Eliciting Requirements of Order Fulfilment in A Company

Andry, Johanes Fernandes; Tannady, Hendy; Nurprihatin, Filscha

doi:10.1088/1757-899x/771/1/012023

Cited by 16 publications

(11 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Dukungan perkembangan teknologi yang semakin tinggi, maka akan membawa peningkatan terhadap kemampuan dalam melakukan pengumpulan serta mengolah data menjadi suatu informasi yang berguna [3], [4]. Akumulasi dari banyaknya data-data tersebut telah menciptakan pola dimana data yang semakin banyak namun perolehan informasi dari data tersebut masih minim [5], [6]. Oleh karena itu, saat ini diperlukan suatu teknik analisa data dalam mencari pola dari kumpulan data-data tersebut, seperti penggunaan data mining [7].…”

Section: Pendahuluanunclassified

Integrasi Data Mining Dan Online Analytical Processing (Olap) Pada Data Performa Siswa

2020

View full text Add to dashboard Cite

Pertumbuhan teknologi membawa dampak terhadap peningkatan data untuk digunakan bagi setiap orang. Akumulasi data tersebut telah menciptakan pola data yang semakin banyak, namun perolehan informasi dari data tersebut masih minim. Oleh karena itu, saat ini diperlukan suatu teknik analisa data dalam mencari pola dari kumpulan data tersebut, salah satunya adalah data mining. Data mining merupakan proses pencarian informasi baru dari kumpulan data yang besar untuk menemukan informasi baru sebagai bahan pertimbangan dalam pengambilan keputusan di berbagai bidang, seperti bidang pendidikan. Dalam bidang pendidikan, banyak menghasilkan berbagai macam data, seperti data performa siswa dalam persiapan mengikuti ujian. Data tersebut dapat dianalisis dengan menggunakan metode On-Line Analytical Processing (OLAP) untuk menemukan pola dari data performa siswa tersebut. Penelitian ini berfokus pada proses integrasi data mining yang terdiri dari association, clustering, classification dan forecasting dengan kombinasi metode On-Line Analytical Processing (OLAP) pada data performa siswa. Penulis juga menggunakan bantuan tools Power OLAP untuk membantu analisa metode data mining. Hasil dari penelitian ini adalah penemuan pola baru dalam proses identifikasi kelompok data tersebut, seperti informasi mengenai rata-rata hasil ujian siswa berdasarkan persiapan ujian yang dilakukan dalam bentuk grafik sebagai alat pemodelan dari data, sehingga pengetahuan baru tersebut dapat membantu pihak universitas/sekolah untuk melalukan klasifikasi mengenai tingkat kelulusan dan dapat menetukan strategi dalam meningkatkan kelulusan siswa pada tahun - tahun berikutnya.

show abstract

Section: Pendahuluanunclassified

Integrasi Data Mining Dan Online Analytical Processing (Olap) Pada Data Performa Siswa

2020

View full text Add to dashboard Cite

show abstract

“…Product price is important to decide on the order quantity from the perspective of inventory management (Nurprihatin, Gotami and Rembulan, 2021). The price data always have been an important thing when it comes to the order fulfillment process (Andry, Tannady and Nurprihatin, 2020), and for designing the maintenance policy (Nurprihatin, Angely and Tannady, 2019). The price was also included to decide the truck scheduling through a crossdocking strategy .…”

Section: Introductionmentioning

confidence: 99%

Analytical Hierarchy Process and Topsis Approach to Perform Supplier Selection in Construction Industry

Nurprihatin

Antonius

Rembulan

et al. 2023

JIEMS

View full text Add to dashboard Cite

<p><em>Suppliers play an important role as suppliers of production raw materials, making companies must choose suppliers correctly. This paper discusses the best supplier selection to avoid financial and non-financial losses This paper uses four criteria for determining the best supplier, such as price, lead time, payment terms, and quality & service. A reasonable price following initial planning is always expected by the customers. Lead time is an essential consideration to ensure on-time delivery. Failure to perform on-time delivery will direct in poor payment terms. Besides, any products that do not meet quality standards will always lead to waste. Analytical Hierarchy Process (AHP) and Technique Order Preference by Similarity to Ideal Solution (TOPSIS) are used to select and determine the best supplier for the company. Pairwise comparisons are performed by making comparisons between each criterion and the alternatives made at each level of the hierarchy in pairs to get the value of the importance of the elements in the form of a qualitative opinion. The weight values for price, lead time, payment terms, and quality and service criteria are 0.0709, 0.1409, 0.2682, and 0.5200, respectively. According to AHP, alternative weight values in each criterion are 0.3899, 0.3063, and 0.3038, namely supplier A (rank 1), supplier B (rank 2), and supplier C (rank 3), respectively. However, the results of supplier selection using the TOPSIS method are supplier B (rank 1), supplier C (rank 2), and supplier A (rank 3) with values of 518.4025, 469.2017, and 412.3928, respectively.</em></p>

show abstract

“…In the development process, the manufacturing industry plays an important role in the Indonesian economy [1]. Current technological developments are a trigger to immediately explore the potential and improve company performance and generate revenue for the organization [2]. Technological innovations and changes in the business environment affect the industry's short-term performance and long-term sustainability as a result of economic growth [3].…”

Section: Introductionmentioning

confidence: 99%

Supply Chain Mapping to Prepare Golden Generation 2045 for Future Technology Infrastructure

2022

Self Cite

View full text Add to dashboard Cite

The continued growth of the manufacturing industry as a result of shifting consumer demands has created turmoil in the supply chain process. The Indonesian government is currently focusing on human development and mastery of science and technology in the supply chain to prepare for Golden Generation 2045. Various problems arise in the current supply chain process, namely lack of transparency, complex production processes, and poor partner relations. The manufacturing industry must begin to prepare for the development of technology infrastructure, especially in supply chain integration, supply chain performance, and information sharing. Based on the problems experienced, a supply chain strategy mapping was carried out to identify challenges and improvements that needed to be made. The supply chain strategy is mapped with market trends and defines divisions affected by constructing new technology infrastructure. This strategy is taken into consideration in defining challenges and improving supply chain processes. This study aims to map supply chain strategies in the form of a mindmap to maximize processes and prepare technology infrastructure. Supply chain strategy mapping allows the manufacturing industry to implement strategies to react quickly if there are problems with suppliers, missing orders, spikes in demand, or other unexpected things.

show abstract

Eliciting Requirements of Order Fulfilment in A Company

Cited by 16 publications

References 9 publications

Integrasi Data Mining Dan Online Analytical Processing (Olap) Pada Data Performa Siswa

Integrasi Data Mining Dan Online Analytical Processing (Olap) Pada Data Performa Siswa

Analytical Hierarchy Process and Topsis Approach to Perform Supplier Selection in Construction Industry

Supply Chain Mapping to Prepare Golden Generation 2045 for Future Technology Infrastructure

Contact Info

Product

Resources

About