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All Journal Jurnal Ilmiah Teknik (JUIT) International Journal Science and Technology (IJST)
Arief Nurdini
Gunadarma University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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ANALISIS PERAMALAN PERMINTAAN TEMPE GMO 450 GRAM DENGAN MENGGUNAKAN METODE REGRESI LINEAR Arief Nurdini; Anita
Jurnal Ilmiah Teknik Vol. 1 No. 2 (2022): Mei : Jurnal Ilmiah Teknik
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (461.453 KB) | DOI: 10.56127/juit.v1i2.203

Abstract

Perkembangan industri makanan saat ini berjalan sangat pesat, hal ini menimbulkan persaingan di antar para produsen perusahaan. Perusahaan pastinya memiliki strategi dalam membuat perencanaan dan pengendalian produksi setiap produk yang dibuatnya. Salah satu faktor yang menunjang perencanaan dan pengendalian produksi adalah permintaan produk dari konsumen. Permintaan konsumen yang tidak menentu tentu saja menyebabkan kesalahan dalam merencanakan permintaan produk yang akan merugikan perusahaan baik dari biaya produksi ataupun keterlambatan pemenuhan permintaan. Oleh karenanya untuk merencanakan dan mengendalikan produksi dibutuhkan proses peramalan. Peramalan dilakukan agar perusahaan memiliki acuan dalam merencanakan dan mengendalikan kegiatan produksinya. Rumah Tempe Indonesia juga merupakan bidang usaha yang mulai menerapkan sistem produksi make to stock dalam proses bisnisnya. Sistem produksi tersebut seringkali menyebabkan ketidaksesuaian antara jumlah produksi dengan jumlah permintaan konsumen. Peramalan dilakukan dengan harapan agar perusahaan dapat memperkirakan kebutuhan produksi di masa mendatang, dapat merencanakan dan mengendalikan kegiatan produksinya dengan optimal sehingga permintaan konsumen dapat terpenuhi sehingga dapat meminimalisisr biaya produksi. Pola data permintaan yang didapatkan dari hasil pengolahan data pada produk tempe GMO 450 Gram adalah pola data trend. Berdasarkan dari pola data permintaan produk, dapat diketahui bahwa metode yang cocok dengan pola data tersebut adalah metode peramalan regresi linier dengan hasil ramalan 12 periode mendatang masing-masing 11788 Pcs, 12006 Pcs, 12224 Pcs, 12442 Pcs, 12660 Pcs, 12878 Pcs, 13096 Pcs, 13314 Pcs, 13532 Pcs, 13750 Pcs, 13968 Pcs, 14186 Pcs.
PERENCANAAN JADWAL INDUK PRODUKSI PADA PRODUK TEMPE DI RUMAH TEMPE INDONESIA Bellinda Ayustina; Arief Nurdini; Ardhy Lazuardy
Jurnal Ilmiah Teknik Vol. 2 No. 1 (2023): Januari : Jurnal Ilmiah Teknik
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/juit.v2i1.497

Abstract

Rumah Tempe Indonesia is a business sector that produces various processed soybeans, one of which is tempeh with two brands, namely Tempekita and Tempe Kim's. Rumah Tempe Indonesia has also started implementing a make to stock production system in its business processes. However, until now Rumah Tempe Indonesia has not implemented a specific method to support the production system it implements. This production system can cause problems including the amount of production that does not match consumer needs, causing a shortage or excess of products which are very inefficient for the company's business continuity. These problems can be solved through production planning using the selected aggregate planning strategy or the strategy that produces the lowest total production costs. This strategy is implemented in the preparation of a production master schedule to estimate the quantity of tempe products that must be met in the next period. In this study, two strategies were used, namely the level strategy with a production cost of 1,403,904,740.04, - and the chase strategy with a production cost of 1,404,149,544.96, -. Based on these considerations of production costs, the strategy chosen to be continued in making the master production schedule is the level strategy. The Master Production Schedule is made based on the calculation results of the disaggregation process on the production units of each brand for each period. The amount of Tempekita and Tempe Kim's production based on the Master Production Schedule (JIP) respectively for the 1st period was 2790 and 13099 pcs, the 2nd period was 1901 and 10624 pcs, the 3rd period was 2104 and 10421 pcs, the 3rd period 4th period 3224 and 8897 pcs, 5th period 4196 and 8329 pcs, 6th period 4117 and 8004 pcs, 7th period 3735 and 8790 pcs, 8th period 4799 and 7726 pcs, 7th period 9th of 3700 and 7613 pcs, 10th period of 5409 and 7116 pcs, 11th period of 5329 and 6792 pcs, 12th period of 5070 and 7455 pcs.
ANALYSIS OF DEMAND FORECASTING FOR TEMPEH PRODUCTS AT INDONESIAN TEMPEH HOUSES USING THE HOLT-WINTERS ADDITIVE METHOD APPROACH Arief Nurdini; Ardhy lazuardy
International Journal Science and Technology Vol. 2 No. 1 (2023): March: International Journal Science and Technology
Publisher : Asosiasi Dosen Muda Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56127/ijst.v2i1.854

Abstract

Rumah Tempe Indonesia is an MSME engaged in processing soybeans into tempeh products. The production system used is made to stockThis production system can cause problems, including the amount of production that does not match consumer needs, causing a shortage or excess of products which are very inefficient for the company's business continuity. For this reason, a study was carried out to determine the forecast for the demand for GMO Tempe at Indonesian Tempe Houses for the next 12 periods using the Holt-winters method and to determine the accuracy of the forecast made. The method used in this research is the Holt-winter method with the help of Ms. Excel Where. The final result of the research using Holt-winters has a level of forecasting accuracy90.1515344%, which means it is very good at predicting the demand for tempe in the future. Forecasting results in periods 37 to 48 respectively are 13372PCS, 12367PCS, 14196PCS, 12848PCS, 16655PCS, 15965PCS, 18032PCS, 15107PCS, 15132PCS, 17969PCS, 14267PCS, 21498PCS.
Co-Authors Anita Ardhy Lazuardy Bellinda Ayustina