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Journal : IJISTECH

Sentiment Analysis Of Instagram Social Media Users For BPJS Health Services Using Support Vector Machine Algorithm Hsb, Dinda Umami; Furqan, Mhd; Armansyah, A
IJISTECH (International Journal of Information System and Technology) Vol 8, No 1 (2024): The June edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i1.349

Abstract

Health services are an important aspect of people's quality of life, and BPJS as a public health service provider in Indonesia is often the subject of discussion on social media platforms. The SVM method has proven effective in sentiment analysis in various domains, including social media. In this study, data in the form of user comments and uploads on BPJS Instagram accounts were collected and processed to identify Positive, Negative or Neutral sentiments regarding the health services provided by BPJS. with the government's efforts to improve access and quality of health services for pregnant women as well as provide financial protection in order to reduce maternal and infant mortality in Indonesia and has the aim of reducing the burden of childbirth costs for people with low and middle incomes. This information can be input for BPJS in improving quality according to public expectations. In this research with a data set of 600 comments, the research was carried out with the support vector machine classification and the highest accuracy results in the first test experiment on 80% training data and 20% test data with 97% precision, 64% recall and 77% F1-Score obtained accuracy by 83%.
Determination of The Closest Path Using The Greedy Algorithm Furqan, Mhd.; Adha, Rifki Mahsyaf; Armansyah, A
IJISTECH (International Journal of Information System and Technology) Vol 7, No 5 (2024): The February edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v7i5.332

Abstract

Several alternate routes are displayed by the greedy algorithm, which is widely used in the closest travel route search application. This study employs the greedy method, which sets up a route map to quickly determine the shortest path. The goal of this study is to find the shortest path using a greedy algorithm. By using a greedy algorithm system to find the closest point to which the user's selection is made, the study's eight times with different points on the graph can be seen in the user's position. In an attempt to find the best solution, the greedy algorithm—which is renowned for its simplicity and effectiveness—iteratively chooses the best option available at each step. The greedy algorithm frequently gives priority to proximity when it comes to travel route optimization, and it might not always produce the shortest path overall. However, it's a well-liked option for some applications due to its quickness and simplicity of implementation. Notwithstanding its drawbacks, the greedy algorithm can offer insightful solutions for optimization and route planning issues. Users can make decisions more quickly and possibly find alternate routes they might not have otherwise thought of by using this algorithm to find the closest point in a travel route search application. The study's conclusions also emphasize how crucial it is to take user convenience and preferences into account when developing route planning systems. Future studies could look into ways to improve the greedy algorithm's performance and fix its drawbacks, like adding more heuristics or combining it with other optimization strategies. Overall, this study's findings validate the greedy algorithm's efficacy as a workable choice for locating the closest point in travel route search applications, providing consumers with a dependable and approachable navigational aid.