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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.
Classification of single origin Indonesian coffee beans using convolutional neural network Rifai, Achmad Pratama; Sari, Wangi Pandan; Rabbani, Haidar; Safitri, Tari Hardiani; Hajad, Makbul; Sutoyo, Edi; Nguyen, Huu-Tho
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i6.pp5140-5156

Abstract

This research aims to develop a coffee bean type detection model using convolutional neural networks (CNN), leveraging a dataset of 14,525 images from 116 types of Indonesian coffee beans. Pre-processing steps including resizing, rescaling, and augmentation were applied to improve the dataset quality. The dataset was split into training, validation, and testing sets with proportions of 80%, 10%, and 10%, respectively. Two model development approaches were used: transfer learning with Inception V3 in two scenarios and a model built from scratch. The transfer learning Inception V3 model in scenario 1 achieved the best performance, with a test accuracy of 0.87 and optimal evaluation metrics across precision, recall, and F1-score. This model was fine-tuned using pretrained weights, allowing it to adapt effectively to the coffee bean dataset. The results highlight that transfer learning, especially with Inception V3, provides a robust method for classifying coffee beans, offering potential applications in the coffee industry for improving classification efficiency and accuracy. The study demonstrates how deep learning can enhance the objectivity and precision of coffee bean classification, contributing to greater consistency in product sorting and quality assessment.
Penerapan Biodigester Untuk Pengolahan Air Limbah Industri Tapioka Berbasis Pemberdayaan Masyarakat Berkelanjutan di Rumah Produksi Pangan Selopamioro, Yogyakarta Sutiarso, Lilik; Karyadi, Joko Nugroho Wahyu; Masithoh, Rudiati Evi; Ngadisih, Ngadisih; Radi, Radi; Nugroho, Andri Prima; Hajad, Makbul; Zahra, Aryanis Mutia; Lestari, Prieskarinda
Jurnal Pusat Inovasi Masyarakat Vol. 5 No. 1 (2023): April 2023
Publisher : Direktorat Pengembangan Masyarakat Agromaritim, Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jpim.5.1.43-60

Abstract

Singkong merupakan salah satu komoditas unggulan di Desa Selopamioro, Kecamatan Imogiri, Kabupaten Bantul, Daerah Istimewa Yogyakarta. Produktivitas singkong di Desa Selopamioro cukup tinggi mencapai 2,75 ton/ha dengan luas total lahan 415 ha. Namun, potensi besar komoditas singkong tersebut masih menghadapi berbagai tantangan dari sektor petani, produksi, kualitas, rendahnya harga jual, hingga terbatasnya akses pemasaran. Pengolahan singkong menjadi tepung singkong termodifikasi (modified cassava flour, mocaf) dan olahan pangannya merupakan inovasi yang telah diterapkan di rumah produksi pangan (RPP) Selopamioro untuk meningkatkan nilai tambah singkong dan diversifikasi produknya. RPP Selopamioro juga dikelola bersama oleh kelompok petani. Namun, proses pembuatan mocaf menghasilkan air limbah sehingga menyebabkan permasalahan bau tidak sedap di masyarakat dan mencemari lingkungan karena belum diolah secara tepat. Air limbah mocaf bersifat asam dan tinggi kandungan bahan organik. Kegiatan pemberdayaan masyarakat ini bertujuan untuk mengatasi permasalahan bau akibat air limbah mocaf di masyarakat, penerapan biodigester sebagai teknologi pengolahan limbah berkelanjutan, menjadikan RPP Selopamioro sebagai sentra transfer pengetahuan pengolahan pangan berwawasan lingkungan, implementasi model pemberdayaan masyarakat berkelanjutan. Kegiatan dilaksanakan pada Juli – September 2022 dengan monitoring berkala. Implementasi biodigester mampu mengolah air limbah mocaf dengan persentase penyisihan BOD, COD, TDS, sianida, total amonia masing-masing berkisar 97,47; 96,53; 12,94; 93,75; 97,17%, dan meningkatkan DO hingga 614,29%. Hal ini sekaligus menyelesaikan permasalahan bau tidak sedap karena air limbah mocaf sudah terolah dengan tepat dan tidak ada lagi keluhan dari masyarakat. Hasil pelaksanaan kegiatan juga telah mampu mengimplementasikan model pemberdayaan masyarakat berkelanjutan dan mewujudkan sentra pengolahan produk pangan lokal berwawasan lingkungan.