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All Journal JURNAL MANAJEMEN INDUSTRI DAN LOGISTIK INVENTORY : Industrial Vocational E-Journal On Agroindustry Serambi Engineering
Juli Astuti
Politeknik APP Jakarta
Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Energy Engineering Environmental Science Industrial & Manufacturing Engineering Transportation

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EVALUASI PEMILIHAN PENYEDIA JASA KURIR BERDASARKAN METODE ANALYTICAL HIERARCHY PROCESS (AHP) Juli Astuti; Erika Fatma
Jurnal Manajemen Industri dan Logistik (JMIL) Vol 1, No 1 (2017): Page 1-74
Publisher : Politeknik APP Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (464.346 KB) | DOI: 10.30988/jmil.v1i1.3

Abstract

Logistics activity plays an important role in the business process where there is a distribution process to deliver product from the manufacturer / seller to the consumer. Nowadays there are many companies that provide logistics services with its own advantages and disadvantages. This condition, gives users more flexibility in determining which courier companies they will use. IN ordr to aid decision makers in selecting the best courier services providers, we conducted a study regarding the criteria used in determining user’s choice by using Analytical Hierarchy Process (AHP). The purpose of this study was to determine the main criteria as user’s consideration for selecting the best logistics service providers. Based on a survey conducted on the online sellers, it is known that the criteria of the key considerations in selecting a courier service is Reliability, the reliability of a courier company in serving the needs and desires of its customers, followed by cost and convenience
Komparasi Metode Regresi Linier, Exponential Smoothing dan ARIMA Pada Peramalan Volume Ekspor Minyak Kelapa Sawit di Indonesia Trisna Yuniarti; Juli Astuti; Irfan Rusmar; Ika Widiana; Fajar Ciputra Daeng Bani
INVENTORY: Industrial Vocational E-Journal On Agroindustry Vol 3, No 1 (2022): Published in June 2022
Publisher : Politeknik ATI Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52759/inventory.v3i1.74

Abstract

This study aims to compare several methods to get the best methods on forecasting the volume of Indonesian palm oil exports. In addition, this study also aims to estimate the volume of Indonesian palm oil exports for the next five years. Some of the forecasting methods used in this study are linear regression, exponential smoothing, and ARIMA. The data used is historical data on the volume of palm oil exports from 1981 to 2020. The results of calculations and analysis show that the exponential smoothing model of the damped trend method produces the smallest error value compared to other methods, the MAD value is 860,353, the MSE value is 1,707,738,707,222, the RSME value is 1,306,805, and the MAPE value is 20.6%. This method has chosen to be the best forecasting method for the next five years. The forecast results obtained that the volume of Indonesian palm oil exports for the next five years are28.864.223,31 tons, 28.967.062,92 tons, 29.064.976,80 tons, 29.158.200,89 tons, and 29.246.959,81 tons.
Pendekatan Text Mining dalam Menilai Sentimen Publik pada Baterai Kendaraan Listrik Trisna Yuniarti; Juli Astuti; Firdhani Faujiyah; M. Zaiyar
Jurnal Serambi Engineering Vol. 9 No. 4 (2024): Oktober 2024
Publisher : Faculty of Engineering, Universitas Serambi Mekkah

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Abstract

The use of technology and information in the Industry 4.0 era has been widely used to extract information from textual data patterns. The development of technology and the availability of big data from various platforms can provide valuable insights and facilitate better decision making. In this study, we aim to extract information and obtain the main topics of public sentiment on electric vehicle batteries. The data source is obtained from the results of comments or tweets on X social media. A total of 1,302 texts were processed using text mining techniques in the orange data mining application. This technique consists of several stages of text processing, namely transformation, filtering and tokenisation. The results of the text processing are extracted by word cloud to find the characteristics of words that are often discussed by the community. Next, sentiment analysis is performed to find out people's opinions about electric vehicle batteries based on positive, negative and neutral categories. Finally, topic modelling is performed using LDA to identify the topics discussed in each sentiment category. The results showed that public opinion was divided into three categories: 37% positive, 42% neutral and 21% negative. A frequently discussed topic in relation to electric vehicle batteries is the word feature nickel. Topic modelling produces five main topic categories that are frequently discussed by the public.
Co-Authors Fajar Ciputra Daeng Bani Fatma, Erika Firdhani Faujiyah Ika Widiana Irfan Rusmar M. Zaiyar Trisna Yuniarti