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All Journal MANAJERIAL Bulletin of Social Informatics Theory and Application
Wicaksono Febriantoro, Wicaksono
Ministry of Trade Republic of Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Social Sciences

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KAJIAN DAN STRATEGI PENDUKUNG PERKEMBANGAN E-COMMERCE BAGI UMKM DI INDONESIA Febriantoro, Wicaksono
Manajerial : Jurnal Manajemen dan Sistem Informasi Vol 17, No 2 (2018): Manajerial : Jurnal Manajemen dan Sistem Informasi
Publisher : Program Studi Pendidikan Manajemen Perkantoran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/manajerial.v17i2.10441

Abstract

Menghadapi Asean Economic Community (AEC) yang telah dimulai pada tahun 2016, Usaha Mikro Kecil Menengah (UMKM) diharapkan semakin produktif dan berdaya saing. Salah satu cara untuk meningkatkan daya saing yaitu melalui adopsi ICT (information, communication and technology) termasuk adopsi e-commerce . Penelitian ini bertujuan untuk mengetahui kondisi eksisting, potensi e-commerce, mengetahui faktor pendukung dan penghambat adopsi e-commerce  bagi UMKM serta merumuskan strategi pendukung perkembangan e-commerce bagi UMKM. Metode Penelitian menggunakan metode kualitatif deskriptif dengan pendekatan induktif. Faktor pendukung dan Penghambat serta strategi pendukung berdasarkan survei perilaku konsumen dan riset perkembangan adopsi e-commerce  telah dipetakan dalam analisis SWOT kualitatif dan kuantitatif. Hal ini bermanfaat sebagai masukan bagi stakeholder khususnya pemerintah dan pelaku UMKM untuk memperkuat sektor UMKM terutama dalam hal peningkatan adopsi e-commerceKata Kunci: e-commerce, UMKM,  strategi pendukung, Analisis SWOT
A review: evolution of big data in developing country Prasetyo, Bayu; Aziz, Faiz Syaikhoni; Faqih, Kamil; Primadi, Wahyu; Herdianto, Roni; Febriantoro, Wicaksono
Bulletin of Social Informatics Theory and Application Vol. 3 No. 1 (2019)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v3i1.162

Abstract

The development of technology from year to year is increasingly rapid and diverse. All systems that exist in human life began to be designed with technology that requires large data storage. Big Data technology began to be developed to accommodate very large data volumes, rapid data changes, and very varied. Developing countries are starting to use Big Data a lot in developing their systems, such as healthcare, agriculture, building, transportation, and various other fields. In this paper, it explains the development of Big Data applied to the sectors previously mentioned in developing countries and also the challenges faced by developing countries in the process of developing their systems.
Twitter sentiment analysis about economic recession in indonesia Eka Putra, Fauzan Prasetyo; Maulana, Fairuz Iqbal; Akbar , Nawawi Muhammad; Febriantoro, Wicaksono
Bulletin of Social Informatics Theory and Application Vol. 7 No. 1 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v7i1.592

Abstract

As one of the most popular social media platforms, Twitter enables users to express their opinions on diverse concepts, products, and services. Large quantities of data shared as tweets can be mined for user feedback and used to improve the quality of products and services. Using Twitter data and social media sentiment analysis, tracking how people feel about the recession in real time is possible. As a consequence, relevant organizations or governments can take preventative measures against the disinformation and unlawful conduct caused by the effects of the recession. This study aims to determine if there is a correlation between how people on Twitter feel about the recession. This study's data acquisition utilized "Recession"-tagged Twitter remarks from 2023. This study analyses filtered tweets for sentiment, emotion, word usage, and trends. According to the findings, 94% of tweets had benign sentiments, 4% had positive sentiments, and 2% had negative sentiments. Tweets with moderate subjective valence cluster in the middle of the polarity scale (between 1 and +1), while tweets with strong subjective valence are dispersed throughout the scale
Co-Authors Akbar , Nawawi Muhammad Aziz, Faiz Syaikhoni Bayu Prasetyo, Bayu Faqih, Kamil Fauzan Prasetyo Maulana, Fairuz Iqbal Primadi, Wahyu Roni Herdianto