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All Journal OPERATION EXCELLENCE: Journal of Applied Industrial Engineering MIND (Multimedia Artificial Intelligent Networking Database) Journal
PAMUNGKAS, CATUR ARTA
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Computer Science & IT Decision Sciences, Operations Research & Management

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Pemetaan Wilayah Desa di Kabupaten Kediri dengan Data Mining PAMUNGKAS, CATUR ARTA; DONORIYANTO, DWI SUKMA
MIND (Multimedia Artificial Intelligent Networking Database) Journal Vol 9, No 2 (2024): MIND Journal
Publisher : Institut Teknologi Nasional Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/mindjournal.v9i2.124-134

Abstract

ABSTRAKKediri yang terdiri dari beberapa wilayah memiliki kelebihan dan kekurangan sehingga perlu diketahui potensi wilayahnya agar dapat mencukupi satu sama lain. Potensi wilayah ini dapat dilakukan dengan pemetaan menggunakan metode complate linkage, metode klasifikasi, dan analisis biplot berdasarkan potensi wilayah tiap desa. Dengan metode ini penyebaran dan sifat data secara heterogen serta heterogen dapat diketahui. Maka penelitian ini memiliki tujuan untuk mengetahui pengelompokan desa, keragaman variabel potensi, dan korelasi keunggulan tiap wilayahnya. Penelitian ini memanfaatkan data dari Badan Pusat Statistik tahun 2018 hingga 2023 agar mudah diketahui wilayah yang memiliki kekuatan komoditas wilayah dengan melihat sumber daya manusianya. Hasil dari penelitian ini menunjukkan nilai complate linkage sebesar 17859125, pada metode kalsifikasi variabel jumlah SMA homogen dan variabel kepala keluarga heterogen, sedangkan untuk analisis biplot menghasilkan nilai sebesar 75,6%.Kata kunci: Analisis Biplot, Data Mining, Kediri, Faktor variabel, Pemetataan wilayahABSTRACTKediri has several regions that have advantages and disadvantages, so it is necessary to know the potential of the regions so that they can be sufficient for each other. This regional potential can be done by mapping using the complate linkage method, classification method, and biplot analysis based on the regional potential of each village. With this method, the distribution and heterogeneous nature of data can be known. So this research aims to determine village groupings, the diversity of potential variables, and the correlation between the advantages of each region. This research utilizes data from the Badan Pusat Statistik 2018 to 2023 so that it is easy to identify regions that have regional commodity strengths by looking at their human resources. The results of this research show a complate linkage value of 17859125, in the classification method for the variable number of homogeneous high school students and the variable for heterogeneous family heads, while the biplot analysis produces a value of 75.6%.Keywords: Area mapping, Biplot Analysis, Data Mining, Kediri, Variable factors
Analysis of waste in the flow process warehouse using the lean warehousing method at ABC Company Pamungkas, Catur Arta; Aryanny, Enny
Operations Excellence: Journal of Applied Industrial Engineering Vol. 17 No. 1 March 2025
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/oe.2025.v17.i1.136

Abstract

ABC Company is a manufacturing company that produces animal feed using raw materials stored in a warehouse. One type of raw material that is widely used for animal feed production needs is the premix type of raw material in warehouse 1. The large number of raw material needs makes warehouse activities increase. The large number of activities causes the warehouse to often experience wasteful activities with a lead time exceeding the company's standard of 420 minutes. This waste can reduce the effectiveness and efficiency of the warehousing flow process. Therefore, the purpose of this study is to determine what waste occurs in the warehouse using the lean warehousing method and to provide suggestions for improvements with Plan, Do, Check, Action and Seiri, Seiton, Seiso, Seiketsu, Shitsuke. Analysis carried out using the lean warehousing method is important for the category of activities that add value, the category of activities that are needed, the category of activities that are not needed, and the time of warehousing flow can be known through value stream mapping both before and after improvement. From the analysis conducted, it was found that there were 52 warehouse flow activities with an activity time of 556 minutes, which after being given a proposal for improvement in the warehouse flow process activities decreased to 39 activities with a lead time of 304 minutes.
Co-Authors Dwi Sukma Donoriyanto Enny Aryanny