Ahmad Rizal Dzikrillah
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Analisis Sentimen Pengguna Terhadap Kinerja Sistem Transportasi Umum Jakarta Menggunakan Algoritma Naive Bayes Muhammad Imam Santoso; Ahmad Rizal Dzikrillah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1936

Abstract

This study uses the Naive Bayes algorithm to analyze netizen sentiment regarding public transportation in Jakarta. In the past, Jakarta's public transportation system was dominated by private operators, including buses, angkot (minibuses), and taxis. However, various challenges arose, such as lack of coordination, inconsistent service quality, safety issues, and inadequate coverage. To improve the quality and availability of public transportation, local or national governments have intervened by taking over public transportation services or imposing stricter regulations on private operators. Significant investments have been made in developing public transportation modes such as TransJakarta (bus rapid transit), KRL Commuter Line (electric train), MRT (Mass Rapid Transit), Jaklingko, and other public transport services. This study aims to analyze the benefits of public transportation, which has largely been taken over by the government, to minimize existing shortcomings. The research focuses on analyzing the differing opinions spread across various social media platforms. Data was collected from social media platforms such as YouTube and X. A total of 987 data points were used in this study, with 612 positive and 375 negative data points. After conducting the research, an accuracy of 94.22% was achieved. The analysis revealed significant variations in sentiment among netizens regarding public transportation in Jakarta. Some groups of netizens have begun to feel positive effects from the current integration of public transportation, but there are still execution shortcomings. The analysis also identified key factors influencing differing opinions, such as user areas, the uneven distribution of drivers with good personal qualities, and the economic conditions of the community. Consequently, this study contributes to sentiment analysis and natural language processing by applying problem-solving procedures to classify netizen comments on various platforms. The results of this study indicate that the Naive Bayes algorithm can be used to classify netizen sentiment about public transportation in Jakarta with a high level of accuracy. These findings can be useful for the government and Jakarta residents in finding solutions to these issues. Thus, this study can serve as a basis for a more comprehensive understanding of the government's response to public transportation issues in Jakarta.
Rancang Bangun Sistem Website Jago-Investasi Sebagai Pembelajaran Berinvestasi Mahasiswa Uhamka (Fakultas Ekonomi Dan Bisnis) Rifqi Favian Hibatullah; Ahmad Rizal Dzikrillah; Pandu Fahrizal; Dafa Setyo Nugroho
Prosiding Seminar Nasional Teknoka Vol 9 (2024): Proceeding of TEKNOKA National Seminar - 9
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/teknoka.v9i1.17557

Abstract

By studying investment, it will make a significant impact on future economic development, both or individually. Even so, there are not a few students who are less fond of and active in studying investment because of system that making students easily distorted by other content. With advances technology, using website as learning media is a powerfull way to attract students to study investment materials. “Jago-Investasi” website aims to develop investment skills, especially for stundents of Faculty of Business and Economy Universitas Muhammadiyah Prof. Dr. HAMKA (UHAMKA), so that students can easily take advantage of this website as learning material that focuses on investment without distortion while studying materials. The Design method used in this design is waterfall, there are four stages required, namely Requirements Analysis, System Design, Implementation and Testing. With the "Jago-Investasi" website, the result provided is a learning platform for students to access materials related to investment with achieving a success rate of over 70%.
Analisis Sentimen Terhadap KPU 2024 Berdasarkan Tweet Media Sosial Twitter Menggunakan Algoritma Naïve Bayes Dion Parisda Ray; Firman Noor Hasan; Ahmad Rizal Dzikrillah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 4 (2024): Februari 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i4.1587

Abstract

The development of technology is currently very rapid making the dissemination of information faster, the dissemination of information is very easy to get on social media such as Twitter. Twitter social media itself provides features for its users to be able to send and read information in the form of text or video. Elections are a very important moment for the Indonesian people in choosing leaders, in this case the "2024 KPU" as the organizer is expected to be able to run the elections so that they run well. Twitter data collected with the keyword "KPU 2024" obtained a total of 3057 datasets, followed by a cleansing process which produced 715 datasets. The aim of this research is to find out how many positive and negative tweets comments and to indicate the accuracy of the implementation of the Naïve Bayes method. The accuracy results given by the Naïve Bayes algorithm are 67.13% with a precision of 66.04% and a recall of 100.00%. This research was conducted to see public sentiment towards the "2024 KPU" later. Evaluation results in the confusion matrix obtained true positives of 457 and true negatives of 235