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Fachruddin Fachruddin
Pascasarjana Program Studi Teknik Sipil dan Lingkungan, Fakultas Teknologi Pertanian, SPs Institut Pertanian Bogor.
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Journal : JURIKOM (Jurnal Riset Komputer)

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Perbandingan Model Decision Tree dan Random Forest untuk Penentuan Kesesuaian Lahan Budidaya Cabai dan Terong Amir, Astiah; Fachruddin, Fachruddin; Idris, Fadli; Safriani, Meylis; Saefuddin, Reskiana; Nasution, Indera Sakti; Sanusi, Sanusi; Arisma Siregar, Mawaddah Putri
JURNAL RISET KOMPUTER (JURIKOM) Vol. 12 No. 5 (2025): Oktober 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i5.8672

Abstract

Kabupaten Aceh Barat memiliki potensi besar dalam budidaya tanaman hortikultura seperti cabai dan terong, meskipun karakteristik tanah gambut dengan tingkat keasaman tinggi dan variabilitas lingkungan menjadi tantangan utama. Penentuan kesesuaian lahan yang akurat memerlukan analisis berbagai variabel seperti pH tanah, kelembaban tanah dan udara, curah hujan, serta tekstur tanah. Penelitian ini bertujuan mengembangkan model klasifikasi kesesuaian lahan menggunakan algoritma Decision Tree dan Random Forest untuk tanaman cabai dan terong di wilayah tersebut. Data lingkungan dan karakteristik tanah dianalisis menggunakan kedua metode tersebut untuk mengevaluasi performa klasifikasi. Hasil penelitian menunjukkan bahwa algoritma Random Forest unggul dengan akurasi mencapai 99% pada klasifikasi lahan cabai, serta nilai precision dan recall yang lebih tinggi dibandingkan Decision Tree. Untuk klasifikasi lahan terong, kedua algoritma menunjukkan performa sempurna dengan akurasi dan metrik evaluasi mencapai 1.00 tanpa kesalahan klasifikasi. Keunggulan Random Forest terletak pada kemampuannya menangani variabel input yang kompleks dan mengurangi risiko overfitting melalui ensemble pohon keputusan, sehingga menghasilkan prediksi yang lebih stabil dan andal. Dengan demikian, Random Forest sangat cocok digunakan dalam sistem klasifikasi kesesuaian lahan berbasis data lingkungan di Aceh Barat, mendukung pengambilan keputusan budidaya yang lebih optimal dan berkelanjutan. Penelitian ini memberikan kontribusi penting dalam penerapan teknologi machine learning untuk meningkatkan efisiensi dan hasil produksi pertanian di wilayah dengan karakteristik tanah gambut yang menantang.Abstract. Kabupaten Aceh Barat has great potential for cultivating horticultural crops such as chili peppers and eggplants, despite the challenges posed by peat soil characteristics with high acidity levels and environmental variability. Accurate land suitability determination requires analysis of various variables such as soil pH, soil and air moisture, rainfall, and soil texture. This study aims to develop land suitability classification models using Decision Tree and Random Forest algorithms for chili and eggplant crops in the region. Environmental data and soil characteristics were analyzed using both methods to evaluate classification performance. The results show that the Random Forest algorithm outperforms with an accuracy of up to 99% in chili land classification, as well as higher precision and recall values compared to Decision Tree. For eggplant land classification, both algorithms demonstrated perfect performance with accuracy and evaluation metrics reaching 1.00 without any misclassification. The advantage of Random Forest lies in its ability to handle complex input variables and reduce the risk of overfitting through ensemble decision trees, resulting in more stable and reliable predictions. Therefore, Random Forest is highly suitable for use in land suitability classification systems based on environmental data in West Aceh, supporting more optimal and sustainable cultivation decision-making. This study makes an important contribution to the application of machine learning technology to improve agricultural efficiency and production outcomes in regions with challenging peat soil characteristics.
Co-Authors AA Sudharmawan, AA Abadi, Cecep Slamet Abidin, Dodo Zaenal Adi Syuriadi Agusmaniza, Roni Ahmad Zaki Aldri Frinaldi Alkhayr, Sabila Mujahidah Alvisyahri, Alvisyahri Andini, Mirna Ria Arbeni, Wawan Ariska, Nana Arisma Siregar, Mawaddah Putri Astuti, Theresia Widji Aulia Rahman Auliya, Nurul Azwardi Azwardi Belyamin Belyamin Beni Irawan Bulan, Ramayanty Candra Damis Widiawaty, Candra Damis Chablullah Wibisono Dahlan Dahlan Desi Kisbianty, Desi Devianti, Devianti Dewi Purnama Sari DIAN FEBRIANTI Dinda, Raina Parmitalia Diswandi Nurba, Diswandi Errissya Rasywir Fahrijal, Farkhan Farizal, Teuku fathushahib, fathushahib Fazlina, Rita Februssi, Aditya Handriyani, Cut Hasibuan, Mulkan Hibatullah, Iqmal Ibrahim, Mikhail Claudio Idris, Fadli Indera Sakti Nasution Isfanda, Isfanda Jasmir, Jasmir Juliwardi, Ilham Kusumawati, Andi Malia, Rezqi Masganti Sit MASRURA, DELFIAN Mauliza, Rahma Meylis Safriani Muhammad Ardiansyah Muhammad Hidayat Tullah, Muhammad Hidayat Muhammad Ismail Muhammad Riza Pahlevi Muhammad Usman, Muhammad Muhammad Yasar Mustaqimah Mustaqimah Novianita, Lizza Nuraini, Assyifah Nurfitriani, Antie Nurhadi Pramulya, Rahmad Pramulya, Rahmat Putra, Nobby Darly Dwi Putri, Shinta Buana Rahman, Farhan Maulana Raina Parmitalia Dinda Rasywir , Errissya Rinaldy Rinaldy Rizki, Gebrina Robin Sirait Saefuddin, Reskiana Sahkholid Nasution Sanusi Sanusi Smarajaya, I Dewa Made Suharmanto, Billy Suhendra, Rivansyah Sulindawati, Rishi Suryadi Suryadi Susanta, Agus Syamsuddin Syamsuddin Utama, Melda Utari, Selfia Dela Utomo, Machfud Priyo Veranita, Veranita WILLY RIYADI Yovi Pratama Yuli Mafendro Dedet Eka Saputra Yusra, Andi yusuf, Ahmad Maulana Zainuddin, Zainuddin Zulyaden, Zulyaden