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All Journal Gudang Jurnal Multidisiplin Ilmu Jurnal Riset Sistem Informasi
Yua Isman Islam
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Religion Aerospace Engineering Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Public Health Social Sciences Other

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SISTEM INFORMASI PEMBUATAN SURAT REKOM PINDAH NIKAH BERBASIS WEBSITE Yua Isman Islam; Naufal Arif Maulana; Nur Azise
Jurnal Riset Sistem Informasi Vol. 2 No. 1 (2025): Januari : Jurnal Riset Sistem Informasi
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/1c83sa23

Abstract

The Website-Based Marriage Status Change Recommendation Letter Information System is developed to simplify the process of creating recommendation letters for couples who wish to change their marital status with the relevant authorities. The primary goal of this application is to streamline a complex process, accelerate letter issuance, and make it easier for users to submit applications online. Key features include personal data entry, uploading supporting documents, and verification by authorized officers. With a web-based platform, this application can be accessed anytime and anywhere, reducing the need to visit government offices in person. The system is expected to make the administrative process related to marriage status changes more efficient and transparent.
Klasifikasi Kemiskinan Di Jawa Timur Menggunakan Data Mining Algoritma K-Nearest Neighbor (KNN) Yua Isman Islam; Zaehol Fatah
Gudang Jurnal Multidisiplin Ilmu Vol. 2 No. 11 (2024): GJMI - NOVEMBER
Publisher : PT. Gudang Pustaka Cendekia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/gjmi.v2i11.1089

Abstract

Kemiskinan merupakan masalah sosial-ekonomi yang serius di Jawa Timur, yang memerlukan analisis mendalam untuk memahami faktor-faktor yang mempengaruhi kondisi tersebut. Algoritma K-Nearest Neighbor (KNN) dalam data mining digunakan untuk mengklasifikasikan tingkat kemiskinan berdasarkan data sosial ekonomi di Jawa Timur. Data yang digunakan mencakup beberapa atribut, seperti persentase penduduk miskin, pengeluaran per kapita, indeks pembangunan manusia, dan akses sanitasi. Dengan mengeksplorasi berbagai nilai K, akurasi KNN dievaluasi dalam memprediksi kategori kemiskinan (tinggi atau rendah). Hasil analisis menunjukkan bahwa model KNN mencapai akurasi 92,11%, memberikan kontribusi dalam pemetaan kemiskinan yang dapat mendukung kebijakan pengentasan kemiskinan di tingkat daerah.
Co-Authors Naufal Arif Maulana Nur Azise Zaehol Fatah