https://journals.unisba.ac.id/index.php/statistika <p><a title="STATISTIKA" href="https://journals.unisba.ac.id/index.php/statistika" target="_blank" rel="noopener">Statistika</a> published by Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung have already <strong>accredited</strong> by Ministry of Research, Technology and Higher Education of the Republic of Indonesia <a title="Peringkat Sinta 3" href="https://journals.unisba.ac.id/public/journals/aset/statistika/sertifikat_statistika.jpg" target="_blank" rel="noopener">Number 200/M/KPT/2020 </a>valid for 5 (five) years from Volume 18 Number 1 until Volume 22 Nomor 2 Tahun 2022 with <a title="Sinta 3" href="https://sinta.kemdikbud.go.id/journals/profile/7529" target="_blank" rel="noopener">Sinta (Science and Technology Index)</a> Score is S3. This Journal as pouring media and discussion of scientific papers in the field of statistical science and its applications, both in the form of research results, discussion of theory, methodology, computing, and review books. Published biannually in May and November each. </p> Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung en-US Statistika 1411-5891 https://journals.unisba.ac.id/index.php/statistika/article/view/3145 <p><strong>ABSTRAK</strong></p> <p>Proses industri seringkali menghasilkan data cacat yang bersifat autokorelasi, hal ini meyebabkan asumsi dasar penggunaan peta kendali tidak terpenuhi. Peta kendali demerit direkomendasikan untuk perusahaan yang terdapat berbagai macam tingkat kesalahan. Peta kendali demerit adalah metode pengendalian kualitas yang mengkategorikan jenis cacat ke dalam beberapa kelas berdasarkan tingkat keseriusannya. Peta kendali demerit sangat berguna dalam situasi di mana terdapat berbagai macam tingkat kesalahan, memungkinkan perusahaan untuk mengidentifikasi dan mengatasi cacat berdasarkan tingkat dampaknya terhadap kualitas produk. Penelitian ini bertujuan untuk memperoleh peta kendali Demerit pada data berautokorelasi dan menerapkan peta kendali Residual Demerit dan peta kendali <em>Moving Centerline Demerit</em> sebagai solusi dalam peta kendali Demerit autokorelasi terhadap pengendalian kecacatan produk pada data wadah plastik anti bocor. Metode yang digunakan adalah peta kendali demerit, peta kendali Residual, dan peta kendali <em>Moving Centerline Demerit</em> (MCD). Data yang digunakan merupakan data sekunder. Hasil penenelitian ini memperlihatkan bahwa peta kendali Residual dan peta kendali <em>Moving Centerline Demerit</em> sama unggulnya dalam mengatasi data autokorelasi pada peta kendali Demerit dimana sama-sama terdapat 4 <em>out of control</em> atau 4 titik yang mengindikasikan adanya masalah proses produksi yang tidak dapat diatasi oleh perusahaan.</p> <p><strong>ABSTRACT</strong></p> <p><em>Industrial processes often produce defect data that is autocorrelated, causing the basic assumptions of using control maps to not be met. If there are various levels of errors in the company, then the company is advised to use the Demerit control map. Demerit control map is a quality control method that categorizes defect types into several classes based on their seriousness. Demerit control maps are particularly useful in situations where there is a wide range of error rates, allowing companies to identify and address defects based on their level of impact on product quality. This study aims to derive Demerit control maps on autocorrelated data and apply the Residual Demerit control map and the Moving Centerline Demerit control map as solutions in the autocorrelated Demerit control map to product defect control on leak-proof plastic container data. The methods used are Demerit control map, Residual control map, and Moving Centerline Demerit (MCD) control map. The data used is secondary data. The results of this study indicate that the Residual control map and the Moving Centerline Demerit control map are equally superior in overcoming autocorrelated data on the Demerit control map where there are both 4 out of control or 4 points that indicate a production process problem that cannot be overcome by the company.</em></p> Nurmasyita Nasruddin Erna Tri Herdiani Nasrah Sirajang Copyright (c) 2024 Statistika 2024-11-13 2024-11-13 24 2 123 134 10.29313/statistika.v24i2.3145