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All Journal Jambi Medical Journal : Jurnal Kedokteran dan Kesehatan Jurnal Kesehatan Masyarakat IPTEK The Journal for Technology and Science Jurnal Riset Kesehatan Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Insights in Public Health Journal Inovasi Jurnal Pengabdian Masyarakat (IJPM) Branding: Jurnal Manajemen & Bisnis PENITI BANGSA (Pemanfaatan Ilmu Pengetahuan dan Teknologi bagi Masyarakat) Jurnal Kesehatan Masyarakat
Radi Radi
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Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Health Professions Languange, Linguistic, Communication & Media Medicine & Pharmacology Public Health Social Sciences Other

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Classification of Roasting Level of Coffee Beans Using Convolutional Neural Network with MobileNet Architecture for Android Implementation Pakaya, Isran Mohamad; Radi, Radi; Purwantana, Bambang
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 3 (2024): September 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i3.924-932

Abstract

The roasting process has a significant impact on the aroma profile and taste of coffee making it an essential stage in the coffee processing. Currently, the classification of coffee bean roasting levels still relies on subjective human visual assessment, which can lead to errors due to fatigue or negligence. To overcome this problem, a classification system was developed using computer vision technology with a deep learning approach. The present study designed a coffee bean roasting level classification system based on image analysis integrated within an Android application. The Convolutional Neural Network (CNN) model with the MobileNet architecture was used to identify and classify coffee beans based on their roasting level. Two CNN models, namely CNN Alpha and CNN Beta were used in this study. The dataset included 1.600 coffee bean images, with 1.200 images used to train the model and 400 images used to test the accuracy. In this experiment, the input image had an optimal size of 70x70 pixels, a learning rate of 0.0001, and 100 epochs for both models. The model training and testing results in the highest accuracy of 98-88% in 6.40-0.0012 minutes.The application test results obtained 93.55% accuracy, 97.06% precision, and 96.67% recall. These results indicate that this model and application function optimally in classifying coffee bean roasting levels accurately. Overall, this study reveals the potential of integrating CNN with the MobileNet architecture into an Android-based application to change the way of roasting level classification, as well as to improve efficiency and accuracy. Keywords: Coffee, Roasting, Convolutional Neural Network, MobileNet, Android.
Potential Analysis of Biomass Briquettes from Sugarcane Milling Waste for Boiler and Generator Turbines Stations Hajad, Makbul; Syahputra, Muhammad Hafidz; Yulianta, Raditya; Radi, Radi; Markumningsih, Sri; Purwantana, Bambang
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 4 (2024): December 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i4.1226-1236

Abstract

The decrease in sugar productivity was due to insufficient process of the sugar production process such as the low efficiency of boiler machine input energy. This study aims to analyze the potential use of Bagasse Briquetting Fuel (BBF) made from sugarcane milling waste at PT Madubaru as an attempt to obtain the optimal efficiency of boiler machine. Analysis of the effect of the adhesive concentration on the BBF quality was carried out to determine the optimal composition of the use of adhesive materials. Economic analysis was also conducted to determine the economic potential of BBF development. The analysis revealed that the BBF from Sugarcane milling waste has Calorific Value of 17,367-19,497 KJ/kg and density of 0.740-0.915 g/cm3. BBF with an adhesive variation of 1.25% is the BBF with the highest efficiency because it meets the needs of boiler fuel with the least amount of 100.8 tons/day for the operation of 1 boiler machine. The development of BBF from sugarcane milling waste has a selling value of Rp1.390.5,-/kg much lower than the existing biomass fuels found in the market. Keywords: Bagasse briquetting fuel; Boiler machine; Energy efficiency; Renewable energy; Sugarcane milling waste.
Literature Review: Risk Factors Affecting The Incidence Of Soil-Transmitted Helminths (Sth) Infection In Adults Rachmawati, Farras Arlinda; Radi, Radi; Rejeki, Dwi Sarwani Sri; Wijayanti, Siwi Pramatama Mars; Wijayanti, Mars
Jurnal Riset Kesehatan Vol 14 No 1 (2025): MEI 2025
Publisher : Poltekkes Kemenkes Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31983/jrk.v14i1.12367

Abstract

Background: Soil-transmitted helminths (STH) infection is still a problem in many countries. Studies on risk factors for soil-transmitted helminths (STH) infection are still more focused on children, while studies in adults are limited. This study aims to summarize risk factors for soil-transmitted helminths (STH) infection in adults. Method: This study used a literature review method by collecting journals from Google Scholar, PubMed, and ScienceDirect. Data was collected using the keywords risk factor, soil-transmitted helmet, and adult.  The article to be reviewed is a research conducted in 2019 - 2023. Result: The results of the article search were obtained as many as 861 articles which were then selected using inclusion and exclusion criteria so that as many as 10 articles were received for review. The results of the review of the entire article found that the risk factors for soil-transmitted helminths (STH) infection in adults are individual factors (Education level, gender, age, and type of occupation ), socioeconomic (Community ethnicity, area of residence, and population density), and Personal hygiene (habit of washing food before consumption, nail hygiene, interaction with animals, waste or dirt removal, handwashing habit, soil-eating habit, and boiling drinking water)). Conclusion: Risk factors for soil-transmitted helminths (STH) are individual, socioeconomic, and personal hygiene
Co-Authors Bambang Purwantana Devi Octaviana Didik Purwadi Dwi Sarwani Sri Rejeki Eri Wahyuningsih Firdaus, Dwiyan Maharani Mutiara Fitriani, Aprilya Gymnastiar, Iman Ahmad Hajad, Makbul Hapsari, Umi Lilik Sutiarso Marheriyanto, Marheriyanto Mashudi Mashudi Mauridhi Hery Purnomo Muhammad Rivai Nurhamzah, Nurhamzah Pakaya, Isran Mohamad Rachmawati, Farras Rachmawati, Farras Arlinda Saldan, Andi Muh. SIWI PRAMATAMA MARS WIJAYANTI Sri Markumningsih, Sri Syahputra, Muhammad Hafidz Triwitono, Priyanto Wawan Saputra Wijayanti, Mars Yatapya, Susina Yulianta, Raditya