JUMINTAL: Jurnal Manajemen Informatika dan Bisnis Digital

Analisis Sentimen Berdasarkan pada Twitter (X) terhadap Layanan Indihome Menggunakan Algoritma Support Vector Machine (SVM)

Diana Puspitasari — 2024-11-25

One of the social media with 24.85 million active users is Twitter. Information published on Twitter can be in the form of user opinions on an object, such as a product or service. Therefore, the company utilizes Twitter as a medium to disseminate information. This makes the company use Twitter as a medium to disseminate information. An example is an Internet Service Provider (ISP) company such as Indihome. Through Twitter, users can discuss their complaints and satisfaction with Indihome services. A method is needed, namely sentiment analysis to understand whether the textual data includes neutral opinion, negative opinion or positive opinion. So, the authors use the Support Vector Machine (SVM) method in sentiment analysis of Indihome service user opinions on Twitter, with the aim of getting a sentiment classification model using SVM and to find out how much accuracy is produced by the SVM method applied to sentiment analysis and to find out how satisfied Indihome service users are based on Twitter. After testing with the SVM method the results are 91% accuracy. Precision 51% Recall 75% and F1-Score 59%.

Perbandingan Analisis Sentimen Ulasan Aplikasi Ajaib Kripto Menggunakan Metode Naïve Bayes dan K-Nearest Neighbor

Calvin Wendy — 2024-11-25

Developments that occur in the investment sector make people interested in investing. The platform that is often used is the crypto magic application on the Google Play Store. Potential users see app reviews, which are based on user opinions and used as consideration before deciding to use the app. So data analysis is needed. One way of analyzing data is called sentiment analysis. There are many methods that can be used for sentiment analysis. So the author uses the Naive Bayes and K-Nearest Neighbor methods to find out a more accurate method. The data taken for this study is a review of the crypto magic application collected from 2022 to 2024 with 4784 data. Dataset through the stages of data division using k-fold cross validation with k=5, then the preprocessing stage, TF-IDF transformation, training Naive Bayes and KNN models with training data. The model was then tested on test data. The result is that the Naïve Bayes method provides an accuracy rate of 82%, precision of 83%, recall of 98% and an f1-score of 90%. While the KNearest Neighbor method provides an accuracy rate of 80%, precision of 84%, recall of 94% and f1-score of 89%. The conclusion of this study is that the Naïve Bayes method has a better level of accuracy than the K-Nearest Neighbor method.

Penilaian Keunggulan Layanan ShopeePay dan DANA Menggunakan Simple Additive Weighting (SAW)

Mhd. Fauzal Pratama — 2025-01-25

Advances in information technology have contributed greatly to the transformation of payment systems, including the emergence of online payment applications or e-wallets. E-wallets such as ShopeePay and DANA have become popular in Indonesia due to the ease, speed, security, and flexibility of transactions they offer. This study aims to evaluate and compare the performance of the two e-wallets using the Simple Additive Weighting (SAW) method. The SAW method is used to analyze and compare alternatives based on a number of predetermined criteria, such as ease of use, security, transaction speed, costs, and user satisfaction levels. Research data was obtained from various sources related to the performance of the two applications, including usage statistics and user reviews. The results of the analysis show that both apps have advantages in certain criteria; for example, ShopeePay is superior in transaction fees, while DANA stands out in speed and security. However, an overall assessment based on the weighting of the criteria reveals a final score that provides important insights for both users and developers. However, analysis using the SAW method provides deeper insight into the advantages of each application based on the weight of the relevant criteria. This study is expected to help users choose an e-wallet that suits their needs and provide guidance for application developers to improve service quality.

Implementasi Metode Simple Additive Weighting (SAW) dalam Rekomendasi Laptop Ekonomis untuk Mahasiswa

Yolanda Victoria Damanik — 2024-11-25

In today's digital era, laptops are a major necessity for students to support academic activities. However, budget limitations are often an obstacle in choosing a laptop that suits the needs and financial capabilities. This research aims to implement the Simple Additive Weighting (SAW) method in an economical laptop recommendation system for students. The way this method works is by calculating alternative choices based on predetermined weights and criteria then sorting to find the best alternative from all existing criteria. So that the results will get a laptop recommendation that is closest to the suitability of the needs of prospective laptop users. The criteria used in the study include price, processor, RAM, storage capacity, and battery life. Sample data is taken from 8 laptop models with a price range of 3-7 million available on the market. The results showed that the application of the SAW method successfully provided laptop recommendations that were in accordance with the needs and budget limitations of students. With this recommendation system, students can more easily choose a laptop that suits their academic needs and budget limitations. This research is expected to be a reference for the development of decision support systems in the selection of efficient and appropriate technology devices.

Sistem Informasi Geografis Pemetaan Kepemilikan Tanah (Studi Kasus di RT 05 RW 03 Desa Klaling)

Wahyu Cahyoaji — 2024-11-25

This research entitled " Geographic Information System for Mapping Land Ownership (Case Study in RT 05 RW 03 Klaling Village)" aims to develop a web-based application that facilitates public access to land information. In the era of information technology advancement, limited access to land information in Klaling Village is a SIGnificant problem, where people still have to visit the village office or land office manually, which is often inefficient. The research method used is the Waterfall method, which allows system development to be carried out in a structured and planned manner. The Geographic Information System (GIS) application developed in this study has succeeded in providing land ownership information online, allowing residents to search for and measure land easily. In addition, this system is expected to reduce the possibility of fraud in the shifting of land ownership rights. The results of the study show that the implementation of web-based GIS in Klaling Village increases the efficiency of access to land information. Residents can quickly and easily see the status of land ownership in their area, which reduces dependence on slow and inefficient traditional methods. The process of searching and verifying land data that previously took time can now be done online, increasing operational efficiency for all parties involved. The conclusion of this study confirms that the information system developed not only increases the accessibility of land information, but also supports better land management. Thus, this application has the potential to provide a positive impact on the community and government in making decisions related to land.

Optimasi Pemilihan Smartphone Gaming Terbaik di Kelas Menengah Menggunakan Metode Simple Additive Weighting (SAW) Berbasis Preferensi Konsumen

Samantha Arta Sinuhaji — 2024-11-25

The selection of middle-class gaming smartphones is a challenge for consumers because there are many choices with varying specifications. This research aims to help consumers make the best choice by applying the Simple Additive Weighting (SAW) method. This method is used to provide recommendations based on a number of key criteria, such as processor performance, RAM capacity, screen quality, battery life, and price. The initial step in this research is to identify the problem, which is the selection of the best gaming smartphone in the middle-class category. Next, alternatives and relevant criteria were determined, followed by data collection through a questionnaire involving 78 respondents. The data obtained was analyzed using the SAW method to determine the importance weight of each criterion and the overall ranking of each alternative. The analysis results show that Infinix ranks highest as the best choice based on the aggregate score obtained for each criterion. The SAW method allows decision making to be more systematic and objective by considering predetermined weights. The conclusion of this study confirms that a SAW-based approach can assist consumers in choosing a gaming smartphone that suits their needs and preferences. This study also provides insights for manufacturers in devising more effective marketing strategies.

Pengaruh Kinerja Portofolio Saham pada Indeks Sektoral Menggunakan Single Indeks Model

Restu Sugesti — 2024-11-25

This article tries to collect and create an optimal portfolio empirically using the single index model. Next, to evaluate portfolio and market returns using the Sharpe, Jensen, and Treynor ratios. This research is based on secondary data that has been collected from www.yahoofinance.com, www.investing.com and www.Idx.com. Taking the Composite Stock Price Index (JCI), namely as the Market Performance Index (market) and using the Sectoral Index stock group in the 2022-2024 period as the population and sample. By taking the top 5 sectors (INFRA, ENERGY, BASIC, FINANCE, and HEALTH) and considering the monthly closing prices of the top 5 stocks in their sectors between June 1, 2022 to June 1, 2024, the cut-off point (C*) has been calculated and the selected securities to build an optimal portfolio with excess returns for ERBi greater than C*(ERBi>C*). This study shows that the optimal portfolio composition is to include CUAN 55.23%, BMRI 12.83%, BBCA 9.07%, SILO 8.25%, BREN 7.33%, JSMR 7.17%, MBMA 7.03%, ISAT 3.48%, KLBF 2.99%, TPIA 2.73%, BRPT 2.43%, and SIDO 0.28% of the amount invested by each sector has its own securities in the optimal portfolio. Portfolio valuation and market returns using the Sharpe, Jensen, and Treynor ratios show lower market returns than stocks. And Sharpe's measurement has a positive portfolio return and has the highest value of 1.00929 compared to Jensen's ratio of 0.172443 and Treynor which gives the lowest return of 0.024321.