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All Journal Jurnal Simantec Applied Information System and Management Zeta - Math Journal Jurnal Mnemonic Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) Buana Informatika Nusantara Journal of Computers and its Applications Intelmatics JIPI (Jurnal IPA dan Pembelajaran IPA) NERO (Networking Engineering Research Operation) Journal of Elektronik Sistem InformasI Bajhrah : Jurnal Pengabdian Kepada Masyarakat
Moh. Badri Tamam
Fakultas Teknik Uim Pamekasan
Religion Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Physics Social Sciences Other

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Journal : Intelmatics

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Optimizing Agricultural Land Fertility through Nutrient Content and pH Analysis Tamam, Moh. Badri; Anwari; Rofiuddin; Supriatin
Intelmatics Vol. 5 No. 2 (2025): July-December
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v5i2.24051

Abstract

This research addresses the challenge of declining soil fertility in Pamekasan, East Java, by proposing a machine learning approach to improve the accuracy of soil fertility classification and provide data-driven recommendations. Conventional methods like linear regression and expert systems are limited in capturing the complexity of soil variables, leading to less accurate results. Therefore, this study compares the performance of two machine learning algorithms, Random Forest and XGBoost, in classifying soil fertility levels based on nutrient content (N, P, K, and micronutrients) and soil pH. The dataset, consisting of 880 soil samples from Pamekasan, revealed an imbalance, with the high-fertility class accounting for only 39 samples. After data preprocessing, both models were evaluated. The Random Forest model achieved an overall accuracy of 90.34%, slightly outperforming XGBoost, which reached 88.64%. Random Forest demonstrated superior performance in detecting low-fertility land (recall 0.97) and medium-fertility land (precision 0.93, recall 0.88). For the high-fertility minority class, Random Forest showed better recall (0.60) than XGBoost (0.40), while maintaining perfect precision (1.00). The study concludes that Random Forest is the optimal model for classifying soil fertility in Pamekasan. These findings provide a basis for more precise, efficient, and sustainable fertilization recommendations, which are expected to help farmers optimize productivity and support the sustainability of the local agricultural ecosystem by reducing excessive fertilizer use.
Exploratory Data Analysis of Agricultural Commodity Prices Across Districts and Cities in East Java Tamam, Moh. Badri; Araujo Bernardo, Januario Freitas
Intelmatics Vol. 6 No. 1 (2026): January-June (In Progress)
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/v6i1.25460

Abstract

Descriptive statistics and visualization revealed significant variations in price distributions, with medium rice, premium rice, and dry milled paddy being the predominant commodities. Monthly trend analysis indicated a consistent upward movement in prices from 2020 to mid-2025. Regional comparisons specifically highlighted that, among all districts studied, Bondowoso had the highest average rice prices, Magetan consistently showed the lowest prices, and Malang City exhibited the greatest price volatility. The Random Forest Classifier achieved 73% accuracy in distinguishing districts based on commodity price patterns. Feature importance analysis singled out medium rice and premium rice as the most influential variables driving classification. These key findings clarify the specific pricing trends, regional disparities, and significant predictors identified in the study.
Co-Authors Adi Darma, Wawang Anwari Anwari . Anwari Anwari Aolia Ikhwanudin Aprilita, Yeni Nur Araujo Bernardo, Januario Freitas Arisca Dyana, Motik Bernardo, Januario Freitas Araujo Chafid, Nurul Ernawati, Tia Fathorrozi Ariyanto Fitriyah, Eka Hozairi Hozairi Hozairi Januario Freitas Araujo Bernardo Kholida MS*, S. Ida Kusrini Kusrini Kusuma, Suteja Wira Dana Kuzairi Maimon Sumo Muhammad Agus Muljanto Muhsi, Muhsi Qurrotul Aini RAJAGUKGUK, SOFIA Rofiuddin Rozi, Khairul Sagito, Redy Wahyan Santoso, Teguh Budi Suprianto Suprianto SUPRIATIN Supriatin Supriatin Supriatin Supriatin, Supriatin Walid, Miftahul Wawan Kurniawan Zulkifli, Ahmad