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All Journal Jurnal Teknologi Industri Pertanian Teknotan: Jurnal Industri Teknologi Pertanian Jurnal AGROTEKNOLOGI Jurnal Keteknikan Pertanian Jurnal Teknologi Pertanian AGRIVITA, Journal of Agricultural Science agriTECH Jurnal Agroindustri E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal Penelitian Pertanian Terapan SAINS TANAH - Journal of Soil Science and Agroclimatology Jurnal Teknologi & Industri Hasil Pertanian Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal Agrotek Tropika Jurnal Teknologi Pertanian Andalas J-Dinamika: Jurnal Pengabdian Kepada Masyarakat Industri Inovatif : Jurnal Teknik Industri MIMBAR INTEGRITAS Rona Teknik Pertanian Jurnal Penelitian Sains dan Teknologi Indonesia
Siswoyo Soekarno
Jurusan Teknik Pertanian - Fakultas Teknologi Pertanian, Universitas Jember
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Analysis of rainfall erosivity factor (R) on prediction of erosion yield using USLE and RUSLE Model’s; A case study in Mayang Watershed, Jember Regency, Indonesia Andriyani, Idah; Indarto, Indarto; Soekarno, Siswoyo; Pradana, Masdharul Putra
SAINS TANAH - Journal of Soil Science and Agroclimatology Vol 21, No 1 (2024): June
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/stjssa.v21i1.63641

Abstract

The Rainfall erosivity has a relatively high effect on soil erosion, in addition to being very difficult to predict and control. The Universal Soil Loss Equation (USLE) and The Revised Universal Soil Loss Equation (RUSLE) model are commonly used to predict erosion yield in Indonesia. However, these models have several erosivity formulations that give different results. In this sense, identifying the sensitivity of different erosivity formulations in both models above is important. The aim of this study is to analyze soil erosion yield prediction influenced by the difference in erosivity equation on the same rainfall data used in the models while other parameters used are the same. The monthly rainfall and annual rainfall data were tested using the erosivity formulas. The (1) Bols and (2) Utomo equations were tested using monthly rainfall data, while the (3) Bols and (4) Hurni equations were tested using annual rainfall data. The results show that the prediction of soil erosion yields estimates using monthly rainfall data in both models have no significant differences. On the other hand, soil erosion estimates using annual rainfall data in the models have significant differences, whereas the USLE model estimation results in 63% erosion yield on low classification (0-15 ton ha-1 year-1). Meanwhile, the RUSLE model estimates only 59% erosion yield on low classifications. Another result is that the USLE model estimates lower erosion yield than the RUSLE model when the models use annual rainfall data, which may give significantly different recommendations for soil conservation in Indonesia, especially in reducing erosion yield at the Watershed level.
Grading Coffee Beans using Extraction of Shape-Based Features Coupled with Support Vector Machine Agus Dharmawan; Rudiati Evi Masithoh; Siswoyo Soekarno; Hanim Zuhrotul Amanah
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 15 No. 3 (2026): June 2026
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v15i3.895-906

Abstract

Evaluating coffee beans through a computer vision system (CVs) requires a large number of visual attributes to be extracted, but may affect prediction accuracy. Therefore, it is essential to reduce the large features to gain better prediction accuracy by generating new data that represents the most informative dimensions of the original data. Previous studies are limited to comparing different methods of feature extraction. The objective of this research was to explore the comparison of six feature extraction methods (PCA, EFA, LDA, SVD, ICA, and PLS) combined with support vector machine (SVM) as a supervised approach to predict three groups of coffee beans, namely long-berry, normal, and peaberry, for grading issues. SVM with three kernel functions (linear, RBF, and sigmoid) was used to construct a superior classification model. Data were acquired from coffee images processed to generate shape-based features. The results show that LDA provides a better visualization in separating sample classes according to the score plot with 2 variables obtained. The combination of SVM and LDA has a better recognition of coffee beans for grading, which is higher than that of other combinations. A combination of SVM-sigmoid with EFA gave mostly the worst recognition. Our findings proved that the investigation of feature extraction methods and SVM successfully achieve accurate results on grading coffee beans.
PENGELOLAAN PANEN DAN PASCAPANEN KOPI BERBASIS PENERAPAN GOOD AGRICULTURE PRACTICES DI KEBUN KOPI RAKYAT LERENG IJEN KABUPATEN BONDOWOSO Soni Sisbudi Harsono; Siswoyo Soekarno; Sudaryanto Sudaryanto
MIMBAR INTEGRITAS : Jurnal Pengabdian Vol 4 No 1 (2025): JANUARI 2025
Publisher : Biro Administrasi dan Akademik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36841/mimbarintegritas.v4i1.5694

Abstract

Penerapan Good Agricultural Practice (GAP) pada pengelolaan panen dan pasca panen kopi sangat penting untuk memastikan kualitas kopi yang optimal dan menjaga keberlanjutan produksi. GAP pada tahap pasca panen berfokus pada serangkaian praktik yang memastikan hasil panen kopi diproses dengan cara yang menjaga kualitas, kebersihan, serta keamanan produk kopi. Tujuan dari pelaksanaan PKM ini adalah memberikan pembimbingan dan pelatihan kepada petani kopi di Lereng Ijen Kabupaten Bondowoso agar dapat meningkatkan kinerja dalam pengelolaan dan pasca panen kopi yang sangat vital untuk memperbaiki dan meningkatkan kualias kopi yang merupakan andalan petani kopi di lereng Ijen ini. 1 Tahap Pertama. Pada tahap pertama ini dilakukan beberapa kegiatan diantaranya, a) observasi, b) kordinasi, dan c) kesepakatan dan kesepamaham antara tim pelaksana dengan petani. Dalam implementasinya, observasi merupakan kegiatan paling awal dan mendasar untuk mengumpulkan data serta mendeskripsikan permasalahan yang ada di lapangan [6]. 2) Tahap II adalah Kegiatan sosialisasi progam pengabdian kepada amasyarakat dan penerapan Good Agriculture Practice on Coffee (GAP on Coffee) pada pascapanen kopi dilaksanakan pada tahap ini. Hasil PKM ini adalah pemanenan yang selektif, pemrosesan yang teliti dan benar, pengeringan yang baik dan proses penyangraian serta pembubukan kopi yang sesuai SNI dengan kemasan yang aman dan higienis.
Co-Authors Abda Abda Adindra, Plasida Geustin Aghata, Ola Riska Aprilia Intan Agus Dharmawan Agus Dharmawan Ahmad Hudi Arif Ajeng Afriska Lailatul Fajriyah Alfarisy, Fariz Kustiawan Andi Eko Wiyono, Andi Eko Andy Eko Wiyono Ankardiansyah Pandu Pradana Aprilia Dila Wardiningrum Apriza Fatkur Roziqin Aristanti, Fransiska Candra Asmak Afriliana Bambang Marhaenanto Bambang Marhaenanto Bayu Taruna Widjaja Putra Dewi Melani Dian Purbasari Dian Purbasari Dwi Wahyu Widarman Edy Suharyanto Eko Wiyono, Andi Elida Novita Elok Sri Utami Ernanda, Heru Eva Yulia Windiari Fajriyah, Ajeng Afriska Lailatul Farchan Mushaf Al Ramadhani Fathan Edy Purwanto Fina Firdiyanti Fiqih Faresa Firdaus Firdiyanti, Fina Firmansyah, Ilham Firmanto, Hendy Gray Miller Damanik Hamid Ahmad Hanim Zuhrotul Amanah Hasana, Siti Hendy Firmanto Herlina Herlina . Herlina Herlina Herlina Herlina Hernanto, Setyawan Dwi Hervian Rahardiansyah Hoesain, Mohammad Ida Bagus Suryaningrat Idah Andriyani Ilham Firmansyah Indarto Indarto Indarto Indarto Iwan Taruna Khoirulloh, Deffa Lestari, Ning Puji Luh Putu Ratna Sundari M. Yogi Riyantama Isjoni Manik Nur Hidayati Melani, Dewi Muhammad Nasir Afandi Ning Puji Lestari Nurhayati Nurhayati Pradana, Masdharul Putra Prihani, Suwita Tri Rizky Akthur Alamsyah Rudiati Evi Masithoh Rufiani Nadzirah Rusdianto, Andrew Setiawan Sakli Petiet Isbi Kurniawan Septian, Taufiq Dwi Setyawan Dwi Hernanto Setyo Harri Silvia, Halimatus Siswi janto Siti Nur Shaidah Soni Sisbudi Harsono Soni Sisbudi Harsono Soni Sisbudi Harsono, Soni Sisbudi Sri Mulato Sudaryanto Sudaryanto Sukrisno Widyoto Sukrisno Widyotomo Sulistyani Sulistyani Sutarsi, Sutarsi Tampatty, Jovansa Tantri Sepriska U Tasliman, Tasliman Triana Lindriati Windiari, Eva Yulia Yuli Wibowo