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Sustainable Production-Inventory Model with Multi-Material, Quality Degradation, and Probabilistic Demand: From Bibliometric Analysis to A Robust Model Dana Marsetiya Utama; Imam Santoso; Yusuf Hendrawan; Wike A. P. Dania
Indonesian Journal of Science and Technology Vol 8, No 2 (2023): (ONLINE FIRST) IJOST: September 2023
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v8i2.54056

An adequate sustainable production inventory model is expected to represent complex real-life cases involving fuel, emissions, and electricity costs as well as multi-materials, quality degradation, and probabilistic demand. Therefore, this study was conducted to develop this kind of model to determine the number of raw material shipments (), production cycle time (), and the number of finished goods delivered (n) to maximize the Expected Total Profit (ETP). The proposed model is based on a bibliometric literature analysis of the sustainable production-inventory problem which is visualized using the VOSviewer. Moreover, a sophisticated Harris-Hawks Optimization (HHO) algorithm was proposed to solve the problems identified in the sustainable production inventory model optimization. It is also important to note that three numerical cases were provided to evaluate the performance of the algorithm. The findings showed that the suggested HHO method outperforms the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in maximizing ETP and this means it is better for ETP optimization. It was also discovered from the sensitivity analysis that an increase in the rate of quality degradation (k) led to a reduction in both the ETP and T.

DETERMINATION OF RISK MINIMIZATION STRATEGY FOR HERBAL DRINK PRODUCTION WITH GMP APPROACH USING SCORING AND AHP Ratining Indah Wardani; Imam Santoso; Riska Septifani
Jurnal Teknologi Pertanian 6th International Conference on Green Agro-industry and Bioeconomy (ICGAB) July 2022 - Special Issue
Publisher : Fakultas Teknologi Pertanian Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (268.902 KB)

Herbal drinks such as herbs have become part of the culture in Indonesia. The herbal plants processed into herbal drinks include bilimbi fruit (Averrhoa bilimbi L.) and secang (Caesalpinia sappan L.). This study aims to determine the risk minimization strategy in producing herbal drinks in CV XYZ by analyzing 14 aspects of Good Manufacturing Practices (GMP) using a scoring form and the Analytical Hierarchy Process (AHP) method. The scope of GMP in this study orients to how to produce good processed food. Determination of risk minimization strategy using the Analytical Hierarchy Process (AHP) method. The assessment results in applying GMP in CV XYZ using scoring calculation gotten three aspects with the highest deviation, “the sufficient qualify category", i. e. the building aspect (78.39%), storing (78.47%), and controlling (78.65%). These results as the base for arranging the risk minimization strategy with some criteria and alternatives using AHP calculation. The priority criteria for risk minimization strategies are the effectiveness level (0.608), the easiness of applying (0.313), and cost (0.079). Then, three priorities of alternative risk minimization for CV XYZ based on the global weight are the repairing of ventilation design (0.323) by adding ventilation in the production room, screens for dust filters that can be easily removed, final product storage separation (0.228) by placing materials or products that have a strong odor and have the potential to affect the final product in a separate room, making SOPs for the production process (0.209).

MAIN TRENDS IN THE DEVELOPMENT OF BIOECONOMIC STRATEGIES IN AGROINDUSTRY: A SYSTEMATIC LITERATURE REVIEW Muflihah Ramadhia; Imam Santoso
Jurnal Ekonomi Vol. 12 No. 3 (2023): Jurnal Ekonomi, 2023, September
Publisher : SEAN Institute

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Bioeconomics is an emerging concept and has not been given a generally accepted definition. Bioeconomic strategy tries to consider every aspect of this emerging concept from different perspectives depending on the country, region, or organization that publishes it. Therefore, each strategy has its advantages depending on the economic, geomorphological, social, environmental, and technological conditions of each country. In this review, attempts are made to address key trend areas of bioeconomic strategies through a systematic literature review. PRISMA analysis is used to review the literature on key trend areas of bioeconomic strategies. Review articles address this topic in two major scientific literature databases, namely Scopus and AgEcon. Using a repeatable search process to identify relevant studies in the literature, only 68 publications that met the eligibility criteria were included in the review. The results showed that the movement of the main trends of the Bioeconomic Strategy in agro-industry 2013-2022 was observed as well as the economic and technological development of each country to show its superiority. The transition to a successful bioeconomy model requires the participation of the whole society because a sustainable society as a whole requires sustainable and environmentally responsible solutions. The study concludes that management with global coordination and training for stakeholders is necessary for the successful implementation of bioeconomic strategies in agro-industry.

EKSTRAKSI NANOKALSIUM TULANG IKAN TENGGIRI (Scomberomorus sp.) DENGAN ULTRASOUND ASSISTED EXTRACTION Muhammad Usman Sihab; Dodyk Pranowo; Imam Santoso
Jurnal Teknologi Pertanian Vol. 24 No. 2 (2023)
Publisher : Fakultas Teknologi Pertanian Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jtp.2023.024.02.7

Kalsium merupakan mineral esensial yang memiliki peranan penting di dalam tubuh untuk pembentukan tulang. Kalsium umumnya dikonsumsi dalam bentuk mikro kalsium yang menyebabkan penyerapan oleh tubuh hanya 50% sehingga sering menyebabkan defisiensi. Sumber kalsium yang aman digunakan umumnya dari tulang ikan, yang merupakan limbah tidak termanfaatkan, salah satunya adalah tulang ikan tenggiri. Pada penelitian ini digunakan ultrasound-assisted extraction (UAE) untuk mengekstrak nanokalsium. Kalsium berukuran nano lebih mudah diserap oleh tubuh dan dapat terapsorbsi secara cepat dan sempurna. Tujuan penelitian ini adalah untuk menganalisis interaksi waktu eksitasi dan amplitudo terhadap karakteristik nanokalsium yang dihasilkan. Hasil penelitian menunjukkan solusi terbaik untuk memproduksi nanokalsium dengan waktu eksitasi 100,04 menit dan amplitudo 75,00% dengan prediksi nilai respons yakni rendemen 47,49%; derajat putih 85,47%; dan kadar kalsium 47,62%. Distribusi ukuran partikel nanokalsium dengan posisi pengukuran 4,65mm dari dinding sel memiliki rata-rata ukuran 142,3nm dan PdI 0,226. Hasil analisis XRD menunjukkan puncak utama muncul pada sudut 2θ = 31,73. Selain itu, beberapa puncak muncul di 25,90; 28,99; 32,99; 34,18; 39,79; 43,97; 46,79 dan 49,62. Berdasarkan persamaan scherrer diperoleh ukuran rata-rata kristal 26,16 nm dan derajat kristalinitas 83,35%. Hasil analisis gugus fungsi yang terindikasi pada nanokalsium diantaranya adalah gugus fosfat (PO43-), karbonat (CO32-) dan gugus hidroksil (OH).

Analisis rantai nilai dalam aspek lingkungan dan ekonomi menggunakan VCOR pada petani kopi di Malang Imam Santoso; Miftahus Sa'adah; Izzum Wafi'uddin; Naila Maulidina Lu'ayya; Dodyk Pranowo; Retno Astuti
AGROINTEK Vol 19, No 1 (2025)
Publisher : Agroindustrial Technology, University of Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/agrointek.v19i1.23430

The coffee agroindustry in Indonesia, particularly in Malang Raya, has undergone expansion through the increased development of coffee processing industries, including waste and emissions. Various factors, including farming practices, land use, waste management, and the utilization of by-products influence the emission levels in the supply chain. A value chain analysis in supply chain management is essential to support sustainable coffee agroindustry. The complexity of the coffee value chain involves multiple stakeholders, including input providers, producers, traders, cooperatives, and exporters, emphasizing the intricate nature of the coffee chain and the need for coordinated efforts to ensure quality and sustainability. This research aims to identify emission sources in the supply chain and determine the economic impact of coffee production at the farmer level. The value chain operations reference is the method used for measuring the value chain. The calculation results indicate that the carbon emission footprint in the supply chain activities at the farmer level amounts to 22,734 kg CO2 with a unit cost of 0.75 €/kg. These values suggest that activities in the coffee value chain at the farmer level are still not environmentally friendly (intolerable region). Suggested approaches for enhancing the value chain for coffee farmers in Karangploso encompass the installation of a smart GPS system in vehicles for route optimization and fuel efficiency, and using organic fertilizers instead of chemical fertilizers to prevent water pollution, along with the adoption of an organic farming system to enhance the economic value of the harvest. The findings of this study are expected to be a reference for research on the value chain in coffee supply chain activities, and contribute to the enrichment of information related to the VCOR model

Analisis rantai nilai dalam aspek lingkungan dan ekonomi menggunakan VCOR pada petani kopi di Malang Imam Santoso; Miftahus Sa'adah; Izzum Wafi'uddin; Naila Maulidina Lu'ayya; Dodyk Pranowo; Retno Astuti
AGROINTEK Vol 19, No 1 (2025)
Publisher : Agroindustrial Technology, University of Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/agrointek.v19i1.23430

The coffee agroindustry in Indonesia, particularly in Malang Raya, has undergone expansion through the increased development of coffee processing industries, including waste and emissions. Various factors, including farming practices, land use, waste management, and the utilization of by-products influence the emission levels in the supply chain. A value chain analysis in supply chain management is essential to support sustainable coffee agroindustry. The complexity of the coffee value chain involves multiple stakeholders, including input providers, producers, traders, cooperatives, and exporters, emphasizing the intricate nature of the coffee chain and the need for coordinated efforts to ensure quality and sustainability. This research aims to identify emission sources in the supply chain and determine the economic impact of coffee production at the farmer level. The value chain operations reference is the method used for measuring the value chain. The calculation results indicate that the carbon emission footprint in the supply chain activities at the farmer level amounts to 22,734 kg CO2 with a unit cost of 0.75 €/kg. These values suggest that activities in the coffee value chain at the farmer level are still not environmentally friendly (intolerable region). Suggested approaches for enhancing the value chain for coffee farmers in Karangploso encompass the installation of a smart GPS system in vehicles for route optimization and fuel efficiency, and using organic fertilizers instead of chemical fertilizers to prevent water pollution, along with the adoption of an organic farming system to enhance the economic value of the harvest. The findings of this study are expected to be a reference for research on the value chain in coffee supply chain activities, and contribute to the enrichment of information related to the VCOR model

Artificial intelligence-based risk assessment in agro-industry using supervised neural networks Imam Santoso; Izzum Wafi'uddin; Naila Maulidina Lu'ayya; Annisa'u Choirun; Siti Asmaul Mustaniroh; Dodyk Pranowo; Ainur Rofiq
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i3.pp2260-2268

The coffee supply chain involves high production volumes, complex multi actor interactions, and increasing sustainability requirements, yet remains highly vulnerable to risks dimension. This study aims to develop and evaluate a decision-support framework that improves the accuracy and consistency of sustainability risk classification in the coffee supply chain. The proposed framework integrates failure mode and effect analysis (FMEA) with a supervised artificial neural network (ANN) using backpropagation (BP) to enable data-driven and adaptive risk assessment. Empirical data was collected from 55 respondents, resulting in the identification of 35 supply chain risk factors. These data were used to train and validate an ANN-based classification model implemented in a Python environment, with standard preprocessing and stratified data partitioning to ensure robustness. The ANN classified risks into five categories using supervised learning. The results demonstrate strong predictive performance, achieving overall accuracy of 98.97%, with precision, recall, and F1-scores exceeding 96.8% across all risk classes. Confusion matrix analysis confirms reliable generalization and minimal misclassification. The findings indicate that integrating FMEA with ANN-BP significantly enhances risk classification compared to conventional qualitative approaches. The proposed framework provides a scalable and reliable decision-support tool for dynamic risk scoring, supporting enhancement of sustainable practices in agro-industrial coffee supply chains.

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