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All Journal SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Fakultas Teknik UNISA Kuningan
Neng Sri Lathifah Zulfa
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Computer Science & IT Control & Systems Engineering Engineering

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PENERAPAN SISTEM MONITORING AKTIVITAS AKADEMIK SISWA PADA SMART INTEGRATED ACADEMIC SCHOOL (SIAS) BERBASIS ANDROID DI MTS AL IKHLAS JAMBAR Neng Sri Lathifah Zulfa; Fanji Fakhru Zaman; Reni Nuraeni
Jurnal Fakultas Teknik Kuningan Vol. 4 No. 3 (2023): Jurnal Fakultas Teknik
Publisher : Universitas Islam Al-Ihya Kuningan

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Abstract

This research aims to provide convenience to parents or guardians of students in knowingtheir students' academic progress. It also aims to facilitate teachers in conveying students'academic performance information to parents and enable easy monitoring of studentsand discussions with the school authorities. The research uses a qualitative method,where the researcher seeks to describe the process of developing the Smart IntegratedAcademic School monitoring system application. This application was developed usingthe waterfall system development method and programmed in PHP. The results to thisresearch show that the application is capable of providing convenience for parents totrack their students' academic progress. Additionally, the program created also facilitatesparents in easily monitoring their students' progress and engaging in discussions with theschool.
KLASIFIKASI KELAYAKAN PENERIMA BANTUAN LANGSUNG TUNAI DANA DESA (BLT DD) MENGGUNAKAN ALGORITMA NAÏVE BAYES DI DESA TARAJU: Bahasa Indonesia Neng Sri Lathifah Zulfa; Iffah Athifah
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 8 No 2 (2025): Jurnal SKANIKA Juli 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v8i2.3560

Abstract

The Direct Cash Assistance from Village Funds (BLT-DD) program is designed to provide support to rural communities with limited economic means. To ensure that the assistance is properly targeted, the selection process for beneficiaries must be carried out carefully. This study applies the Naïve Bayes algorithm to classify the eligibility of BLT-DD recipients in Taraju Village. Three variants of the Naïve Bayes algorithm were tested, namely Bernoulli Naïve Bayes, Gaussian Naïve Bayes, and Complement Naïve Bayes, using 10-fold cross-validation for evaluation. The results showed that Bernoulli Naïve Bayes achieved the highest accuracy at 91%, followed by Gaussian Naïve Bayes with 90%, and Complement Naïve Bayes with 64%. These findings indicate that Bernoulli Naïve Bayes is more effective in classifying the eligibility of BLT-DD recipients compared to the other two variants.
Co-Authors Fanji Fakhru Zaman Iffah Athifah Reni Nuraeni, Reni