Claim Missing Document
Check
Articles

Found 4 Documents
Search
Journal : Indonesian Journal of Cultural and Community Development

Application System Document Submission to Improving Services in Jedongcangkring Village, Prambon District Web-Based Muhammad Fadil Santoso; Arif Senja Fitrani
Indonesian Journal of Cultural and Community Development Vol 9 (2021): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (275.44 KB) | DOI: 10.21070/ijccd2021752

Abstract

One of the problems faced by the Jedongcangkring village government, Prambon sub-district, is the process of submitting village documents in making or submitting manual letters, where this has an impact on services that are less than optimal for Jedongcangkring village residents, Prambon sub-district. During this Covid-19 pandemic, information technology is needed by humans in carrying out various human jobs. A computer is a device that was created to facilitate human work, while achieving rapid progress both in terms of hardware and software. The use of Microsoft Word, Excel, Outlook, and other office software in making letters has several weaknesses, such as dependence on high village administrative capabilities resulting in letter formats often changing and prone to inaccuracies in recording data from letters that have been made. With this web-based village village document submission application, it is hoped that it can solve the problems that are being faced by Jedongcangkring village, Prambon sub-district in carrying out correspondence activities and improving correspondence administration services to be better.
Web-Based Digital Marketing Application for Selling Qurban Animals in Qurban Cages in Sidoarjo Regency Silvie Nur Millah; Arif Senja Fitrani
Indonesian Journal of Cultural and Community Development Vol 11 (2022): March
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (306.841 KB) | DOI: 10.21070/ijccd2022786

Abstract

Technological advances in various fields of technology encourage the emergence of various new innovations that have a very positive impact on the world of trade. With the number of internet users increasing day by day, it opens up opportunities for entrepreneurs to develop their business through mobile phones. Like cattle and goats, which are in great demand by the public for religious purposes or for consumption, the demand for these animals increases at the time of Eid al-Adha. In 2019, beef consumption was 18,913,246 tons while goat meat was 8,608,121 tons. However, in buying and selling activities, cattle farmers still use simple information media so that they are not optimal. Therefore, to support the sales process, a web-based information system is needed. Customers will find it easier to access the information they need at any time regarding prices, conditions, and maintenance. This application is made using the waterfall method starting from analysis, design, coding, testing, to maintenance. With these problems, the authors examine the existing problems, namely "Digital Marketing Applications in Increasing Web-Based Livestock Sales in Qurban Cages in Ganggang Panjang Village, Sidoarjo.
Prediction Model of Voter Participation Using Naïve Bayes and Village Development Indicators: Model Prediksi Partisipasi Pemilih Menggunakan Naïve Bayes dan Indikator Pembangunan Desa Abidin, Husnul; Fitrani, Arif Senja; Setiawan, Hamzah; Indahyanti, Uce
Indonesian Journal of Cultural and Community Development Vol. 16 No. 2 (2025): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijccd.v16i2.1243

Abstract

Background: Electoral participation reflects the quality of democracy, particularly in rural communities with diverse socioeconomic structures. Specific Background: In Sidoarjo Regency, disparities in participation levels among villages suggest that local development factors play a crucial role. Knowledge Gap: Previous models only used demographic attributes without integrating the multidimensional Village Development Index (IDM) indicators. Aims: This study aims to construct a predictive model of voter participation using the Naïve Bayes classification algorithm based on IDM data. Results: By applying preprocessing, feature selection, and probabilistic classification to 48 attributes of IDM, the model achieved 78.65% accuracy, 79% precision, 76% recall, and 77% F1-score, revealing that education, health, and accessibility variables are key predictors. Novelty: Unlike prior research, this work combines social, economic, and ecological IDM dimensions with an open-source Python-based approach for transparent model validation. Implications: The findings demonstrate the feasibility of data-driven governance tools for mapping electoral participation and can support strategic planning to improve civic engagement in rural Indonesia.Highlights:• Uses IDM indicators to predict election participation• Naïve Bayes model achieves 78.65% accuracy• Supports data-driven democratic planning
Decision Tree Analysis for Predicting Voter Participation Using IDM Data: Analisis Pohon Keputusan untuk Memprediksi Partisipasi Pemilih Menggunakan Data IDM Yuwanto, Mahmud Adi; Fitrani, Arif Senja; Dijaya, Rohman; Indahyanti, Uce
Indonesian Journal of Cultural and Community Development Vol. 16 No. 2 (2025): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijccd.v16i2.1255

Abstract

General Background: Voter participation serves as a core indicator of democratic quality and civic awareness. Specific Background: In East Java’s Mataraman region, significant disparities in electoral participation highlight socioeconomic influences measurable through the Village Development Index (IDM). Knowledge Gap: No prior research integrates IDM-based indicators with machine learning methods for voter behavior prediction. Aims: This study develops a classification model using C4.5, Naïve Bayes, and SVM algorithms to predict voter participation based on IDM attributes. Results: The Decision Tree C4.5 algorithm achieved the highest accuracy (80.87%) and F1-score (0.88) compared to Naïve Bayes and SVM, identifying education and healthcare access as primary determinants of high participation. Novelty: The integration of IDM and C4.5 classification introduces a novel framework for data-driven political participation analysis. Implications: The model can assist policymakers and electoral bodies in targeting civic engagement initiatives within underrepresented regions. Highlights: C4.5 algorithm effectively predicts voter engagement. Education and health access influence participation. Data-driven policy enhances democratic quality.