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All Journal Jurnal Teknologi Pertanian ULIN: Jurnal Hutan Tropis JSIKTI (Jurnal Sistem Informasi dan Komputer Terapan Indonesia)
Rudito Rudito
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Agriculture, Biological Sciences & Forestry Computer Science & IT Environmental Science

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Effect of Gelatine and Citric Acid in the Glycerol Containing Edible Coating Used For Storage of Tomato Rudito, Rudito
Jurnal Teknologi Pertanian Vol 6, No 1 (2005)
Publisher : Fakultas Teknologi Pertanian Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (137.679 KB)

Abstract

A fresh is perishable mainly due its high respiration rate. This research was conducted to examine the use of gelatine and citric acid in the glycerol containing edible coating to reduce the rate of deterioration of tomatoes during storage at room temperature. The use of edible coating is expected to be able to substitute a low temperature storage which is more expensive. The respective concentrations evaluated were 10%, 12% and 14% for gelatine and 0,5%, 0,7% and 0,9% for citric acid. The experiment was run in triplicates employing a factorial completely Randomized Block Design using a breaker ripe stadium tomatoes of Intan variety grown in Malang regions. The treated tomatoes were stored at room temperature until a red ripe stadium was achieved. The results indicated that all the 9 treated samples were able to reach a red ripe stadium with some variations of quality after 15 days of storage. In general, the treated samples show a higher rate of respiration and higher level of vitamin C, but were firmer in texture and a lower level of weight lost than the ones of control. It was found that the use of 14% (w/v) gelatine and 0,9% (w/v) citric acid in a combination with 5% glycerol is the most effective to use as an edible coating for tomatoes stored at room temperature (26-29oC). The lost of the above-mentioned quality attributes is still minim after 15 days storage.   Key Words: Tomatoes, Edible coating, Respiration
Potensi pemanfaatan tumbuhan invasif daun sacha inchi (Plukenetia volubilis) sebagai antioksidan Sari, Nur Maulida; Aryani, Farida; Wartomo, Wartomo; Paurru, Periani; Lumbanraja, Gabriel Permadi; Astuti, Reni Puji; Rudito, Rudito
ULIN: Jurnal Hutan Tropis Vol 8, No 1 (2024)
Publisher : Fakultas Kehutanan Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32522/ujht.v8i1.13203

Abstract

Aktivitas antioksidan dan antibakteri pada jenis tumbuhan invasif berpotensi sebagai obat telah diidentifikasi. Tumbuhan yang digunakan adalah bagian daun tumbuhan sacha inchi (Plukenetia volubilis). Tumbuhan diketahui memiliki kandungan antioksidan dan antibakteri yang diketahui aman dikonsumsi oleh manusia. Masyarakat memiliki kecenderungan memanfaatkan tumbuhan sebagai alternatif pengobatan alami. Penelitian ini bertujuan untuk mendapatkan informasi kandungan kimia tumbuhan serta mengetahui potensi antioksidan pada ekstrak etanol daun sacha inchi (Plukenetia volubilis). Analisis fitokimia dilakukan dengan menggunakan metode uji kualitatif mengacu pada Harborne dan Kokate. Pengujian aktivitas antioksidan dilakukan dengan menggunakan metode uji dekolorisasi radikal bebas DPPH. Hasil analisis fitokimia menunjukkan ekstrak etanol daun sacha inchi (Plukenetia volubilis) mengandung alkaloid, flavonoid, triterpenoid, tanin dan saponin. Aktivitas antioksidan ekstrak etanol daun sacha inchi (Plukenetia volubilis) menunjukkan kemampuan menghambat radikal bebas DPPH sebesar 84 % pada konsentrasi 100 ppm. Hasil penelitian ini menunjukkan bahwa ekstrak etanol daun sacha inchi (Plukenetia volubilis) memiliki kandungan antioksidan alami dan berpotensi untuk dikembangkan lebih lanjut serta memberikan informasi ilmiah sebagai dasar penggunaan tumbuhan sebagai antioksidan alami.
Support Vector Machine for Classifying Prostate Cancer Data B, Muslimin; Rachmadani, Budi; Rudito, Rudito
Jurnal Sistem Informasi dan Komputer Terapan Indonesia (JSIKTI) Vol 7 No 3 (2025): March
Publisher : INFOTEKS (Information Technology, Computer and Sciences)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33173/jsikti.205

Abstract

Prostate cancer is one of the most prevalent cancers among men worldwide, making early detection and accurate classification essential for improving patient outcomes. This study investigates the application of Support Vector Machine (SVM) models for classifying prostate cancer using clinical and demographic data. Features such as prostate-specific antigen (PSA) levels, Gleason scores, tumor stage, and patient age were utilized to train and evaluate the model. Comprehensive preprocessing techniques, including handling missing values, feature normalization, and addressing class imbalance with the Synthetic Minority Oversampling Technique (SMOTE), were employed to ensure robust model performance. The SVM model, optimized with a radial basis function (RBF) kernel, achieved an accuracy of 94.2%, with precision, recall, and F1-scores indicating reliable classification of both cancerous and non-cancerous cases. However, the results highlight challenges with the minority class, emphasizing the need for better handling of imbalanced datasets. Explainability techniques such as SHAP (Shapley Additive Explanations) were integrated to provide interpretable insights into the model’s predictions, with PSA levels and Gleason scores identified as the most influential features. This research demonstrates the potential of SVM in prostate cancer classification, providing a foundation for integrating machine learning models into clinical workflows for improved diagnostic precision and patient care.
Co-Authors Astuti, Reni Puji Farida Aryani Lumbanraja, Gabriel Permadi Muslimin B, Muslimin Paurru, Periani Rachmadani, Budi Sari, Nur Maulida Wartomo, Wartomo