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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Sistem dan Informatika International Journal of Law Reconstruction Jurnal Pendidikan Informatika dan Sains Jurnal Khatulistiwa Informatika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Al-Khidmah JURNAL EDUCATION AND DEVELOPMENT NUSANTARA : Jurnal Ilmu Pengetahuan Sosial CYBERNETICS BULETIN AL-RIBAATH JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) GERVASI: Jurnal Pengabdian kepada Masyarakat Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) Jurnal Teknika Jurnal Abdi Insani JIKA (Jurnal Informatika) Journal of Innovation Information Technology and Application (JINITA) Innovation in Research of Informatics (INNOVATICS) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) JUTECH : Journal Education and Technology Jurnal Pengabdian Masyarakat Nusantara Jurnal Media Informatika JUSTIN (Jurnal Sistem dan Teknologi Informasi) Joutica : Journal of Informatic Unisla Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Riset Rumpun Ilmu Teknik (JURRITEK) Jurnal Ilmiah Teknik Informatika dan Komunikasi Kohesi: Jurnal Sains dan Teknologi SmartComp Jurnal Informatika Polinema (JIP) Journal of Multidiscipline and Collaboration Research Jurnal Ragam Pengabdian JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) KREATIF: Jurnal Pengabdian Masyarakat Nusantara
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Journal : smartcomp

Implementation of Data Mining to Predict Dengue Prone Areas Using C4.5 Algorithm (Case Study: Sanggau Regency) Kalsum, Dayang Nur; Alkadri, Syarifah Putri Agustini; Istikoma, Istikoma
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 14, No 1 (2025): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v14i1.7540

Abstract

Applying data mining to predict areas prone to dengue fever is the right thing. The C4.5 algorithm or also known as the decision tree algorithm is a data mining technique that can be used to create predictive models based on historical data. This research aims to develop a prediction model for dengue-prone areas in Sanggau Regency using the C4.5 algorithm with research methodology such as problem identification, data collection, data needs analysis, system design, system development, system testing, analysis of test results system, drawing conclusions. The author can build a website application to help predict areas prone to dengue fever. The application that was built can help the Health Service in predicting dengue fever even though there is a lack of accuracy. In this context, historical data regarding dengue cases, risk factors and regional characteristics in Sanggau Regency can be used to make accurate predictions regarding dengue-prone areas. It is hoped that the creation of a prediction application for dengue-prone areas by taking data from the Sanggau Regency office from 2018-2023 will be more helpful in providing information, especially for areas experiencing dengue fever in the future
SISTEM PAKAR DIAGNOSA PENYAKIT TANAMAN JERUK MENGGUNAKAN METODE CERTAINTY FACTOR Pirman Pirman; Barry Ceasar Octariadi; Syarifah Putri Agustini Alkadri
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 15, No 2 (2026): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v15i2.10197

Abstract

Jeruk adalah komoditas utama di Desa Tekarang, Kabupaten Sambas, Kalimantan Barat. Namun, dalam beberapa tahun terakhir, produksi jeruk mengalami penurunan akibat serangan penyakit seperti lalat buah, kutu loncat, diplodia basah, dan kering, yang mengakibatkan penurunan kualitas dan kerugian bagi petani. Penelitian ini mengembangkan Sistem Pakar Diagnosa Penyakit Jeruk menggunakan metode Certainty Factor untuk membantu Dinas Pertanian dalam mendiagnosa penyakit berdasarkan gejala yang terdeteksi. Certainty Factor digunakan untuk mengukur tingkat keyakinan diagnosis guna meningkatkan akurasi hasil. Uji coba menunjukkan akurasi sistem sebesar 78,57% dibandingkan dengan diagnosis pakar. Sistem ini diharapkan dapat menjadi alat bantu efektif bagi petani dan pihak terkait dalam mengenali penyakit jeruk dan mengambil langkah pengendalian yang tepat.