5 and then processed by calculating K-Means. The calculation of the SSE value in the K-Means process produces the lowest SSE value, and the sharpest elbow angle graph visualization is in cluster 4. So, it can be stated that the best number of clusters in this K-Means calculation is four (4) which are used as material for further analysis. Then the analysis results of four (4) clusters state that potential customers are those with high purchase retention, consisting of female customers who dominate in the three (3) clusters. Most potential female customers are customers with an age range above 35 years. Meanwhile, customers with less potential are spread across each cluster with varied gender and age but are not dominant. Thus, this knowledge can be used as a consideration for the management in determining the right promotion strategy.
Co-Authors Alfi Septianto Alif Dio Raka Wisnu Alif Dio Raka Wisnu Anastasia L Maukar Anastasia Lidya Maukar Andri Andri Andy Hardianto Andy Hardianto Anik Vega Vitianingsih Apriliano, Muhammad Aufar Mepian Arief Rizki Fadhillah Dadang Hermawan Emma Budi Sulistiarini Erri Wahyu Puspitarini Fachrudin Fachrudin Fatikah, Nur Fitri Marisa Fitri Marisa Hasean, Regina Berliane Febe Imaudy Alif Okananti Istiadi Mardiana Andarwati Muslimin, M. Mustakim Mustakim Naif Fuhaid Nisak, Anggun Cahya Choirun Nova Risdiyanto Ismail Paramita, Niken Purbo Suwandono Riko Dwi P. Riska Suryanti Putri Riska Suryanti Putri Sabela, Nanda Budiarta Sakinah, Renada Julia Saputra, Reza Rafi Sari, Yuninda Wulan Silviana Silviana Silviana Silviana Syahroni Wahyu Iriananda, Syahroni Wahyu Tubagus Mohammad Akhriza Uyun Nadzirotul Faidah Wiwin Purnomowati Yuninda Wulan Sari Yuninda Wulan Sari