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Siti Nurhaliza Sofyan
Universitas Pembangunan Panca Budi
Computer Science & IT

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Implementasi Sistem Pendukung Keputusan dalam menentukan Kecamatan Terbaik Menggunakan Algoritma Entropy dan Additive Ratio Assessment (ARAS) Andi Ernawati; Ayu Ofta Sari; Siti Nurhaliza Sofyan; Ananda Aulia; Zulham Sitorus; Khairul
Bulletin of Information Technology (BIT) Vol 4 No 4: Desember 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i4.1066

Abstract

In the context of regional development and decision making related to determining the best village, the use of a Decision Support System (DSS) with the application of the Entropy and Additive Ratio Assessment (ARAS) algorithms is a very important approach. The main objective of this research is to propose and implement a method that utilizes the Entropy algorithm to evaluate criteria weights and ARAS to rank villages based on predetermined criteria. This approach begins the process by identifying relevant criteria to determine the best village in an area. Next, the Entropy algorithm is used to measure the level of importance or relative weight of each predetermined criterion. This step helps in assessing how informative each criterion is in the decision-making process regarding determining the best Village. After determining the criteria weights using Entropy, the approach continues with the application of the ARAS method. ARAS is used to rank villages based on normalized values ​​from previously determined criteria. The data normalization process is carried out to ensure the validity of comparisons between villages. The final result of this approach is a ranking of villages indicating the best villages based on the criteria considered. This method was tested in a case study using a dataset involving a number of relevant criteria for assessing village development potential. Experimental results show that the use of the Entropy and ARAS algorithms in the Decision Support System provides an effective and informative framework for decision makers in determining the best Village. In conclusion, this approach provides a solid foundation to support a more effective and precise decision-making process in regional development based on clearly defined criteria.
Analisis Sentimen Terhadap Dampak Inflasi Menggunakan Naive Bayes Siti Nurhaliza Sofyan; Muhammad Iqbal
Bulletin of Information Technology (BIT) Vol 6 No 1: Maret 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v6i1.1796

Abstract

This research aims to analyze public sentiment regarding the impact of inflation in 2024 on survival. Inflation is seen as one of the most important factors influencing a country's economic growth. In this research, the results of public sentiment in 300 tweets on the Twitter application were obtained, namely the emotion 'joy' was 194 or 64%, 'surprise' was 71 or 23%, 'fear' was 20 or 6%, 'sadness' was 9 or 3% , 'disgusted' by 7 or 2% and 'angry' by 0.06% . This research uses the orange mining application with multilingual sentiment analysis techniques visualized through box plots and scatter plots, which aims to classify Twitter users based on their emotional responses. The decline in the level of economic growth has led to the emergence of the view that inflation has a negative effect on economic growth, not a positive effect. The findings of this research provide insight into the government's role in overcoming current inflation and providing sustainable benefits and are expected to be used as material for evaluating the government's role.
Co-Authors Ananda Aulia Andi Ernawati Ayu Ofta Sari Khairul Muhammad Iqbal Sitorus, Zulham