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All Journal International Journal of Economics Development Research (IJEDR) Jurnal Ilmiah Dan Karya Mahasiswa Konstruksi: Publikasi Ilmu Teknik, Perencanaan Tata Ruang dan Teknik Sipil
Rusindiyanto Rusindiyanto
Universitas Pembangunan Nasional “Veteran” Jawa Timur
Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Social Sciences

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Analisis Beban Kerja Fisik Dan Mental Terhadap Rider Grab Menggunakan Metode Cardiovascular Load (CVL) Dan Subjective Workload Assesment Technique (SWAT) (Studi Kasus: Rider Grab Domisili Kelurahan Balas Klumprik Kecamatan Wiyung) Muhammad Zaky Mubarok; Rusindiyanto Rusindiyanto
Jurnal Ilmiah Dan Karya Mahasiswa Vol. 1 No. 3 (2023): JUNI : JURNAL ILMIAH DAN KARYA MAHASISWA
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jikma.v1i3.328

Abstract

Online motorcycle taxis are a mode of transportation that is widely used today. Online motorbike taxis are very quickly accepted by the public because of the ease of ordering and are application-based which can be easily downloaded by smartphone users on both Android and iOS systems. Thanks to online motorcycle taxis, passengers no longer need to wait on the side of the road to be picked up. In addition, passengers do not have to participate in negotiations, because the price has been determined per kilometer by the application system. The presence of online motorcycle taxis also adds jobs for the people of Indonesia.
Workload Analysis of Production Workers at PT Mitra Maharta: Applying the NASA-TLX and Full-Time Equivalent Methods Maulana Malik Agungdiningrat; Rusindiyanto Rusindiyanto; Mega Cattleya Prameswari Annissaa Islami
International Journal of Economics Development Research (IJEDR) Vol. 5 No. 2 (2024): International Journal of Economics Development Research (IJEDR)
Publisher : Yayasan Riset dan Pengembangan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/ijedr.v5i2.5395

Abstract

Combine Harvester is one of the products of PT Mitra Maharta that requires high work demands and accuracy in the production process. Workers in the production division tend to cause uneven workloads due to intensive labor demands and the obligation to work with high accuracy. Therefore, measurements of the workloads experienced by workers are needed. The NASA-TLX and FTE (Full Time Equivalent) methods were used to measure the workloads of 14 production workers. Some workers have an average WWL value from the range of 64 - 84.33 with the categories “High” to “Very High” in the NASA-TLX calculation, while in the FTE method calculation, they have an FTE index value from the range of 0.79 - 1.32 with the categories “Underload”, “Normal”, and “Overload”. Recommendations from this study include task restructuring and reallocation of human resources, additional manpower, as well as policies such as adequate rest time and training to improve worker efficiency.
Analisis Churn Nasabah Bank Dengan Pendekatan Machine Learning dan Pengelompokan Profil Nasabah dengan Pendekatan Clustering Arief Sulistyo Wibowo; Rusindiyanto Rusindiyanto
Konstruksi: Publikasi Ilmu Teknik, Perencanaan Tata Ruang dan Teknik Sipil Vol. 2 No. 1 (2024): Januari: Konstruksi: Publikasi Ilmu Teknik, Perencanaan Tata Ruang dan Teknik S
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/konstruksi.v2i1.43

Abstract

Rapid technological developments encourage the banking sector to continue to innovate so as not to be left behind. Tight competition in this industry is caused by customers' freedom to choose products and services that are considered more profitable. This phenomenon is known as Customer Churn, which is a condition where customers choose not to continue subscribing to a particular company. The method applied uses a machine learning approach and customer segmentation approach. The churn analysis results show that the machine learning model, especially the random forest model, has the highest level of accuracy with an F1-Score of 91%. This model has the potential to reduce churn rates from 20.4% to 5.61%, illustrating its positive impact. Apart from that, for the clustering results, the K-Prototype model was obtained for the clustering model with the highest Silhouette Score number of 0.1557 and 4 clusters were obtained.
Co-Authors Arief Sulistyo Wibowo Maulana Malik Agungdiningrat Mega Cattleya Prameswari Annissaa Islami Muhammad Zaky Mubarok