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The, Jin Ai
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Industrial & Manufacturing Engineering

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Peran Natural Language Processing dalam Proses Pengembangan Produk Baru: Tinjauan Literatur Simanullang, Gerald Shan Benediktus; The, Jin Ai
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.6790.117-130

Abstract

Customer satisfaction is a key success factor for a business. To provide products that meet customer satisfaction, companies must be able to understand the customers’ needs and desires. Technological developments nowadays have helped companies to understand customer desires more easily so that companies can provide products that satisfy their customer. Natural Language Processing (NLP) is a technology that allows computers to process human language. NLP is also commonly referred as text-mining. NLP has been utilized in the New Product Development (NPD) process. We compiled studies related to NLP and NPD and conducted a literature review to map out how far NLP has been utilized in NPD processes. We found that in this era of Big Data, current NLP studies most often have the goal to process text data from online reviews on e-commerce and from social media. By using NLP, large amounts of data can produce valuable Voice of Customer (VOC) information for product development. We also found that NLP technology also has been utilized in other NPD processes that do not involve VOC, such as the design stage, document processing, and extraction of requirements in the NPD process.
Penentuan Jumlah Sumber Daya Manusia (SDM) di Bank XYZ dengan Menggunakan Pemodelan Simulasi Kusferyano, Bonfilio Elyan; The, Jin Ai; Purnama, Ign. Luddy Indra
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.7183.155-164

Abstract

In 2020 Covid-19 Pandemic strikes the whole country. It forces Organization to change their work habits from Work from Office (WFO) to Work from Home (WFH). It is also triggered by Indonesia Government policy to keep Social Distancing and start Work from Home (WFH). Bank XYZ response by change their working policy to allow employee Work from Office and Work from Home (Hybrid). Then each employee has a different work schedule every week based on their position and Line Manager discretion. Change of amount employee who work from office affects its performance obviously, especially operational function in this case HR Data Management Function. Bank XYZ has not make a further assessment, planning or working simulation about the optimal number of WFO employees yet. By direct observation, processing time data measurement, and memo arrival time data measurement, we make a model simulation based on Arena Software to find most suggested number of WFO employee. The simulation result shows that 7 employees is the best employee number consisting of 1 Team Lead, 1 Analyst, 1 Analyst Assistant, 2 Administrator and 2 Archive Personnel. This number is less than existing employee number before, 14 employees.
Peran Natural Language Processing dalam Proses Pengembangan Produk Baru: Tinjauan Literatur Simanullang, Gerald Shan Benediktus; The, Jin Ai
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.6790.117-130

Abstract

Customer satisfaction is a key success factor for a business. To provide products that meet customer satisfaction, companies must be able to understand the customers’ needs and desires. Technological developments nowadays have helped companies to understand customer desires more easily so that companies can provide products that satisfy their customer. Natural Language Processing (NLP) is a technology that allows computers to process human language. NLP is also commonly referred as text-mining. NLP has been utilized in the New Product Development (NPD) process. We compiled studies related to NLP and NPD and conducted a literature review to map out how far NLP has been utilized in NPD processes. We found that in this era of Big Data, current NLP studies most often have the goal to process text data from online reviews on e-commerce and from social media. By using NLP, large amounts of data can produce valuable Voice of Customer (VOC) information for product development. We also found that NLP technology also has been utilized in other NPD processes that do not involve VOC, such as the design stage, document processing, and extraction of requirements in the NPD process.
Penentuan Jumlah Sumber Daya Manusia (SDM) di Bank XYZ dengan Menggunakan Pemodelan Simulasi Kusferyano, Bonfilio Elyan; The, Jin Ai; Purnama, Ign. Luddy Indra
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.7183.155-164

Abstract

In 2020 Covid-19 Pandemic strikes the whole country. It forces Organization to change their work habits from Work from Office (WFO) to Work from Home (WFH). It is also triggered by Indonesia Government policy to keep Social Distancing and start Work from Home (WFH). Bank XYZ response by change their working policy to allow employee Work from Office and Work from Home (Hybrid). Then each employee has a different work schedule every week based on their position and Line Manager discretion. Change of amount employee who work from office affects its performance obviously, especially operational function in this case HR Data Management Function. Bank XYZ has not make a further assessment, planning or working simulation about the optimal number of WFO employees yet. By direct observation, processing time data measurement, and memo arrival time data measurement, we make a model simulation based on Arena Software to find most suggested number of WFO employee. The simulation result shows that 7 employees is the best employee number consisting of 1 Team Lead, 1 Analyst, 1 Analyst Assistant, 2 Administrator and 2 Archive Personnel. This number is less than existing employee number before, 14 employees.
Co-Authors Ign. Luddy Indra Purnama Kusferyano, Bonfilio Elyan Simanullang, Gerald Shan Benediktus