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All Journal Jurnal Ekonomi Syariah Pelita Bangsa Jurnal Ilmiah SIGMA: Informatics Engineering Journal of UPB JURNAL PARADIGMA: Journal of Sociology Research and Education Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Juni-Jurnal Pelita Nusa RESLAJ: Religion Education Social Laa Roiba Journal Da'watuna: Journal of Communication and Islamic Broadcasting Jurnal Dirosah Islamiyah El-Mujtama: Jurnal Pengabdian Masyarakat
Aceng Badruzzaman
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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Prediksi Pasien Terkena Penyakit HIV Dengan Algoritma K Nearest Neighbor KNN di RSUD Dr Chasbullah Abdul Madjid Kota Bekasi Firdaus, Abdul Aziz; Sanudin, Sanudin; Aceng Badruzzaman
JURNAL PARADIGMA : Journal of Sociology Research and Education Vol. 6 No. 1 (2025): JUNI 2025 JURNAL PARADIGMA: Journal of Sociology Research and Education
Publisher : Labor Program Studi Pendidikan Sosiologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53682/jpjsre.v6i1.11357

Abstract

HIV AIDS is a global health concern present in almost every part of the world The advancement of information system technology has helped solve various problems across different fields one of which is through the application of data mining The utilization of data mining is not only implemented in the healthcare sector but also in the technology industry One method to predict patients who potentially have HIV AIDS is by using Machine Learning ML ML aims to train models with algorithms capable of performing statistical analysis using Supervised Learning techniques to generate accurate predictions Prediction is one of the most important statistical elements in the decision making process This research uses the K Nearest Neighbor algorithm which classifies data based on the majority class of K nearest neighbors The algorithm is combined with the SMOTETomek technique as a resampling method to address data containing noise and class imbalance problems The dataset used to train the K Nearest Neighbor model comes from the Voluntary Counselling and Testing VCT unit with a total of 2 205 data points The disease testing prediction results are then processed and visualized in a website format Based on testing conducted using Confusion Matrix the model s performance measurement results show and Accuracy value of 97 96 Precision of 78 61 Recall of 98 88 and f1 score of 84 45 The results indicate that the use of machine learning is quite effective for implementation in HIV AIDS disease prediction < p>
Penerapan Data Mining Untuk Penentuan Status Gizi Balita Menggunakan Algoritma Naive Bayes (Studi Kasus Posyandu Seruni Xii Kelurahan Karangraharja) Aceng Badruzzaman; Rita Nuraeni
Jurnal SIGMA Vol 13 No 3 (2022): September 2022
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/sigma.v13i3.7306

Abstract

Pembangunan kesehatan merupakan bagian penting dari upaya pemerintah dalam meningkatkan kualitas sumber daya manusia, salah satunya melalui pembinaan kesehatan sejak usia dini. Gizi berperan penting pada masa balita karena berpengaruh langsung terhadap pertumbuhan dan derajat kesehatan. Penelitian ini memanfaatkan data balita yang diolah menggunakan teknik data mining untuk menentukan status gizi balita. Metode yang digunakan adalah algoritma Naive Bayes dengan atribut berat badan (BB), tinggi badan (TB), dan umur. Hasil penelitian menunjukkan tingkat akurasi sebesar 90,91% untuk penentuan status gizi berdasarkan BB/U dan 92,42% berdasarkan TB/U.
Implementasi Metode Simple Additive Weighting Dalam Sistem Pendukung Keputusan Penentuan Beasiswa Santri Pondok Pesantren Nurul Ulum Bekasi Berbasis Website Aceng Badruzzaman; Ahmad Ripaldi
Jurnal SIGMA Vol 14 No 2 (2023): Juni 2023
Publisher : Teknik Informatika, Universitas Pelita Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37366/sigma.v14i2.7310

Abstract

Penelitian ini dilakukan di Pondok Pesantren Nurul Ulum Bekasi Jawa Barat. Beberapa hal yang melatarbelakanginya adalah karena ditemukan masalah tentang bagaimana melakukan penyeleksian untuk penerimaan beasiswa di pondok pesantren Nurul Ulum agar lebih efektif dan efisien. Dalam penelitian ini, digunakan beberapa calon santri sebagai alternatifnya dan menggunakan 5 kriteria, diantaranya hafalan, nilai rapor, tes bahasa arab, tes bahasa inggris dan prestasi. Penelitian ini menghasilkan sebuah aplikasi sistem pendukung keputusan berbasis web yang diharapkan dapat membantu pondok pesantren dalam seleksi penerima beasiswa. Metode yang digunakan dalam pengembangan sistemnya adalah menggunakan waterfall, dan metode analisa perhitungannya adalah Simple Additive Weighting (SAW). Sistem dimodelkan menggunakan UML (Unified Modelling Language) yang teridi dari Use Case Diagram, Acticity Diagram, Sequence Diagram dan class diagram. Sistem dibangun menggunakan Bahasa Pemrograman PHP dan Database MySQL dan pengujian dilakukan menggunkan Black Box Testing. Sedangkan teknik pengumpulan data menggunakan metode penelitian dengan cara observasi, wawancara, dan studi pustaka.
Nilai-nilai Khazanah Kearifan Lokal dalam Pengembangan Pendidikan Islam di Lingkungan Pesantren Aceng Badruzzaman; Muhammad Najamuddin Dwi Miharja
Reslaj: Religion Education Social Laa Roiba Journal Vol. 7 No. 7 (2025): RESLAJ: Religion Education Social Laa Roiba Journal
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/reslaj.v7i7.7779

Abstract

Islamic education is referred to as a system and method for improving the quality of human life which basically aims to develop true Muslim individuals by developing each person's physical and spiritual potential. This research aims to identify and analyze local wisdom values ​​that can be integrated in the development of Islamic education in the Islamic boarding school environment. Local wisdom is cultural wealth that contains noble values, which, if applied in Islamic education, can enrich and strengthen the character of students. Using a qualitative approach with a case study method, this research examines educational practices in several Islamic boarding schools that have succeeded in integrating local wisdom in their curriculum. The research results show that local wisdom values, such as mutual cooperation, tolerance and respect for nature, have high relevance to the basic principles of Islam. The implementation of these values ​​not only deepens understanding of religion, but also shapes the attitudes and behavior of students who are more civilized and broad-minded. The conclusions of this research emphasize the importance of developing an adaptive and contextual curriculum, which is able to accommodate local wisdom values ​​to improve the quality of education in Islamic boarding schools. It is hoped that these findings can become a reference for Islamic boarding school managers in designing holistic and integrative education programs.
Co-Authors Abdul Bari Ahmad Ripaldi Ali Nur Ahmad Badriya Hisniati, Sally Ermanto Firdaus, Abdul Aziz Hasan Basri Irvan Destian Ismamudi Ismamudi Kisanda Midisen Listian Indriyani Achmad Matnin Muhammad Guntur Alting Muhammad Najamuddin Dwi Miharja Nova Sariwati Rita Nuraeni Sanudin Sanudin Shofiyatus Sholihah Sukron Makmun Sukron Mamun Wira Syuhada Wulan Windiarti