Article Per Year (5 Year)
p-Index From 2020 - 2025
0.659
P-Index
This Author published in this journals
All Journal Jurnal Informatika Universitas Pamulang Jurnal Riset Manajemen dan Ekonomi Southeast Asia Journal on Open and Distance Learning
Ihsan Fauzi
Unknown Affiliation
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Strategi Branding Online melalui Konten Kreatif untuk Meningkatkan Daya Saing Produk Rawon Kluwek Surabaya Ihsan Fauzi; Ni Made Ida Pratiwi
JURNAL RISET MANAJEMEN DAN EKONOMI (JRIME) Vol. 3 No. 4 (2025): Oktober : JURNAL RISET MANAJEMEN DAN EKONOMI
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jrime.v3i4.2895

Abstract

This study aims to develop an online branding strategy for Rawon Kluwek Surabaya through the creation of creative content to enhance the product's competitiveness in the culinary market. Through this community service activity, business owners were trained in techniques for creating engaging visual content, managing social media, and implementing storytelling to strengthen brand image. The results of this activity show that business owners experienced an improvement in their skills in producing more professional product photos and videos, as well as in managing their social media accounts more effectively. Increased interaction and engagement from consumers on social media demonstrate that creative content successfully attracted a wider audience, which in turn contributed to improving the product's competitiveness. Based on the evaluation conducted, this activity has had a positive impact on strengthening Rawon Kluwek Surabaya’s position in an increasingly competitive market. However, there are still challenges in maintaining consistent content production, which requires further attention to ensure the sustainability of this branding strategy.
Educational Data Mining: Comparison of Models for Predicting Non-Academic Students Aldin Febriansyah; Ihsan Fauzi
Southeast Asian Journal on Open and Distance Learning Vol. 1 No. 02 (2023): Capturing the Future of Education with AI-Driven Innovations in Online Learnin
Publisher : SEAMEO SEAMOLEC

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Passing the national assessment test in Bahasa Indonesia for Paket C students is still a challenge, especially for non-academic students. This is caused by various factors, such as educational background, economic conditions, and learning motivation. This research aims to develop a prediction model for Package C students passing the national assessment exam in Indonesian using four machine learning algorithms, namely neural network, logistic regression, support vector machine, and naive bayes. The data used in this study are data on equivalency education exam tryout scores, equivalency education exam scores, schools, and regional information from 1,240 non-academic students who took the Equivalency Education Exam in the Indonesian language subject in the 2020-2021 academic year. This research uses machine learning methods in the context of Educational Data Mining. The preliminary analysis results show that the four machine learning algorithms can be used to predict the graduation of Paket C students with a fairly high accuracy. The neural network algorithm shows the best performance with 57.5% accuracy. SVM, LR, and NB algorithms achieved 56.2%, 54.8%, and 48.4% accuracy, respectively. The results of this study have the potential to increase the pass rate of Package C students on the Indonesian language national assessment test. The prediction model developed can be used to identify students at risk of not graduating, so that appropriate educational interventions can be provided.
Pengaruh Smoothing Data Terhadap Hasil Prediksi Volume dan Ritasi Sampah di Kota Bandung Menggunakan Metode Regresi Linear Gunawansyah; Ihsan Fauzi
Jurnal Informatika Universitas Pamulang Vol 9 No 3 (2024): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v9i3.43271

Abstract

The waste problem is very important in big cities, especially Bandung. The population, people's lifestyles and waste management that has not been carried out professionally are a challenge in itself. One of the preparatory steps to deal with the waste problem is to predict the development of waste volume. In this study, a statistical time series approach, namely the linear regression method, is used to predict the volume and transportation of waste in the city of Bandung. In the prediction process, data processing before being used in the prediction process plays an important role, one of which is data smoothing. A process to smooth the data using the moving average method with intervals of 2.3 and 4 and moving averages with weights of 242 and 12421 will be used to see its effect on the prediction results. Scenario 1 of the data used is all monthly data in the dataset time range and scenario 2 uses the same month's data for each year to predict the results of the month in the following year. The results of the volume and transportation predictions of waste between the best results from the Smoothing method and the results without going through the data smoothing process in scenario 1 show less significant results, namely less than 1%, while in scenario 2 it shows quite significant results, namely around 10% when compared to the actual data. Patterns and data ranges affect the final result from scenarios above.
Co-Authors Aldin Febriansyah Gunawansyah Pratiwi, Ni Made Ida