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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer INFOKUM Jurnal Pengabdian Kepada Masyarakat Bulletin of Information Technology (BIT)
Dian Noviandri
Universitas Medan Area
Arts Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Nursing Public Health Social Sciences Veterinary Other

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Upaya Peningkatan Kemampuan Penggunaan Microsoft Access Programming Bagi Pegawai Unit Usaha Bank Sumut Syariah Dian Noviandri; Indra Hermawan; Agnita Yolanda; Fahmi Sulaiman
PaKMas: Jurnal Pengabdian Kepada Masyarakat Vol 2 No 1 (2022): Mei 2022
Publisher : Yayasan Pendidikan Penelitian Pengabdian Algero

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54259/pakmas.v2i1.822

Abstract

This training aims to improve the ability to use microsoft access programming for employees of the Bank Sumut Syariah business unit. This training was attended by all employees because this training is considered very important to support the performance of the employees. Currently, the Bank Sumut Syariah business unit has implemented technology based on Microsoft Access Programming in the context of carrying out all office activities. This training is carried out by means of socialization to employees, discussions, training and also direct practice of its use. The service activities for the Microsoft Access Programming Training have been carried out well. The service activity for the Microsoft Access Programming Training received an enthusiastic response from the participants of the Bank Sumut Syariah unit employees. Microsoft Access Programming training is carried out in stages and distributed in 14 meetings with a student center learning system and project based learning model so that employees can solve work problems with the skills that have been taught. Microsoft Access is a relational computer database application program that is used to design, create and process various types of data with large capacities. Database is a collection of related tables. Between tables with one another are related to each other, so it is often called a relational database. The relations between tables are connected by a key, namely the primary key and foreign key
Perancangan Teknologi Embedded System Deteksi Kebocoran Gas dan Api berbasis Internet of Things Dian Noviandri
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 6 No. 3 (2022): Volume 6 Nomor 3 Agustus 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v6i3.11619

Abstract

Penelitian berdasarkan hasil observasi di dapur yang menggunakan gas sebagai bahan bakar untuk memasak, untuk mendeteksi kebocoran gas hanya mengandalkan indera penciuman saja, apabila kebocorn terjadi di malam hari maka dapat menimbulkan kebakaran akibat kebocoran gas yang mengkaibatkan kebakaran. Tuujuan penelitian ini merancang teknologi embedded system pendeteksi kebocoran gas dan api yang disebabkan gas, yang dapat memberikan peringatan dini kebocoran dan kebakaran yang disebabkannya berbasis Internet of Things. Metode yang digunakan Rapid Application Development (RAD) dengan langkah a.definisikan kebutuhan alat, membuat rangcangan/model alat, mengerjakan alat sesui saran/perbaikan prototipe oleh pengguna dan penyelesaian proyek. Hasil penelitian sebuah rancangan alat embedded system pendeteksi kebocoran gas dan deteksi api berbasis IoT yang mampu secara aktif menutup tabung gas dengan handuk/kain basah dam menyiram api yang disebabkan oleh percikan gas serta mengirimkan pesan ke pemilik dapur bahwa terjadi kebocoran gas atau api terdeteksi. Kesimpulan Ala Embedded System berhasil dirancang untuk keperluan deteksi kebocoran gas dan api.
Implementation of IOT on Laboratory Door Security System Using Dian Noviandri; Rizaldy Khair
INFOKUM Vol. 10 No. 4 (2022): October, computer, information and engineering
Publisher : Sean Institute

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

Abstract

The door security system using RFID is one of the many systems that can be used to increase the level of security on the doors of houses, classrooms, warehouses and so on. The door security system uses RFID as a medium to read or identify so that the door can open. It uses a relay as a link and breaker of electric current that is flowed to the load (Solenoid Door Lock). It uses LCD as a notification whether RFID successfully identifies what not. When RFID identifies the card and the condition of the card that the RFID reads successfully then the LCD will pop up the text "WELCOME LAB IOT" and the Solenoid will open. After a few seconds then the solenoid will lock again. Conversely, When RFID identifies the card and the condition of the card read RFID is not successfully detected then the LCD will pop up the text "PLEASE TRY AGAIN" and the Solenoid will remain locked. If during the RFID card reading process there is a failure 3 times, the Buzzer will sound and the LCD will display the text "YOU ARE NOT REGISTERED".
The Expert System of Determining the Type of Malaria by using Dempster-Shafer Method Ronal Maruli Marusaha; Dian Noviandri; Andre Hasudungan Lubis
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.887

Abstract

Malaria is the most dominant disease in Asia and Africa and may become a life-threatening disease for it suffers. The types of malaria such as Plasmodium Vivax, Plasmodium Ovale, Plasmodium Malariae, and Plasmodium Falciparum are mostly infected people around the world. These types of malaria have certain symptoms that drives difficulties for some patients to confirm which malaria that their infected. A clinical testing and medical diagnostic assessments may be performed to determine the types of malaria, but utilizing a system also brings some benefits for rural areas which lack of medical facilities. The study develops a system by implementing the Dempster Shafer method to determine types of malaria. We collected the knowledge from the experts including 18 possible symptoms along with the density value. This paper present 5 cases of sufferers and provide the system result with the possibilities of malaria types. The result pointed out a various percentage of malaria types that may infected to the patients.
Analysis of The Multilayer Perceptron Algorithm on Twitter User’s Sentiment Towards The COVID-19 Vaccine Fordinand Halomoan Pasaribu; Nurul Khairina; Dian Noviandri; Susilawati Susilawati; Rahmad Syah
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.9664

Abstract

The World Health Organization (WHO) declared COVID-19 a global pandemic due to its rapid spread and infection of people worldwide. The emergence of COVID-19 vaccines has garnered both support and rejection from the public. Some people support the vaccines, while others remain cautious, even though the government provides them for free. The procurement of coronavirus vaccines has generated diverse opinions in society. COVID-19 vaccines have become a trending topic on social media, particularly on Twitter. This research aims to explore public opinions on the COVID-19 vaccine. The methods used in this study include data collection, text preprocessing, TF-IDF, multilayer perceptron algorithm, and testing with confusion matrices. Out of a total of 228,208 positive, negative, and neutral opinions from Twitter users about the COVID-19 vaccine, with a training-to-testing ratio of 90% to 100%, the model will learn more by using a large amount of training data. The performance results of this research obtained the highest accuracy of 81.2%, precision of 83.8%, and recall of 71.2%. The results of sentiment analysis can be seen in the public opinions on the COVID-19 vaccine, which are divided into three categories: 35% positive opinions, 16.3% negative opinions, and 48.7% neutral opinions. The word cloud results show that positive opinions revolve around three topics: availability, cost, and dosage. Negative opinions from Twitter users about the COVID-19 vaccine focus on two main issues: vaccine side effects and deaths. Neutral opinions cover three topics, including dosage, availability, age, and expiration date
Co-Authors Agnita Yolanda Andre Hasudungan Lubis Fahmi Sulaiman Fordinand Halomoan Pasaribu Indra Hermawan Nurul Khairina Rahmad B.Y Syah Rizaldy Khair Ronal Maruli Marusaha Susilawati Susilawati