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All Journal Jurnal SPEKTRUM PROSIDING CSGTEIS 2013 JOIV : International Journal on Informatics Visualization JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Ilmiah Ilmu Sosial Scientific Journal of Informatics
Fajar Purnama
Jurusan Teknik Elektro, Fakultas Teknik, Universitas Udayana
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice

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RANCANG BANGUN APLIKASI ARISAN ONLINE DENGAN SMART CONTRACT UNTUK MEMINIMALISIR RESIKO PENIPUAN Lintin, Yosep Tara; Aditya Widhiatama, Ngakan Putu; Purnama, Fajar; Shandyasa, I Wayan; Sukadarmika, Gede; Gede Manuaba, Ida Bagus; Oka Widyantara, I Made; Juliawan Pawana, I Wayan Adi
Jurnal SPEKTRUM Vol 10 No 4 (2023): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/SPEKTRUM.2023.v10.i04.p17

Abstract

Arisan is an activity that is usually carried out by housewives where each member will donate money and at each meeting there will be a lottery to hand over the money that has been collected to one of the lucky members. Usually, arisan is done regularly and offline. However, since the pandemic in 2020, many people have started doing arisan online. With the rise of arisan online activities, there are many cases of fraud with a large amount of loss and of course it cannot be ignored. Based on these problems, a platform is needed to conduct arisan online that can prevent fraud cases. This container will be made in the form of a decentralized application by utilizing blockchain technology in this case this article utilizes smart contracts on the Binance Smart Chain to ensure that after this application is published, no party will be able to make changes to the data or functions of this application to minimize frauds.
PENERAPAN SENSOR CJMCU101 UNTUK MENDUKUNG SISTEM SMART LECTURE ROOM Maisha Putra, I Gusti Agung Ngurah; Andika Pranata, I Kadek; Paramitha Sekar Putri A.P., Ni Made; Sukadarmika, Gede; Raka Agung, I Gusti Agung Putu; Purnama, Fajar; Indra ER, Ngurah
Jurnal SPEKTRUM Vol 10 No 4 (2023): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/SPEKTRUM.2023.v10.i04.p22

Abstract

This study presents the design of a Smart Lecture Room system that utilizes light intensity sensors, specifically CJMCU101. These sensors are installed in each classroom to monitor the ambient conditions. The implementation of the designed system was carried out in the classrooms of the Udayana University Electrical Engineering Study Program. To achieve this goal, the classroom utilized by the Electrical Engineering Study Program of Udayana University was divided into two classes (DH101 and DH102) and a sensor was installed in each class as an IoT device. The IoT devices are connected to a Raspberry Pi Access Point, where the data from the sensors is stored and monitored using the Thinger.io platform. The validation of the sensor testing is carried out by comparing the results obtained from the sensors with the results obtained from a thermohygrometer measurement. This research produces a prototype smart lecture system, applied to a classroom mockup, that employs IoT devices, sensor databases, and sensor monitoring. The data from each sensor's detection is stored in the LAMP database, which employs Linux, Apache, MySQL, and PHP. The Thinger.io platform monitors the values of each sensor. A variation in accuracy between the sensor and measuring instrument results in a difference in their values. The CJMCU101 light intensity sensor has an average accuracy of 93.48% compared to the measuring instrument on DH101. The average accuracy of the sensor value compared to the measuring instrument on DH102 is 95.96%.
UNJUK KERJA KOMUNIKASI NIRKABEL HALF-DUPLEX ANTARKENDARAAN MEMANFAATKAN NRF24L01 Amanda Saraswati, Ni Putu; Indra ER, Ngurah; Purnama, Fajar
Jurnal SPEKTRUM Vol 11 No 1 (2024): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/SPEKTRUM.2024.v11.i01.p24

Abstract

This study investigates the efficacy of the affordable NRF24L01 wireless communication module in half-duplex mode for vehicle-to-vehicle (V2V) communication. The prototype integrated the NRF24L01 module with an ESP32 microcontroller and an OLED display. The study assesses the delay and packet success rate to uncover the module's attributes under half-duplex situations. This not only surpasses the mere collecting of data, but also emphasizes the practical limitations and strengths of the module. The project aims to achieve two main objectives: firstly, to gather empirical data that may be used to make well-informed decisions in the design of NRF24L01 applications, and secondly, to contribute to the broader examination of wireless communications protocols. It improves comprehension of the impact of half-duplex operation on the performance of the NRF24L01 module. By revealing the mechanics of half-duplex communication, it enhances the efficiency of NRF24L01 usage and facilitates the development of a better protocol.
RANCANG BANGUN SISTEM CHATBOT PEMESANANMENU MAKANAN DAN MINUMAN PADA RESTORAN BERBASIS TELEGRAM BOT DENGAN PENDEKATAN NATURAL LANGUAGE PROCESSING Nur Adl, Waliyin; Dwika Prihambodo, Prakoso; Care Khrisne, Duman; Arsa Suyadnya, I Made; Purnama, Fajar
Jurnal SPEKTRUM Vol 11 No 2 (2024): Jurnal SPEKTRUM
Publisher : Program Studi Teknik Elektro UNUD

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In the era of technological advancement, especially in computer and artificial intelligence (AI), there is a significant impact on various fields, including the Food and Beverage business. The use of chatbots with AI technology enables human-computer interaction in natural language, facilitating efficient ordering, information, and customer services. Chatbots are based on Natural Language Processing (NLP) and are trained using Machine Learning techniques such as Artificial Neural Networks (ANN), with TensorFlow as the main tool. This provides ease, accuracy, and efficiency in customer service. From the conducted research, NLP- based reservation chatbots perform well and receive positive feedback from users in most aspects. Keywords: Chatbot, Artificial Intelligence (AI), Artificial Neural Network (ANN), NLP
Co-Authors Aditya Widhiatama, Ngakan Putu Aji Prasetya Wibawa Alviana Ratna Malinda Amanda Saraswati, Ni Putu Andika Pranata, I Kadek Anisa Dalilah Dalilah, Anisa Duman Care Khrisne Dwika Prihambodo, Prakoso Emmy Rosiana Dewi , Ni Wayan Gede Manuaba, Ida Bagus Gede Sukadarmika I Gusti Agung Putu Raka Agung, I Gusti Agung Putu I Made Arsa Suyadnya I Made Oka Widyantara I Nyoman Gede Arya Astawa I Wayan Shandyasa Islam, Noorul Jabari, Nida Juliawan Pawana, I Wayan Adi Lingga Pratyaksa Nugraha, Anak Agung Lintin, Yosep Tara Luther Latumakulita Mairi, Vitrail Gloria Maisha Putra, I Gusti Agung Ngurah Malinda, Alviana Ratna Monicha, Windha Ngurah Indra ER Nur Adl, Waliyin Nyoman Putra Sastra Oktapiyansyah, Recky Pangidoan, Annes Maria Paramitha Sekar Putri A.P., Ni Made Putu Wira Buana Recky Oktapiyansyah Saputra, Deva Dimastawan Windha Monicha