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All Journal Jurnal PAI Raden Fatah JSAI (Journal Scientific and Applied Informatics) Jurnal Informasi dan Teknologi Jurnal Software Engineering and Computational Intelligence
Evi Purnamasari
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Religion Humanities Computer Science & IT Education Social Sciences

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Journal : JSAI (Journal Scientific and Applied Informatics)

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Pendekatan Data-Driven untuk Pengembangan Model Prediksi Tingkat Kemiskinan di Provinsi Indonesia Evi Purnamasari; Dwi Asa Verano
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7596

Abstract

Poverty in Indonesia remains a major issue that requires serious attention, particularly at the provincial level. Various factors, such as access to education, healthcare, and employment opportunities, affect the poverty rate. This study aims to develop a poverty prediction model using a data-driven approach through cluster analysis and classification. The methods used in clustering are K-Means, Hierarchical Clustering, and DBSCAN, while for classification, the algorithms applied are Random Forest, Naive Bayes, and Support Vector Machine (SVM). The clustering analysis results show that K-Means provides clearer cluster divisions with the highest Calinski-Harabasz Index value (179.45). In classification model testing, Naive Bayes provides the best results with an accuracy of 99.42%, which is higher than the other models. To address overfitting, cross-validation testing was conducted, yielding a Mean Accuracy of 99.32% and a Standard Deviatin of 0.23%. This study successfully identifies the factors influencing poverty levels in Indonesia’s provinces, which can be used as a basis for government policies in poverty alleviation efforts. The results achieved contribute significantly to the development of a more accurate and effective predictive model for addressing poverty issues in Indonesia.
Prediksi Kepuasan Pelanggan pada Layanan E-government Menggunakan Algoritma Decision Tree Indah Permatasari; Dona Marcelina; Evi Purnamasari
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7718

Abstract

The Online Licensing Service Information System (SIPPERI) implemented by DPMPTSP Palembang City aims to enhance efficiency, transparency, and accountability in public services. However, several challenges were reported by users, including unintuitive navigation, slow system responses, and inaccurate information. These challenges impact the level of user satisfaction with the service. This study uses the decision tree algorithm to evaluate user satisfaction based on data obtained through questionnaires with a Likert scale assessment involving 100 respondents. The analysis process uses the Python programming language. The dimensions analyzed include Efficiency (E), Trust (T), Reliability (R), Service (CS), Usability (U), Information Availability (I), and Interaction (SI). The analysis results show that the decision tree algorithm achieves an accuracy rate of 95%. The highest-scoring dimensions were recorded in the indicators Download Speed of Forms (R1: 392) and Accuracy of Instructions (E4: 392). Conversely, the lowest-scoring dimensions were Intuitive Navigation (E1: 300) and Information Availability (I1: 314). This study provides strategic recommendations for DPMPTSP Palembang City to improve dimensions with low scores to enhance user experience and strengthen public trust in e-government services.
Co-Authors Dewi Sartika Dona Marcelina Dwi Asa Verano haviz, Muhammad haviz irfani Indah Permatasari MIFTAHUL JANNAH Priscila Yuni Praditya, Ni Wayan