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All Journal SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JurTI (JURNAL TEKNOLOGI INFORMASI) Jurnal Pengabdian Kepada Masyarakat MEMBANGUN NEGERI Infotekmesin Scientific Journal of Informatics Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat TIERS Information Technology Journal Jurnal Pengabdian Mitra Masyarakat (JPMM)
Ali Nur Ikhsan
Universitas Amikom Purwokerto
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : Infotekmesin

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Komparasi Model Prediksi Kurs Pada Masa Pandemi Covid-19 Menggunakan Neural Network Berbasis Genetic Algorithm dan Particle Swarm Optimization Ali Nur Ikhsan; Primandani Arsi; Jali Suhaman
Infotekmesin Vol 13 No 1 (2022): Infotekmesin: Januari, 2022
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v13i1.938

Abstract

Data from Bank Indonesia shows that the rupiah exchange rate against dollar weakened at the beginning of the Covid-19 pandemic. This exchange rate volatility is an important problem in the Indonesian economy. Therefore, the prediction model for the exchange rate against the dollar is needed during the Covid-19 pandemic to predict the exchange rate during the Covid-19 Pandemic. This study is proposed to compare the prediction of the rupiah exchange rate against the dollar using the GA-based Neural Network algorithm and the PSO-based Neural Network algorithm. Initially the data was collected in the period 2019 to 2021, then the data is preprocessed. Validation used the k-fold validation technique with a ratio of 70:30, while the evaluation is carried out with the output of RMSE. The results showed that the performance of PSO and GA was the same, namely 0.020 +/- 0.006.
Penerapan Multi-Palette Color untuk Pemberian Saran Pemilihan Warna Tema Desain Visual Vektor Suliswaningsih; Adam Prayogo Kuncoro; Ali Nur Ikhsan; Muhammad Thoriq Jamil; Syahrul Sani
Infotekmesin Vol 15 No 1 (2024): Infotekmesin: Januari, 2024
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v15i1.2081

Abstract

In graphic design, many creative applications offer many templates. This design platform is suitable for creative designers and hobbyists such as marketers, bloggers, social media managers, etc. In a design workflow, users select a template and replace elements with their resources. Instead of creating one color palette for all elements, researchers extract multiple color palettes from each visual element in a graphic document and then combine them into a set of colors. Researchers design sample color schemes to complement color sets and we recommend colors that might be determined based on the color context in a multi-palette. Researchers conducted model training and created a color recommendation system for a collection of vector visual designs. The proposed color recommendation method is targeted to be a color prediction medium, as well as a color recommendation system on vector media. The results of this study are in the form of color recommendations for vector graphic design based on a multi-palette of visual elements.
Co-Authors Adam Prayogo Kuncoro Alfiansyah Arifudin Akbar Alif Nur Fadilah Dani Arifudin Desri Nur Astri Deuis Nur Astrida Hendra Marcos Hidayah, Debby Ummul Imun Faizal Irma Darmayanti Isnaini, Khairunnisak Nur Jali Suhaman M. Syaiful Amin Muhammad Thoriq Jamil Muslimin Hidayat Primandani Arsi Pungkas Subarkah Raditya Sani Alifian Rayinda Maya Anjani Septi Oktaviani Nur Hidayah Siti Alvi Solikhatin Suliswaningsih Syahrul Sani