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All Journal Jurnal Ilmiah Rekayasa Pertanian dan Biosistem Journal of Agricultural and Biosystem Engineering Research
Muna, Mukhes Sri
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Agriculture, Biological Sciences & Forestry Control & Systems Engineering Energy Industrial & Manufacturing Engineering Mechanical Engineering

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Analisis Kebutuhan Alat dan Mesin Pertanian Padi di Desa Sokaraja Lor untuk Mewujudkan Pertanian Mekanis Jaya, Gigieh Henggar; Wiratmoko, Ardan; Hita, Muhammad Arga; Brillyansyah, Degita Fahmi; Muna, Mukhes Sri; Novitasari, Dian; Furqon, Furqon; Mustofa, Asna
Journal of Agricultural and Biosystem Engineering Research Vol 6 No 1 (2025): Journal of Agricultural and Biosystem Engineering Research: Regular Issue
Publisher : Program Studi Teknik Pertanian, Fakultas Pertanian, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jaber.2025.6.1.15875

Abstract

Pertanian tidak hanya menjadi industri penyedia sumber bahan pangan, tetapi juga pemegang peran sentral dalam berjalannya roda perekonomian di Indonesia sebagai penyedia lapangan pekerjaan. Di Indonesia kegiatan pertanian didominasi dengan budidaya tanaman padi yang merupakan tanaman penghasil beras sebagai sumber makanan pokok mayoritas masyarakat di Indonesia. Kebutuhan beras yang tinggi di Indonesia, perlu diimbangi dengan penerapan teknologi seperti mekanisasi. Desa Sokaraja Lor merupakan sebuah desa yang memiliki potensi pertanian yang tinggi dengan luasan lahan sawah selebar 101 Ha. Akan tetapi, Pemerintah Desa dan Kelompok Tani Desa Sokaraja Lor masih belum memiliki alat dan mesin pertanian untuk pengolahan tanah, penanaman, dan pemanenan. Adapun hasil analisa yang telah dilakukan menunjukkan kebutuhan alat dan mesin untuk pengolahan tanah adalah traktor roda dua kelas besar sebanyak 2 unit dan traktor roda empat kelas sedang sebanyak 5 unit. Untuk tahapan penanaman membutuhkan transplanter tipe dorong kelas B sebanyak 4 unit. Proses pemanenan memerlukan combine harvester kelas C sebanyak 1 unit.
Klasifikasi Kematangan Buah Kelapa Sawit Menggunakan Model Yolov8 Berbasis Deep Learning Muna, Mukhes Sri; Setiyo, Yohanes; Wirawan, I Putu Surya; Syarovy, Muhdan; Jaya, Gigieh Henggar
Journal of Agricultural and Biosystem Engineering Research Vol 6 No 1 (2025): Journal of Agricultural and Biosystem Engineering Research: Regular Issue
Publisher : Program Studi Teknik Pertanian, Fakultas Pertanian, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jaber.2025.6.1.15953

Abstract

Determining the ripeness level of oil palm fruit is a crucial aspect in enhancing the efficiency and quality of palm oil production. To date, most ripeness classification processes are still manually conducted, leading to inconsistencies and human error. This study aims to develop an oil palm fruit ripeness classification model using YOLOv8, a state-of-the-art deep learning architecture known for its excellence in computer vision tasks. The dataset consists of six ripeness classes, divided into training, validation, and testing sets sourced from the Roboflow platform. The training process involved five YOLOv8 sub-models with optimized parameter configurations. Evaluation was carried out using MAPE and confidence score metrics to measure prediction accuracy. The results showed that all sub-models successfully classified fruit ripeness with high accuracy, with YOLOv8l-cls achieving the lowest MAPE value of 0.01167. These, confirm that the YOLOv8-based approach is highly effective in supporting automated classification of oil palm fruit ripeness, offering faster, more accurate, and consistent results, and holds strong potential for widespread application in the plantation industry.
Analisis Produktivitas dan Kualitas Buah Stoberi var Sujarli (Rosalinda) Berdasarkan Model Budidaya dan Pengolahan Citra Digital Handayani Nofiyanti, Sri; Setiyo, Yohanes; Muna, Mukhes Sri; Wirawan, I Putu Surya; Yosika, Nur Ida Winni
Jurnal Ilmiah Rekayasa Pertanian dan Biosistem Vol 13 No 2 (2025): Jurnal Ilmiah Rekayasa Pertanian dan Biosistem
Publisher : Fakultas Teknologi Pangan & Agroindustri (Fatepa) Universitas Mataram dan Perhimpunan Teknik Pertanian (PERTETA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jrpb.v13i2.1187

Abstract

Strawberry (Fragaria sp.) is a high-value horticultural commodity with broad market potential, particularly in tropical highland areas such as Bedugul, Bali. However, its productivity and fruit quality are often constrained by climatic fluctuations and limited application of appropriate cultivation technologies. This study aimed to evaluate the productivity and fruit quality of Sujarli (Rosalinda) strawberry variety under four cultivation models: conventional open field, tunnel, fertigated open field, and greenhouse. In addition, a predictive model for Total Soluble Solids (TSS) content was developed using fruit color parameters obtained through digital image analysis. A total of 100 strawberry samples across five ripening stages were analyzed for biometrical characteristics (length, diameter, and weight), pH, and TSS. Image analysis was performed in two color spaces, namely RGB and HSV, and the corresponding color values were used as input variables in a multiple linear regression (MLR) model to predict TSS values. The results showed that the fertigated open field system produced strawberries with good physical and chemical quality, making it a feasible option for small-scale farmers. The MLR model based on HSV color space outperformed the RGB-based model, achieving R² values of 0.826 (training) and 0.775 (testing), with lower RMSE values as well. These findings support the use of digital color data as a non-destructive indicator for assessing the quality of strawberries during postharvest evaluation.
Co-Authors Asna Mustofa Brillyansyah, Degita Fahmi Dian Novitasari Furqon Furqon, Furqon Handayani Nofiyanti, Sri Henggar Jaya, Gigieh Hita, Muhammad Arga I Putu Surya Wirawan Muhdan Syarovy Wiratmoko, Ardan Yohanes Setiyo Yosika, Nur Ida Winni