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All Journal Aptisi Transactions on Technopreneurship (ATT) Computer Science and Information Technologies ADI Bisnis Digital Interdisiplin (ABDI Jurnal)
Purnama Harahap, Eka
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Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Library & Information Science Social Sciences

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GOOD, BAD AND DARK BITCOIN: A Systematic Literature Review Rahardja, Untung; Aini, Qurotul; Purnama Harahap, Eka; Raihan, Raihan
Aptisi Transactions On Technopreneurship (ATT) Vol 3 No 2 (2021): September
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v3i2.175

Abstract

Crypto currency investments have been in demand since the popularity of bitcoin. Crypto currency (cryptocurrency) is a currency based on cryptography or digital currency. The birth of bitcoin as one of the important foundations in the formation of the reputation of the crypto currency. Investing in crypto currencies is considered to provide more security and large profits for investors, with a cryptographic system the crypto currency is difficult to hack and fake. This cryptocurrency is also a digital key with encryption capabilities as security and validity, as well as real value that can be exchanged as an option. The most popular type of virtual currency is known as Bitcoin, and its popularity and strength continue to increase. At first glance, Bitcoin is very confusing. But here are ten facts that can be explained in simple terms, exactly what that little coin is and what happens.
Trends in sentiment of Twitter users towards Indonesian tourism: analysis with the k-nearest neighbor method Purnama Harahap, Eka; Dwi Purnomo, Hindriyanto; Iriani, Ade; Sembiring, Irwan; Nurtino, Tio
Computer Science and Information Technologies Vol 5, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v5i1.p19-28

Abstract

This research analyzes the sentiment of Twitter users regarding tourism in Indonesia using the keyword "wonderful Indonesia" as the tourism promotion identity. The aim of this study is to gain a deeper understanding of the public sentiment towards "wonderful Indonesia" through social media data analysis. The novelty obtained provides new insights into valuable information about Indonesian tourism for the government and relevant stakeholders in promoting Indonesian tourism and enhancing tourist experiences. The method used is tweet analysis and classification using the K-nearest neighbor (KNN) algorithm to determine the positive, neutral, or negative sentiment of the tweets. The classification results show that the majority of tweets (65.1% out of a total of 14,189 tweets) have a neutral sentiment, indicating that most tweets with the "wonderful Indonesia" tagline are related to advertising or promoting Indonesian tourism. However, the percentage of tweets with positive sentiment (33.8%) is higher than those with negative sentiment (1.1%). This study also achieved training results with an accuracy rate of 98.5%, precision of 97.6%, recall of 98.5%, and F1-score of 98.1%. However, reassessment is needed in the future as Twitter users' sentiment can change along with the development of Indonesian tourism itself.
Analisa Sistematis Manajemen Pengetahuan Digital Aplikasi Berbasis Kecerdasan Buatan di Universitas Sediyono, Eko; Hasibuan, Zainal Arifin; Setyawan, Iwan; Purnama Harahap, Eka; Darmawan, Arif
ADI Bisnis Digital Interdisiplin Jurnal Vol 3 No 2 (2022): ADI Bisnis Digital Interdisiplin (ABDI Jurnal)
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/abdi.v3i2.790

Abstract

Melalui kajian literatur yang menyeluruh, analisis ini bertujuan untuk memberikan gambaran luas tentang kajian penggunaan AI di universitas. Temuan deskriptif mengungkapkan bahwa ilmu komputer dan mata pelajaran STEM merupakan mayoritas topik yang tercakup dalam publikasi Artificial Intelligence in Learning (AIL) dan bahwa penelitian empiris paling sering menggunakan pendekatan kuantitatif. Temuan gabungan menunjukkan empat aplikasi untuk AIL dalam layanan kelembagaan dan administrasi dan layanan kontribusi akademik: 1. Metode artikel ini berdasarkan model pembelajaran, algoritma, dan jaringan saraf, yang dapat membuat keputusan tentang jalur pembelajaran individu dan konten siswa, memberikan pijakan kognitif, dan memberikan dukungan kepada siswa untuk berpartisipasi dalam dialog. Masalah penggunaan AIL di universitas dilarang karena persyaratan untuk meningkatkan pendekatan etis dan pedagogis, serta hambatan dan risiko AIL, hubungannya yang rapuh dengan sudut pandang pedagogis teoritis, dan faktor lainnya. Tujuan analisis sistematis adalah untuk memberikan solusi untuk masalah tertentu berdasarkan pendekatan pencarian yang eksplisit, sistematis, dan dapat direproduksi dan kriteria inklusi atau eksklusi yang menentukan penelitian mana yang termasuk pengkodean dan ekstraksi data berikut dari penelitian yang relevan, hasilnya diringkas dan setiap kesenjangan atau inkonsistensi dengan aplikasi nyata disorot. Menjelaskan dampak sifat kognitif dan non-kognitif siswa dalam memprediksi kinerja akademik untuk mahasiswa teknik. Untuk meningkatkan akurasi prediksi, mereka menggunakan faktor non-kognitif seperti mengatur waktu, kepribadian, identitas, kepemimpinan, dan dukungan masyarakat, berbeda dengan banyak studi lain.
Co-Authors Ade Iriani Arif Darmawan Eko Sediyono Hindriyanto Dwi Purnomo Irwan Sembiring Iwan Setyawan Nurtino, Tio Qurotul Aini Raihan Raihan, Raihan Untung Rahardja Zainal Arifin Hasibuan