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All Journal Jurnal Mantik Penusa Jusikom: Jurnal Sistem Informasi Ilmu Komputer Journal of Informatics Management and Information Technology
Fitriani, Pristiwati
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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SISTEM PENDUKUNG KEPUTUSAN PEMBELIAN SMARTPHONE ANDROID DENGAN METODE MULTI ATTRIBUTE UTILITY THEORY (MAUT) Fitriani, Pristiwati
Jurnal Mantik Penusa Vol 4, No 1,Jun (2020): MANAJEMEN DAN INFORMATIKA
Publisher : Pelita Nusantara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (650.231 KB)

Abstract

Buying a smartphone is very coveted among the people, many models and types of smartphones of various brands confuse people to buy a smartphone that requires new knowledge to solve the problem. The method used in this research is a literature study of various smartphone prices starting from the website and local prices. The criteria used are price, memory space, Ram space and smartphone advantages. The results of this study show that smartphones are the best of various smartphones. with this the purchase of a smartphone can be done computationally using the Multi-Attribute Utility Theory (MAUT) method. MAUT method is a decision method to make the results more precise based on the attributes and criteria that are with the system utility. Furthermore, this method has features of the compensation method. attributes are independent of each other and qualitative attributes are transformed into quantitative attributes.Key Words : Decision Support System, Android Smartphone Purchase, Multi-Attribute Utility Theory (MAUT)
Sistem Monitoring Dan Deteksi Dini Terjadinya Gempa Berbasis Iot (Internet Of Things) Fatimah, Fitri; Abdy, Sahara; Ramadhany, Sri; Fitriani, Pristiwati; Afifudin
Journal of Informatics Management and Information Technology Vol. 5 No. 1 (2025): January 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i1.472

Abstract

Designing and developing systems capable of monitoring ground tremors in real-time and providing early warning before major earthquakes occur, increasing speed and accuracy in detecting potential earthquakes. This technology is known as an Internet of Things (IoT)-based earthquake monitoring and early detection system that uses motion sensors. To detect seismic activity, the system uses several motion sensors connected to the Internet of Things network. These motion sensors measure changes in ground vibration and transmit the data to a central server, which will process it to detect possible earthquakes. This research uses a methodology consisting of several stages. First, primary data is collected from motion sensors located in various earthquake-prone locations. This data is sent to a central server over the internet network. Furthermore, digital signal processing algorithms are used to analyze data to distinguish normal ground tremors from those that can signal earthquakes. This algorithm was created to identify suspicious changes in the intensity and frequency of ground vibrations. The system then sends a warning or notification to the user's device, such as a smartphone or computer, if a potential earthquake is detected. According to BMKG (Meteorology, Climatology, and Geophysics Agency) Earthquake intensity scale (GIS) states the impact caused by earthquakes. This scale is arranged more simply by having only five levels, namely I-V, where each level has its own meaning, level I is marked with white and level II is marked with green and level III is marked with yellow and level IV is marked with orange and the last level V is marked with red, and each level has its own meaning. The results show that the designed system can detect vibrations with high accuracy and provide early warning within seconds after suspicious seismic activity is detected. In addition, this system has a speed of sending data from the sensor to the server and good performance in the use of the internet network. IoT-based motion sensors allow for broader and decentralized monitoring of earthquakes. So, this Internet of Things-based earthquake monitoring and early detection system can be a good solution to improve earthquake disaster preparedness. By applying these technologies in different earthquake-prone areas, they can help spread and respond to potential earthquakes more quickly
ANALISIS TEKNIKAL UNTUK PREDIKSI PORTOFOLIO SAHAM YANG OPTIMAL DENGAN MENGGUNAKAN BAYESIAN NETWORK Fitriani, Pristiwati
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 1 (2019): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1064.685 KB) | DOI: 10.34012/jusikom.v3i1.481

Abstract

Pengambilan keputusan bagi investor untuk melakukan investasi pada saham selalu mempertimbangkan faktor perolehan dan risiko. Risiko diidentifikasikan dengan ketidakpastian. Bayesian Network dapat dijelaskan sebagai Diagram Asiklik Grafik (DAG) yang mendefinisikan faktorisasi distribusi probability bersama atas variabel yang diwakili oleh node dari DAG. Bayesian Network telah digunakan untuk data mining model grafis yang membuat hubungan probabilistik antara variabel interest, teknik statistik, model grafis yang memiliki beberapa keuntungan bagi pemodelan data. Bayesian Network dapat menyelesaikan masalah prediksi portofolio saham berdasarkan analisis teknikal untuk basis data yang bersifat statistik. Penerapkan metode Bayesian Network untuk menentukan portofolio saham yang optimal dapat mengetahui kapan sebaiknya melakukan transaksi jual dan beli. Kata kunci : Bayesian Network, Saham, Portofolio, Pemodelan Data.
Co-Authors Abdy, Sahara Afifudin Fitri Fatimah, Fitri Ramadhany, Sri