Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Unnes Law Journal : Jurnal Hukum Universitas Negeri Semarang Recursive Journal of Informatics
Muhammad Fikri
Universitas Negeri Semarang
Computer Science & IT Law, Crime, Criminology & Criminal Justice

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Implementation of Carbon Capture and Storage in order to Achieve Net Zero Emissions in Indonesia Raphael Mayaka; Stephen Rodriguez; Ubaidillah Kamal; Muhammad Fikri
Unnes Law Journal Vol. 10 No. 1 (2024): April, 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/ulj.v10i1.4526

Abstract

In Indonesia, currently many people still use fossil fuels as the main energy source, but with the use of fossil fuels, greater carbon dioxide emissions will be released into the atmosphere, ultimately causing climate change (global warming). To overcome this problem, Indonesia is now starting to adopt techniques that have been used by several countries, namely carbon capture. Carbon Capture and Storage or commonly called CCS or some call it CCUS (Carbon Capture, Utilization and Storage) is one solution to climate change which continues to worsen over time. Indonesia itself is currently preparing 15 projects that will develop and use CO2 capture technology. The research method in the research carried out is using a normative juridical approach. The normative juridical approach is carried out by examining legal principles, legal provisions, legislation and legal mechanisms. Based on the normative type of legal research, several normative approaches are also used, namely the Conceptual Approach and the Statutory Approach. ESDM Ministerial Regulation No. 2 of 2023 does not directly provide benefits to society. This regulation focuses on regulations and incentives for business actors in the upstream oil and gas sector to implement Carbon Capture and Storage (CCS) technology. In Presidential Regulation no. 14/2024 states that holding CCS can be based on three things Carrying out CCS or CCUS implementation in Indonesia begins after obtaining a storage permit for CCS implementation schemes based on permits, whereas for CCS implementation schemes based on cooperation contracts begins when the contractor obtains approval for the proposed field development plan or changes. There are a few things that Indonesia should do such as making a new regulation about funding, insentive and public participation.
Analysis Of The Use Of Nazief-Adriani Stemming And Porter Stemming In Covid-19 Twitter Sentiment Analysis With Term Frequency-Inverse Document Frequency Weighting Based On K-Nearest Neighbor Algorithm Muhammad Fikri; Zaenal Abidin
Recursive Journal of Informatics Vol. 2 No. 2 (2024): September 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/fqc79v89

Abstract

Abstract. This system was developed to determine the accuracy of sentiment analysis on Twitter regarding the COVID-19 issue using the Nazief-Adriani and Porter stemmers with TF-IDF weighting, along with a classification process using K-Nearest Neighbor (KNN) that resulted in a comparison of 48.24% for Nazief-Adriani and 48.24% for Porter. Purpose: This research aims to determine the accuracy of the Nazief-Adriani and Porter stemmer algorithms in performing text preprocessing using a dataset from Indonesian-language Twitter. This research involves word weighting using TF-IDF and classification using the K-Nearest Neighbor (KNN) algorithm. Methods/Study design/approach: The experimentation was conducted by applying the Nazief-Adriani and Porter stemmer algorithm methods, utilizing data sourced from Twitter related to COVID-19. Subsequently, the data underwent text preprocessing, stemming, TF-IDF weighting, accuracy testing of training and testing data using K-Nearest Neighbor (KNN) algorithm, and the accuracy of both stemmers was calculated employing a confusion matrix table. Result/Findings: This study obtained reasonably accurate results in testing the Nazief-Adriani stemmer with an accuracy of 50.98%, applied to sentiment analysis of COVID-19-related Twitter data using the Indonesian language. As for the accuracy of the Porter stemmer, it achieved an accuracy rate of 48.24%. Novelty/Originality/Value: Feature selection is crucial in stemmer accuracy testing. Therefore, in this study, feature selection is carried out using the Nazief-Adriani and Porter stemmers for testing purposes, and the accuracy data classification is conducted using the K-Nearest Neighbor (KNN) algorithm
Co-Authors Raphael Mayaka Stephen Rodriguez Ubaidillah Kamal Zaenal Abidin