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Journal : Jurnal Ilmiah Teknik Industri

MODEL PENENTUAN JUMLAH PESANAN PADA AKTIFITAS SUPPLY CHAIN TELUR AYAM MENGGUNAKAN FUZZY LOGIC Santosa, Sesar Husen; Hidayat, Agung Prayudha
Jurnal Ilmiah Teknik Industri Vol. 18, No. 2, Desember 2019
Publisher : Muhammadiyah University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v18i2.8486

Abstract

This study aims to present a fuzzy logic approach in the modeling of optimal order quantities of chicken eggs to suppliers. Determination of the number of egg orders using fuzzy logic by considering the condition of supply and demand so that the number of eggs ordered by Agent eggs is optimal so that the amount of stock in the warehouse is reduced. The variables used in developing the fuzzy set model are the price of eggs/crates, the composition of the weight of eggs in the crates, and the amount of stock of eggs in the warehouse at the time of ordering. The membership set for egg ordering uses the Triangular and Trapezoidal membership functions. The fuzzy set model produced in this study can be used as a tool for decision making in determining the optimal number of egg orders to suppliers.
FUZZY LOGIC APPROACH TO DETERMINE THE OPTIMUM NUGGET PRODUCTION CAPACITY Santosa, Sesar Husen; Sulaeman, Suhendar; Hidayat, Agung Prayudha; Ardani, Ilham
Jurnal Ilmiah Teknik Industri Vol. 19, No. 1, June 2020
Publisher : Muhammadiyah University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v19i1.10295

Abstract

This research aimed to present the Fuzzy approach in determining the optimal production capacity of the Nugget Production. The Fuzzy Model was developed by using two membership sets; i.e. the Overall Equipment Effectiveness (OEE) variable membership set of the production machine and Nugget Demand Forecasting. Nugget demand forecasting uses an exponential smoothing method due to its time-series type of query history data. OEE values were calculated using Availability, Performance and Quality Yield. In the Fuzzy approach, the Forecasting Membership Set uses the Triangular Membership Function type, and the OEE Membership Set uses the Trapezoidal Membership Function type. The fuzzy set model produced can be used as a tool for the company in determining the value of the Optimal Capacity production so that demands can be fulfilled and the product stocks decrease.
Model Penentuan Jumlah Pesanan Pada Aktifitas Supply Chain Telur Ayam Menggunakan Fuzzy Logic Sesar Husen Santosa; Agung Prayudha Hidayat
Jurnal Ilmiah Teknik Industri Vol. 18, No. 2, Desember 2019
Publisher : Department of Industrial Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v18i2.8486

Abstract

This study aims to present a fuzzy logic approach in the modeling of optimal order quantities of chicken eggs to suppliers. Determination of the number of egg orders using fuzzy logic by considering the condition of supply and demand so that the number of eggs ordered by Agent eggs is optimal so that the amount of stock in the warehouse is reduced. The variables used in developing the fuzzy set model are the price of eggs/crates, the composition of the weight of eggs in the crates, and the amount of stock of eggs in the warehouse at the time of ordering. The membership set for egg ordering uses the Triangular and Trapezoidal membership functions. The fuzzy set model produced in this study can be used as a tool for decision making in determining the optimal number of egg orders to suppliers.
Fuzzy Logic Approach to Determine the Optimum Nugget Production Capacity Sesar Husen Santosa; Suhendar Sulaeman; Agung Prayudha Hidayat; Ilham Ardani
Jurnal Ilmiah Teknik Industri Vol. 19, No. 1, June 2020
Publisher : Department of Industrial Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v19i1.10295

Abstract

This research aimed to present the Fuzzy approach in determining the optimal production capacity of the Nugget Production. The Fuzzy Model was developed by using two membership sets; i.e. the Overall Equipment Effectiveness (OEE) variable membership set of the production machine and Nugget Demand Forecasting. Nugget demand forecasting uses an exponential smoothing method due to its time-series type of query history data. OEE values were calculated using Availability, Performance and Quality Yield. In the Fuzzy approach, the Forecasting Membership Set uses the Triangular Membership Function type, and the OEE Membership Set uses the Trapezoidal Membership Function type. The fuzzy set model produced can be used as a tool for the company in determining the value of the Optimal Capacity production so that demands can be fulfilled and the product stocks decrease.
Smart Production Planning Model for T-Shirt Products at Raensa Convection Sesar Husen Santosa; Agung Prayudha Hidayat; Ridwan Siskandar; Khoirul Aziz Husyairi
Jurnal Ilmiah Teknik Industri Vol. 22, No. 1, June 2023
Publisher : Department of Industrial Engineering Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/jiti.v22i1.21398

Abstract

The increasing stock condition of cotton combed 30s t-shirts causes Convection to require optimal production planning, influenced by demand, safety stock, and selling price. The analysis of forecasting demand for t-shirts obtained a need for 217 t-shirts using the Multiplicative Decomposition forecasting method with MAD = 22.47 and MAPE = 0.17. Based on demand data for 1 year, the Safety Stock that must be maintained is 126 shirts/month or 3 shirts/week. The optimal production defuzzification results are 369 t-shirts with 81 fuzzy rules used. The Master Production Planning (MPS) directs the production schedule to be carried out in January, scheduled for the 4th week of December the previous year, as many as 123 shirts and ended on the third Sunday in January as many as 92 shirts to maintain stock conditions and meet the demand of consumer.
Co-Authors Agung Prayudha Hidayat Aldiyansyah Aleida, Silvera Marsya Anamy, Fathia Marcha Ananda, Dea Angga Eben Ezer Annisa Kartinawati Antonio Banggas Gregory Sinaga Apristio Faza Ridhar Rahman Aqim Try Kurnia Ardani, Ilham Azka Khairani Marisda Bachtiar, Willy Barokah, Wuliddah Tamsil Bayu Suriaatmaja Suwanda Bayu Suriaatmaja Suwanda Bayyinah, Aulia Nabil Billi Rifa Kusumah Bintang Aprilio Dardanella, Derry Derry Dardanella Divo Wibowo Adi Doni Yusri Fany Apriliani Faqihhudin, Muhammad Raka Fauzan Naufal Gibran Fionando Emir Satriadana Firman Muhammad Basar Ghailan Arhab Hafiz Agi Alfasih Hendri Wijaya, Hendri Herti Herti Heryudianto Vibowo Husyairi, Khoirul Aziz Iklima Istiqomah Ilham Ardani Indrawan, Purana Insani, Mutiara Fitria Irfan Tigranaufal Nugraha Irmansyah Irmansyah Irzaman, Irzaman Jimmy Mohamad Alpino Anak Gumay Keinanjung Ruswandi Laily Rochmatul Charky Lutfi Aziz Febrika Ardy Madyananda, Fauzaan Fadhlurrohman Marithasari, Harries Mohammad Akbar Alfa Dirk Steyer Muhamad Raihan Afarel Nadji Baraba Muhamad Zikri Abdillah Muhammad Al-Ghifari Muhammad Danang Mukti Darmawan Muhammad Danang Mukti Darmawan Muhammad Fakhri Alauddin Muhammad Habiburrahman, Muhammad Muhammad Ifan Al Aziz Nabil Bayyinah, Aulia Nalanaya, Nalanaya Nanda Octavia Nanda Octavia Nayla Cahya Kamila Nerol, Ivan De Noer A Indrawan Nourma Ayuadika Novia Rahmawati Pane, Nelson Andreas Pangestu, Fattah Jati Prayuda Hidayat, Agung Purnomo, Hanif Putri, Stevani Rafiq Rizki Prabowo Refiansyah Nur Renny Soelistiyowati Revanda Arifia Ridwan Siskandar Rina Martini Ringga Gilang Baskoro Rizkiriani, Annisa Robby Priaji Sakti Samsudin, Discania Martiani Savanah, Khadijah Meutia Septiyaningsih, Lutfi Sinaga, Antonya Rumondang Sista Naelly Adzimi Siti Aisyah Suhendar Sulaeman Suhendi Irawan Sulaeman, Suhendar Susanti, Raskia Suwanda, Bayu Suriaatmaja Tiara Safitrah Vina Puspitasari Wiyanto, Renhard Cornelis Wiyoto Wiyoto Zahran, Fadhil Rizqi Az Zahrani, Firda Alifathuz Zaki Rafi Athallah