Claim Missing Document
Check
Articles

Found 3 Documents
Search

MACHINE LEARNING-BASED CLASSIFICATION OF SPACE TRAVEL ELIGIBILITY USING SUPPORT VECTOR MACHINE, RANDOM FOREST, AND XGBOOST Zahroni, Teguh Rizali; Imran, Bahtiar; Tahrir, Muhammad; Muh. Akshar; Marroh, Zahrotul Isti’anah
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 4 No. 2 (2025): May 2025
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v4i2.310

Abstract

This study applies machine learning classification techniques to predict passenger displacement events based on corrupted data retrieved from a hypothetical interstellar spacecraft mission. Using a cleaned and preprocessed dataset containing demographic, behavioral, and exposure-related features, we compare the performance of three classification models: Random Forest, Support Vector Machine (SVM), and XGBoost. Each model is trained on 80% of the data and evaluated on the remaining 20% using precision, recall, f1-score, and accuracy metrics. The SVM model shows the most notable improvement after feature selection, achieving a balanced performance across metrics. Meanwhile, Random Forest and XGBoost models maintain consistent and robust accuracy above 80% on both training and testing sets. Feature importance analysis also supports the interpretability of the models, particularly in Random Forest and XGBoost. The comparative analysis demonstrates that ensemble-based methods such as Random Forest and XGBoost are more effective in handling the complexity of the dataset, making them suitable for predictive tasks in high-dimensional, partially incomplete data scenarios.
Peningkatan Produksi Kompos Biochar Pembenah Tanah melalui Rekayasa Konstruksi Mesin Pencacah Bahan Organik dalam Mendukung Adaptasi dan Mitigasi Perubahan Iklim Pertanian bagi Masyarakat Kampung Belimau-Kelurahan Lempake, Kelurahan Sempaja Utara, Kota Samarinda Syafii, Syafii; Zarta, Abdul Rasyid; Akshar, Muh; Marroh, Zahrotul Isti'anah; Nurmarini, Eva; Patulak, Ita Merni; Alex, Taman; Tahrir, Muhammad; Zahroni, Teguh Rizali; Yusdiansyah, Yusdiansyah; Ridwan, Ridwan; Azzahrah, Nadia Fatimah
Jurnal SOLMA Vol. 14 No. 2 (2025)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v14i2.17412

Abstract

Background: Berkuranganya lahan subur, cekaman alam dan biotik terhadap lahan pertanian di Kalimantan Timur menuntut tindakan adaptasi yang bermuara pada peningkatan produktivitas dan keberlanjutan usaha pertanian. Adaptasi dan keberlanjutan menuntut inovasi kreativitas yang didasarkan riset, dengan adanya kegiatan produksi kompos biochar menggunakan mesin pencacah maka kuantitas hasil produksi akan semakin bertambah yang akan berpengaruh pada jumlah dan kualitas hasil pertanian. Tujuan dari kegiatan pengabdian ini adalah untuk memberikan pemahaman kepada masyarakat mengenai upaya peningkatan produksi kompos biochar pembenah tanah melalui rekayasa konstruksi mesin pencacah bahan organik. Mitra pada kegiatan pengabdian ini adalah Lembaga Swadaya Masyarakat (LSM) P4S Puri Leisa. Metode: Untuk mengatasi permasalahan maka diadakan penyuluhan dan pelatihan terhadap 15 – 20 orang petani dan mahasiswa, dengan materi teori dan praktek pembuatan kompos biochar selama 1 hari (4 jam) antara lain Penyiapan Alat Pirolysis, Pemilihan Bahan Biochar, Proses Pembakaran, Pemantauan Suhu dan Pemadaman, Penjemuran, Aktivasi dan Penepungan, Analisis dan Distribusi.  Hasil: Pada tahap awal kegiatan pengabdian, para peserta pelatihan mendapatkan kulsponsi penjelasan prosedur cara membuat kompos biochar dari instruktur. Tahap kedua adalah praktik dengan memasukkan bahan-bahan organik yang berasal dari limbah pertanian dan serasah kehutanan ke mesin pencacah untuk menghasilkan serbuk yang seragam sebelum akhirnya diproses menjadi biochar.  Limbah pertanian serta limbah kehutanan atau limbah alami organik lainnya tidak membutuhkan perlakuan khusus maupun perlakuan pendahuluan seperti dengan menjemurnya atau membuatnya menjadi bagian-bagian dengan ukuran lebih kecil. Kesimpulan: Melalui penggunaan mesin pencacah bahan alami, produktivitas kompos meningkat menjadi 800 kg per hari dibandingkan sebelumnya hanya berkisar 100-200 jika menggunakan tenaga manual. 
Mathematical Model of Basal Stem Rot (BSR) Disease Spread in Oil Palm Plants Zahroni, Teguh Rizali; Fahrizal, Fahrizal
Poltanesa Vol 25 No 1 (2024): June 2024
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v25i1.3003

Abstract

This study discusses the stability analysis of mathematical models for the spread of Basar Stem Rot(BSR) in oil palm plants. In developing this mathematical model, several assumptions are taken to obtain a model that is suitable for the spread of BSR disease. The resulting model is a system of first-order nonlinear differential equations with three variables. This research includes both analytical and numerical analysis. Analytical analysis includes determination of equilibrium points and local stability analysis, while numerical analysis is conducted using Microsoft Excel application. From this study, two equilibrium points were found with stability conditions that depend on the fulfillment of certain conditions. One important result obtained is that the equilibrium point will be locally stable if and only if α > μ and b > √D, where D is the discriminant of a quadratic equation. After analyzing analytically, the study continued with numerical simulations to illustrate and test the analytical results. Numerical results in the form of graphs show that the solution of the system is stable, which indicates that the disease will be endemic under certain conditions and time. This research provides a deeper understanding of the dynamics of the spread of BSR and the conditions that affect the stability of the spread of the disease. With this analysis, it is expected to contribute to efforts to control BSR disease in oil palm plants. In addition, this research also opens opportunities for the development of similar mathematical models for other plant diseases.