Process Mining for Six Sigma

Process mining offers a set of techniques for gaining data-based insights into business processes from event logs. The literature acknowledges the potential benefits of using process mining techniques in Six Sigma-based process improvement initiatives. However, a guideline that is explicitly dedicated on how process mining can be systematically used in Six Sigma initiatives is lacking. To address this gap, the Process Mining for Six Sigma (PMSS) guideline has been developed to support organizations in systematically using process mining techniques aligned with the DMAIC (Define-Measure-Analyze-Improve-Control) model of Six Sigma. Following a design science research methodology, PMSS and its tool support have been developed iteratively in close collaboration with experts in Six Sigma and process mining, and evaluated by means of focus groups, demonstrations and interviews with industry experts. The results of the evaluations indicate that PMSS is useful as a guideline to support Six Sigma-based process improvement activities. It offers a structured guideline for practitioners by extending the DMAIC-based standard operating procedure. PMSS can help increasing the efficiency and effectiveness of Six Sigma-based process improving efforts. This work extends the body of knowledge in the fields of process mining and Six Sigma, and helps closing the gap between them. Hence, it contributes to the broad field of quality management

Business analytics in industry 4.0: a systematic review

Recently, the term “Industry 4.0” has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet-of-Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modelling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on the usage of Business Analytics within the Industry 4.0 concept, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analysed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modelling method. Our SLR analysis provides a mapping of how data-based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.The work of P. Cortez was supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We would like to thank to the three anonymous reviewers for their helpful suggestions

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

KINERJA Jurnal Bisnis dan Ekonomi

1. Kepemilikan lnstitusional sebagai Pemonitor Manajemen laba melalui Pemilihan Auditor Berkualitas oleh Endang Raino Wirjono 2. Pengaruh Partisipasi Anggaran, Persepsi Keadilan Distributif, Keadilan Prosedural, dan Goal Commitment terhadap Kinerja Dinas oleh I. G. K. Ulupui 3. Pengaruh Rasa Manfaat dan Kemudahan Terhadap Minat Berperilaku (Behavioral Intention} Para Mahasiswa dan Mahasiswi Dalam Penggunaan Internet oleh I Putu Sugiartha Sanjaya 4. Praktik-Praktik Manajemen Sumber Daya Manusia Strategik: Pengujian Empiris Universalistik dan Kontinjensi Dalam Menjelaskan Kinerja Organisasional oleh Heru Kurnianto Tjahjono 5. Pengaruh Ketidakamanan Kerja sebagai Dampak Restrukturisasi terhadap Kepuasan Kerja, Komitmen Organisasi dan Intensi Keluar Survivor oleh Nur Wening 6. Analisis Perbandingan Faktor-Faktor Penentu Perceived Risk Pada Konsumen Rokok Ringan dan Regular: Studi Kasus pada Mahasiswa Universitas Atma Jaya Yogyakarta oleh lndra Setiawan dan P. Didit Krisnadewara 7. Hubungan Pertukaran Pemimpin-Anggota dengan Kepuasan Kerja dan Komitmen Organisasional yang Dimediasi oleh Keadilan Organisasional oleh Vibriwati 8. Bedah Buku: Heroic Leadership: Praktik Terbaik "Perusahaan" Berumur 450 Tahun yang Mengubah Dunia oleh Nurcahyaningtya

Rancang Bangun Heater Element Segment pada Rangkaian Sistem Reactor Cavity Cooling RDNK

RANCANG BANGUN HEATER ELEMENT SEGMENT PADA RANGKAIAN SISTEM REACTOR CAVITY COOLING RDNK. Proses pendinginan secara pasif menjadi perhatian khusus sejak kecelakaan PLTN Fukushima dan TMI-2, kecelakaan tersebut diakibatkan oleh gagalnya sistem pendingin aktif dimana pompa tidak berfungsi. Kemudian, aliran sirkulasi alam sebagai prinsip kerja sistem pendingin pasif juga digunakan pada model pendinginan di celah antara dinding luar Reactor Pressure Vessel (RPV) reactor High Temperature Gass Cooled Reactor (HTGR) dan beton penopang RPV. Riset terkait reactor cavity cooling system berbasis pendingin pasif dilakukan dengan membuat Untai Uji Reactor Cavity Cooling System-Reaktor Daya Non Komersial (RCCS-RDNK), namun saat dilakukan komisioning fungsi pemanasannya tidak optimal, temperatur yang ingin dicapai yaitu 300oC – 400oC pada permukaan simulator RPV HTGR tidak tercapai, sehingga dilakukan modifikasi pada sistem pemanas dengan heater element segments (HES) berbasis proses radiasi. Tujuan penelitian adalah untuk melakukan analisis pada pengujian pemanasan HES hasil konstruksi hingga mencapai temperatur optimal. Metode eksperimen dilakukan dengan menghidupkan heater dan merekam Perubahan temperatur pada titik pengukuran di bagian permukaan insulator brick (BRICK), permukaan dalam RPV (RPVD), permukaan luar RPV (RPVL) dan udara luar. Hasil pengujian menunjukkan, secara umum capaian maksimal temperatur pada bagian permukaan RPV sekitar 400oC, dengan temperatur permukaan brick sekitar 700oC. Hal ini menunjukkan bahwa, konstruksi pemanas HES dapat beroperasi optimal dan memenuhi kriteria simulasi pendingin pada RCCS HTGR