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All Journal Jurnal Teknologi Industri Pertanian Journal of Informatics and Advanced Computing
Taufik Djatna
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Agriculture, Biological Sciences & Forestry Computer Science & IT Engineering Industrial & Manufacturing Engineering

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DATA MINING DENGAN ALGORITMA DYNAMICSOME UNTUK PENENTUAN PENGIRIMAN DAN STOK YANG BELUM DI KIRIM PUPUK SUBSIDI Rini Prasetyani; Taufik Djatna
Journal of Informatics and Advanced Computing (JIAC) Vol 3 No 1 (2022): Journal of Informatics and Advanced Computing
Publisher : Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/jiac.v3i1.3944

Abstract

Data Mining is a new technology that is very useful to help companies find very important information from their data warehouses. Some data mining applications focus on prediction, they predict what will happen in a new situation from data that describes what happened in the past. In order to find out how many tons of fertilizer have been sent and how many have not been sent by the subsidized fertilizer factory appointed by the government. can be done by using analytical techniques, namely the analysis of consumer buying habits. Detection of fertilizers that are often purchased together is done using association rules. In this study, an a priori algorithm will be used to determine the association rules for buying fertilizer. So in solving these problems, the DynamicSome Algorithm method is used, which is a modification of the Apriori algorithm which will search for frequent itemsets from transaction data. Frequent itemset is a pair of items found in transaction data. In addition, the DynamicSome algorithm is also used to analyze the relationship between different items in a large set of items, this aims to see the relationship and attachment between these items, from the calculation results obtained in the 2016 tax year there are still 5 districts that have not been sent and in 2017 still 3 districts have not been sent.
RISK MANAGEMENT MODEL FOR RAW MATERIAL PROCUREMENT AND PRODUCTION PLANNING IN THE COFFEE AGROINDUSTRY: A CASE STUDY IN KALIBARU, BANYUWANGI Khotijah; Taufik Djatna; Marimin
Jurnal Teknologi Industri Pertanian Vol. 35 No. 2 (2025): Jurnal Teknologi Industri Pertanian
Publisher : Department of Agroindustrial Technology, Bogor Agricultural University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24961/j.tek.ind.pert.2025.35.2.107

Abstract

The coffee agroindustry encounters significant risks due to its intricate business processes and the involvement of multiple stakeholders. These risks, particularly in raw material procurement and production planning, threaten business sustainability and include inconsistent raw material quality and quantity, fluctuating prices, limited resources, and inefficiencies in decision-making. This study analysed business processes, identifies risks, and develops a risk mitigation model for the coffee agroindustry in Kalibaru, Banyuwangi. Business process analysis employed descriptive methods focusing on supply chain mechanisms and drivers, complemented by supply chain management metrics. Risk management utilized the House of Risk (HOR) Phase 1 and 2 framework. Results revealed a refined business process model emphasizing efficiency and integration, alongside 20 risk events and 20 risk sources in both procurement, and production planning. Eleven priority risk sources were identified for procurement, and ten for production, forming the basis for targeted mitigation strategies. Key mitigation actions include training farmers in Good Agricultural Practices (GAP), partnering with research institutions for procurement and implementing preventive maintenance of processing equipment for production. These strategies enhance resource management and industry competitiveness. Keywords: business process, coffee agroindustry, risk mitigation, procurement planning, production planning 
Co-Authors Khotijah Marimin , Rini Prasetyani