Analysis Characteristics of Car Sales In E-Commerce Data Using Clustering Model

Sari, Puspita Kencana; Purwadinata, Adelia

doi:10.21108/jdsa.2019.2.19

Cited by 8 publications

(12 citation statements)

References 4 publications

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“…Increasing world car sales from 2015 until 2018 as shown in Figure 1. The biggest portion of world car sales was from Asia region with increasing 11.7% in 2016, 2.9% in 2017 and 4.6% in 2018 [1]. Indonesia is one of automotive car manufacturer country in South East Asia that lead the region in automotive sector since the 1990s [2].The other side that the production cost increased from 2016 until 2018 due to exchange rate of United States Dollar increased to Indonesian Rupiah rate, in 2016 rose by 2.0% compared to 2015, in 2017 rose by 0.5% compared to 2016, then in 2018 rose by 3.4% compared to 2017.…”

Section: Introductionmentioning

confidence: 99%

Increasing Overall Equipment Effectiveness in Automotive Company Using DMAIC and FMEA Method

Rozak¹,

Jaqin²,

Hasbullah³

2020

JESA

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Cylinder Block Machining Line in Indonesian automotive company has launched a worldclass company, but this company still has intention to increase the OEE value. The aim of this research was to show the application of Failure Mode and Effect Analysis (FMEA) for increasing OEE value using the DMAIC cycle (Define, Measure, Analyze, Improve and Control). Others tool to analyze this problem were Pareto Diagram and Cause and Effect Diagram. Before improvement condition, the availability average value was 90.5% from the total of production loading time. FMEA was one of tool to select the priority of the production problem that should be taken action, so it could improve the industrial operating system from the long time and frequent breakdown equipment base on highest FMEA Risk Priority Number, by additional critical components check point and feedback system to others machine for similar problem. Thus, the ITS-0015 machine that selected as observed machine could reduce the machine breakdown time from 111 became 85 minutes/month and breakdown quantity from 4.7 became 3.5 times/month. Finally, we could increase the availability value from 90.8% became 96.0% and the impact was increasing OEE value from 87% became 92%. Keywords:overall equipment effectiveness, availability, failure mode and effect analysis, DMAIC cycle, pareto diagram, cause and effect diagram Journal Européen des Systèmes Automatisés

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Section: Introductionmentioning

confidence: 99%

Increasing Overall Equipment Effectiveness in Automotive Company Using DMAIC and FMEA Method

Rozak¹,

Jaqin²,

Hasbullah³

2020

JESA

View full text Add to dashboard Cite

show abstract

“…Namun dalam klasifikasi teks, KNN juga memiliki beberapa kekurangan, yaitu dalam menghadapi data dengan dimensi vektor yang tinggi yang menyebabkan ruang yang besar dan waktu komputasi yang tinggi. [10]. Oleh karena itu, diperlukan metode yang lebih efektif untuk dapat mereduksi dimensi agar mengurangi waktu komputasi dari algoritma KNN [10].…”

Section: Pendahuluanunclassified

“…[10]. Oleh karena itu, diperlukan metode yang lebih efektif untuk dapat mereduksi dimensi agar mengurangi waktu komputasi dari algoritma KNN [10].…”

Section: Pendahuluanunclassified

“…Penelitian [10] melakukan klasifikasi teks dengan menggunakan improvisasi terhadap algoritma KNN menggunakan Latent Semantic Analysis (LSA). LSA mampu mereduksi fitur vector, sehingga mampu mengurangi kompleksitas waktu klasifikasi KNN.…”

Section: Pendahuluanunclassified

“…LSA mampu mereduksi fitur vector, sehingga mampu mengurangi kompleksitas waktu klasifikasi KNN. Penelitian [10] juga membuktikan bahwa performansi yang didapat pada LSA -KNN mengalami peningkatan jika dibandingkan dengan klasifikasi menggunakan KNN saja.…”

Section: Pendahuluanunclassified

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Klasifikasi Topik Multi Label pada Hadis Shahih Bukhari Menggunakan K-Nearest Neighbor dan Latent Semantic Analysis

2020

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Hadith is the second source of Islamic law after Al-Quran, making it important to study. However, there are some difficulties in learning hadith, such as to determine which hadith belongs to the topic of suggestions, prohibitions, and information. This certainly obstructs the hadith learning process, especially for Muslims. Therefore, it is necessary to classify hadiths into the topic of suggestions, prohibitions, information, and a combination of the three topics which also called as multi-label topic. The classification can be done with the K-Nearest Neighbor, it is one of the best methods in the Vector Space Model and is the simplest but quite effective method. However, the KNN has a lack in dealing with high vector dimension, resulting in the long time computing classification. For that reason, it is necessary to classify Sahih Bukhari's Hadiths into the topic of recommendations, prohibitions, and information using the Latent-Semantic Analysis - K-nearest Neighbor (LSA-KNN) method. Binary Relevance method is also employed in this research to process the multi-label data. This research shows that the performance of LSA-KNN is 90.28% with the computation time is 19 minutes 21 seconds and the performance of KNN is 90.23% with the computation time is 37 minutes 06 seconds, which means that the LSA-KNN method has a better performance than KNN

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Implementation of Hybrid Blockchain in a Pre-Owned Electric Vehicle Supply Chain

Subramanian

Thampy

2021

IEEE Access

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Ecumenical carbon dioxide (CO2) emission emanates from car, bus, taxi, and motorcycle is around 45%.Electric vehicle could be the major contributor to abbreviate the pollution level in a transportation sector. According to the Forbes report the ecumenical passenger electric vehicle demand expected to reach 15% in 2025, and 23% in 2030. This research provides a blockchain predicated solution for a pre-owned electric vehicle market that could engender a trust, transparency, immutable records, and an efficient way to track the entire life cycle of a futuristic electric vehicle supply chain. At present most of the pre-owned electric conveyance purchase transpires through the third-party accommodations, websites, and mobile applications. This does not provide the authentic information on electric conveyance history, charging capabilities of the battery, history of the charging records, and performance of the driver (wear and tear affect battery life). Our solution implemented utilizing hybrid blockchain technology. Each stakeholder assigned with the Ethereum blockchain address to track the vehicle records as a distributed ledger. This design considered electric vehicle manufacturer, charging station, battery manufacturer, road convey ascendancy as major stakeholders. Astute contract designed with solidity programming. Truffle platform used to deploy keenly intellective contract in private blockchain that ascertain the privacy of electric conveyance owners and other stakeholders. Meta mask a mobile application utilized kovan network for tracking vehicle in a public blockchain. This application tested with 0.1 Ether for each transaction. Blockchain Electric Vehicle Cloud of Things (BEVCoT) concept proposed to integrate the IoT-Blockchain application in a cloud environment.

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Analysis Characteristics of Car Sales In E-Commerce Data Using Clustering Model

Cited by 8 publications

References 4 publications

Increasing Overall Equipment Effectiveness in Automotive Company Using DMAIC and FMEA Method

Increasing Overall Equipment Effectiveness in Automotive Company Using DMAIC and FMEA Method

Klasifikasi Topik Multi Label pada Hadis Shahih Bukhari Menggunakan K-Nearest Neighbor dan Latent Semantic Analysis

Implementation of Hybrid Blockchain in a Pre-Owned Electric Vehicle Supply Chain

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