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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic JSI: Jurnal Sistem Informasi (E-Journal) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Teknik Komputer AMIK BSI Cakrawala : Jurnal Humaniora Bina Sarana Informatika Paradigma Bina Insani ICT Journal Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Infortech Jurnal Inovasi Informatika RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Bulletin of Computer Science Research Computer Science (CO-SCIENCE) Reputasi: Jurnal Rekayasa Perangkat Lunak Informatics and Computer Engineering Journal SATIN - Sains dan Teknologi Informasi Jurnal Komputer Antartika Information Technology and Systems
Yopi Handrianto, Yopi
Universitas Bina Sarana Informatika
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Library & Information Science Social Sciences Other

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Metode Technology Acceptance Model (TAM) Dalam Analisis Tingkat Kepuasan Pengguna Transportasi Umum Terhadap Aplikasi TJ : Transjakarta handrianto, yopi; Saputra, Ilham Thomas
Reputasi: Jurnal Rekayasa Perangkat Lunak Vol. 6 No. 1 (2025): Mei 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/reputasi.v6i1.8488

Abstract

Abstract - Transjakarta is the first Bus Rapid Transit (BRT) transportation system in Southeast and South Asia managed by PT Transportasi Jakarta. Some time ago, in an event PT Transportasi Jakarta issued a new innovation, namely the TJ : Transjakarta. The purpose of this study is to analyze how the level of satisfaction of public transportation users with the TJ : Transjakarta application. The research problem approach used is the technology acceptance model (TAM) model with the variables used are Perceived ease of Use, Perceived Uselfulness, Actual System Usage, Behavioral Use and Attitude Toward Using. The data collection method used is a questionnaire distributed via Google Form. The results of the questionnaire were processed using SPSS 30.0. From the results of data analysis that has been done, it is concluded that the Perceived Ease of use variable has the most significant influence on user satisfaction. Based on the results of the simultaneous analysis, it shows that the variables Perceived Ease of use (X1), Perceived Usefulness (X2), Behavioral Intention to Use (X3), and Actual System Usage (X4) simultaneously positively affect Attitude Toward Using (user satisfaction) (Y) with a percentage level of influence of 67.1%. This means, there is an influence on the satisfaction of public transportation users who use the TJ : Transjakarta application. Keywords : Technology Acceptance Model (TAM), User Satisfaction, TJ : Transjakarta
Optimasi Algoritma Naïve Bayes Berbasis Particle Swarm Optimization Untuk Klasifikasi Status Stunting Pahlevi, Omar; Amrin, Amrin; Handrianto, Yopi
Computer Science (CO-SCIENCE) Vol. 4 No. 1 (2024): Januari 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i1.2963

Abstract

Every parent wants their children to grow up healthy. Eating a healthy diet can minimize stunting. Long-term nutritional deficiencies can lead to stunting, a chronic nutritional problem that impairs physical growth and development, including low body weight and height. Preventive action against stunting is a fundamental activity that must be done immediately in the form of counseling and taking further medical action.  In data mining there are several methods for extracting information including classification. There are various methods for extracting information using data mining, such as classification. In this research, researchers will apply Naïve Bayes with Particle Swarm Optimization (PSO) for the classification of stunting status in order to determine whether a child has a case of stunting or not based on gender, age, birth weight, body weight, body length, and breastfeeding. In the final results of the research, it is known that the accuracy of the truth obtained through the performance of the Naïve Bayes algorithm model is 80.69% and a score of 0.801 resulting from Area Under the Curva (AUC). Then based on the calculation results with the Naïve Bayes algorithm model with Particle Swarm Optimization, it can be obtained a truth accuracy rate of 83.06% with an Area Under the Curve (AUC) value of 0.801. Based on the final value obtained, the pattern of applying Particle Swarm Optimization to the Naïve Bayes algorithm can improve the performance of the classification method used in this research activity.
Co-Authors Achmad Nurhadi Ade Christian Adjat Sudradjat Ahmad Sinnun Alamul Huda, Alamul Aldo Priamnistiko Ali Haidir AlWafi, Muadz Zidan Amrin Amrin Amrin Amrin Anastasiaa Siwi Fatma Utami Andi Nugroho Budi Sanjaya Budi Waluyo Dewi Ayu Nur Wulandari Eka Wahyu Styani Fajar Arrizky Syuhada Ghofar Taufiq Hadi Sukmana, Sulaeman Hariyanto Harna Govin Pratama Henny Destiana Henny Leidiyana Karlena Indriani Latifa, Nurul Robiatul Luci Kanti Rahayu Maisyaroh Muflih, Dzaky Fallah Muhamad Raka Fadilah Muhammad Farhan Muhammad Fatkhul Munir Muhammad Hamdan Sukri Noval, Qibran Omar Pahlevi Pamungkas, Jarseno Panjaitan, Leo Fernando Phindika, Phindika Pratama, Lutfi Fadillah Rusdiansyah Rusdiansyah Santiyana Yulia Santoso Setiawan Saputra, Ilham Thomas Sri Radhitya Murti Mahening Suhar Janti Sutisna, Alifan Widad Tuslaela Wahyu Styani, Eka