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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal REKOMEN (Riset Ekonomi Manajemen)
Agus Sasmito Aribowo
UPN Veteran Yogyakarta
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering

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Ease of Communication as Mediating the Effect of Instagram Social Media on Purchase Intentions on the Marketplace Wisnalmawati Wisnalmawati; Agus Sasmito Aribowo; Dipo Hardi Dewantoro; Preya Alvita Yasmine; Olinda da Conceicao
Jurnal REKOMEN (Riset Ekonomi Manajemen) Vol 5, No 1 (2021)
Publisher : Universitas Tidar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31002/rn.v5i1.4344

Abstract

ABSTRACT. Marketing using digital media on the internet has become a necessity in the era of industrial technology 4.0. The Covid-19 pandemic has caused a shift in consumer behavior. Usually face to face changes to online shopping. UMKM Kuncup Seruni is a company that manufactures herbs and herbs from agricultural and plantation products. MSME Sri Rejeki is engaged in processing salak fruit products into various types of food, drinks, and snacks. The two MSME partners have produced many products. MSME's marketing reach is only local and promotions only rely on MSME exhibitions and showrooms that are available in the hope that consumers will come directly to the location. After the COVID19 pandemic, the number of visitors decreased drastically so that sales also decreased. The purpose of this study is to analyze the influence of Instagram social media on purchase intentions on Marketplace and analyze the influence of Instagram social media on purchase intentions on Marketplace mediated by the ease of communication. The novelty that emerged in this research is to develop the ease of communication so that the ease of communication is a very important concept to increase purchase intention. The research method related to the unit of analysis of this research is the consumers of UMKM Seruni and Sri Rejeki. The sample is 60 consumers, the sampling technique uses accidental, data collection uses a questionnaire (google form), conducts validity and reliability tests. The analysis technique uses the model of Structural Equation Modeling with PLS (Partial Least Square). Data analysis is descriptive and quantitative analysis. The results showed that there was no significant and significant effect of Instagram social media on purchase intentions on the Marketplace. The influence of Instagram social media on purchase intention is mediated by the ease of communication
Model Text-Preprocessing Komentar Youtube Dalam Bahasa Indonesia Siti Khomsah; Agus Sasmito Aribowo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (397.867 KB) | DOI: 10.29207/resti.v4i4.2035

Abstract

YouTube is the most widely used in Indonesia, and it’s reaching 88% of internet users in Indonesia. YouTube’s comments in Indonesian languages produced by users has increased massively, and we can use those datasets to elaborate on the polarization of public opinion on government policies. The main challenge in opinion analysis is preprocessing, especially normalize noise like stop words and slang words. This research aims to contrive several preprocessing model for processing the YouTube commentary dataset, then seeing the effect for the accuracy of the sentiment analysis. The types of preprocessing used include Indonesian text processing standards, deleting stop words and subjects or objects, and changing slang according to the Indonesian Dictionary (KBBI). Four preprocessing scenarios are designed to see the impact of each type of preprocessing toward the accuracy of the model. The investigation uses two features, unigram and combination of unigram-bigram. Count-Vectorizer and TF-IDF-Vectorizer are used to extract valuable features. The experimentation shows the use of unigram better than a combination of unigram and bigram features. The transformation of the slang word to standart word raises the accuracy of the model. Removing the stop words also contributes to increasing accuracy. In conclusion, the combination of preprocessing, which consists of standard preprocessing, stop-words removal, converting of Indonesian slang to common word based on Indonesian Dictionary (KBBI), raises accuracy to almost 3.5% on unigram feature.
Co-Authors Dipo Hardi Dewantoro Olinda da Conceicao Preya Alvita Yasmine Siti Khomsah, Siti Wisnalmawati -