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Fuzzy Logic for Determination of Community Assistance Using the Tsukamoto Method for Residents of Kasreman Village, Rembang Dahlan Dahlan; Dini Rohmayani; Rachmat Iskandar
Journal of Applied Intelligent System Vol 7, No 3 (2022): Journal of Applied Intelligent System
Publisher : Universitas Dian Nuswantoro and IndoCEISS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v7i3.7162

Abstract

The obstacle to regional progress and the main cause of social problems is due to the large number of poor people, so there must be a poverty management program by the government, one of which is citizen assistance. The selection process by the local village apparatus is very much needed in the process of determining the recipients of citizen assistance, because the quota for the recipients of citizen assistance is less than that of registrants for citizen assistance. The distribution of aid does not fall to the right party resulting in injustice to other underprivileged families so that it creates several problems, where the method that will be used is Tsukamoto's Fuzzy Logic. In this study, the data used are land area, income of residents, number of dependents of the family. The evaluation method carried out in this study is using a confusion matrix, for one test the level of accuracy produced is 92.74%. Based on the experiment, it can be concluded that the Tsukamoto algorithm is quite accurate in determining citizen assistance to the residents of Kasreman Village, Rembang.
OPTIMALISASI FITUR DENGAN FORWARD SELECTION PADA ESTIMASI TINGKAT PENYAKIT PARU-PARU MENGGUNAKAN ALGORITMA KLASIFIKASI RANDOM FOREST Rangga Aditya Tarigan, Lukman; Dahlan, Dahlan
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 8 No. 5 (2024): JATI Vol. 8 No. 5
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v8i5.11064

Abstract

Penyakit paru-paru merupakan masalah kesehatan serius di Indonesia, dengan peningkatan kasus dan kematian yang signifikan. Penelitian ini bertujuan untuk meningkatkan akurasi klasifikasi penyakit paru-paru menggunakan algoritma Random Forest dengan metode optimasi fitur Forward Selection. Dataset yang digunakan terdiri dari 1.000 sampel dengan 10 atribut. Penelitian dilakukan dalam dua tahap: pertama, pengujian awal algoritma Random Forest tanpa optimasi fitur, dan kedua, pengujian dengan optimasi fitur menggunakan metode Forward Selection. Hasil pengujian awal menunjukkan akurasi sebesar 89,45%, Presisi 83.20%, Recall 100.00%. Setelah menerapkan optimasi fitur, akurasi meningkat menjadi 92,46%, presisi 95,88%, recall 89.42%. Peningkatan akurasi sebesar 3,01% ini menegaskan pentingnya optimasi fitur dalam meningkatkan performa model klasifikasi. Analisis atribut penting mengidentifikasi bahwa aktivitas olahraga, kebiasaan merokok, dan usia merupakan faktor yang paling signifikan dalam memprediksi penyakit paru-paru. Penelitian ini menyoroti bahwa penggunaan metode optimasi fitur seperti Forward Selection dapat secara signifikan meningkatkan akurasi prediksi model klasifikasi penyakit paru-paru.
Pelatihan Troubleshooting Komputer Dasar bagi Siswa Menengah di SMK Pusdikhubad Ari Sudrajat; Dahlan
JPPkM: Jurnal Pengabdian dan Pemberdayaan kepada Masyarakat Vol. 2 No. 1 (2026): JPPkM:Januari
Publisher : Yayasan Pemimpin Inovasi Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Enhancing the competence of Vocational High School students in the field of information technology is a primary priority to address the challenges of Industry 4.0 and the demands of the business and industrial world. Computer Troubleshooting Training is designed to bridge the gap between theoretical mastery in the classroom and students' practical skills in handling various technical issues with computer devices. The primary challenge faced by students is a lack of understanding regarding systematic diagnostic methodologies, which frequently leads to human error during the repair process. This training employs a combination of interactive lectures, demonstrations, and hands-on laboratory sessions. The training modules encompass hardware failure identification and software optimization. The expected outcome of this activity is an increase in students' technical independence and their readiness for job traning. By mastering methodical troubleshooting techniques, students are expected to provide efficient, rapid, and accurate technical solutions within a professional work environment.
Co-Authors Ari Sudrajat Dini Rohmayani Rachmat Iskandar Rangga Aditya Tarigan, Lukman