Nina Sevani
Universitas Kristen Krida Wacana

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Pemanfaatan Mean Stack Dalam Digitalisasi Administrasi Tugas Akhir Menggunakan Kombinasi Iteratif dan Scrum Model Nina Sevani; Rita Wiryasaputra; Jeremy Wijaya; Vini Janti Anggelica
Jurnal Ilmiah FIFO Vol 14, No 1 (2022)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2022.v14i1.002

Abstract

Citra suatu organisasi tercermin dari baiknya penyusunan administrasi organisasi yang melibatkan kepemimpinan, kebijakan, dan hubungan antar manusia. Kegiatan administrasi mencakup kegiatan pengendalian informasi yaitu tulis menulis/mencatat, menggandakan, menyimpan, dimana kegiatannya bertransformasi menjadi lebih praktis dan transparansi pada era digitalisasi. Program studi sebagai bagian dari perguruan tinggi menghadapi kompleksitas administrasi Tugas Akhir (TA) mahasiswa yang menimbulkan beberapa permasalahan antara lain human error, keberagaman formating berkas, komunikasi panjang dan koordinasi bertingkat antar unsur dalam perguruan tinggi jika proses administrasi tersebut dikerjakan secara manual. Permasalahan berdampak pada terganggunya pengambilan keputusan.  Akan tetapi hal tersebut dapat diminimalisir dengan pendigitalisasian administrasi TA mahasiswa berbasis web dengan teknologi MEAN (MongoDB, Express, Angular, dan NodeJS) stack menggunakan metodologi kombinasi antara Traditional Iterative model dengan Scrum model.  Pemanfaatan modern teknologi MEAN STACK mengakomodir administrasi TA sebagai sebuah SPA (Single-Page Application) yang menggunakan  bahasa pemrograman JavaScript baik dari client-side maupun server-side. Upaya ini dilakukan agar perangkat lunak yang dihasilkan dapat lebih adaptif atas perubahan sistem, namun biaya pengembangan terjangkau dan pengendalian dapat dilakukan pada setiap tahap secara transparan dalam sebuah tim kerja kecil.
Web-Based Expert System to Detect Stress on College Students Grensya Bella Vega Persulessy; Nova S Pratama; Novianti Setiawan; Nina Sevani
ComTech: Computer, Mathematics and Engineering Applications Vol. 10 No. 1 (2019): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v10i1.4987

Abstract

This research aimed to make the application to detect stress for the college students. By early detecting stress on college students, it could help them to cope with their stress and avoid the negative impact of the stress. The Holmes-Rahe Readjustment Rating Scale was used to detect stress based on student’s life events. Each event had its score. There were 31 questions provided by the system. The final score would conclude the stress categories. Using the Forward Chaining Inference Engine, the system would collect the fact of the student’s life and give the result by accumulating scores on questions posed to the users from every question. The system also provided the reminder feature that led to continuous monitoring of stress condition in the students. About 65 correspondents who were selected using random sampling were asked to fill out questionnaires regarding this system after they tried the application. With the continuous monitoring, the researchers find that this system gives a result that all users have decreased their score of stress levels. Moreover, the correspondents rate that the design of the application is good enough, and the system is interesting and useful for helping students to provide a solution for stress.
IMPLEMENTASI FORWARD CHAINING UNTUK DIAGNOSA DEFISIENSI VITAMIN LARUT DALAM LEMAK BERBASISKAN WEB Nina Sevani; Melvin Joshua
Jurnal Informatika Vol 10, No 2 (2014): Jurnal Teknologi Komputer dan Informatika
Publisher : Universitas Kristen Duta Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (15478.48 KB) | DOI: 10.21460/inf.2014.102.293

Abstract

The growth of information technology is increasing lately. People can get the actual information from websites. The combination between website and expert system will help people to make an application that can think like an expert and spread it all around the world using the internet. The technology can be used to solve the availability problem of expert nutrient in Indonesia. The application was developed using forward chaining method as the inference system. It will make the application work like a nutrient expert, which asks the patient from general to specified symptoms. The knowledge based of the application was collected from trusted resources like nutrient experts and nutrient books. The application was tested by the nutrient expert. The result shows that the application can work properly like an expert.
Peningkatan Pola Berpikir Komputasi pada Siswa/i SMAK MATER DEI Melalui Bahasa Pemrograman Java dan Python Rita Wiryasaputra; Albert Salomo; Nina Sevani; Seruni
Servirisma Vol. 2 No. 2 (2022): Servirisma : Jurnal Pengabdian kepada Masyarakat
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) Universitas Kristen Duta Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (949.039 KB) | DOI: 10.21460/servirisma.2022.22.28

Abstract

In this industrial era 4.0, the development of science, especially in the field of technology and information is growing rapidly. This requires every level of education in Indonesia to prepare students to move into the world of technology. Therefore, students must be equipped with an understanding of Computational Thinking (CT). CT is a method to train solving problems using several techniques in the field of computer science and informatics. With the application of CT, students are trained to think gradually, systematically, and creatively using computers and the internet. Through the application of this teaching, it’s hoped that it can advance the thinking of every student in Indonesia so that they can compete in the world of work later. Therefore, the Informatics Study Program, Faculty of Engineering and Computer Science, Krida Wacana Christian University, cooperates with SMAK Mater Dei by holding programming training in the form of extracurricular activities. This training takes place from 10 August 2021 to 9 November 2021. The training was held in 10 meetings which were divided into 3 phases, planning, implementation, and evaluation (finalization). The programming material includes Greenfoot IDE and Python programming language using several teaching methods. The measurement of student abilities will be tested using a pre-test and post-test model using several indicators. The assessment indicator used are the understanding of the algorithms and the ability to create simple programs using Greenfoot and Python. The training went well and students' understanding of Computational Thinking improved after the program was held.