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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Jurnal Teknik Informatika UNIKA Santo Thomas Journal of Technopreneurship and Information System (JTIS) Journal of Computer System and Informatics (JoSYC) Jurnal Kajian Ilmiah Jurnal Sistem Informasi Journal of Students‘ Research in Computer Science (JSRCS) Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) J-Shelves of Indragiri (JSI)
Nani Agustina - AMIK BSI Jakarta, Nani Agustina
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences

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Algoritma Naive Bayes untuk Prediksi Keberhasilan Mahasiswa pada Mata Kuliah Praktikum Sutinah, Entin; Agustina, Nani; Martini, Martini
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 8 No. 2 : Tahun 2023
Publisher : LPPM UNIKA Santo Thomas

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Abstract

The lecture system at BSI University has practicum courses, where the teaching and learning process is 20% theory and 80% practicum by learning software according to current technological developments. In the practicum-based teaching and learning process, there are several problems including understanding the content of the material delivered by the lecturer, communication between students in class and lecturers because there are many discussions, in practicum learning made in groups to make projects, this group cohesiveness is also an assessment in achieving predetermined targets, the learning atmosphere also supports the teaching and learning process, the process of lecturer assessment of students will be the final result of learning and teaching activities. In the practicum course, 4 credits are provided and this 4 credits time is still considered insufficient to complete quite a lot of material at each meeting, from these problems the author wants to know the prediction of student success rates in practicum course learning. This study uses the naive bayes method with a total sample of 130 samples from the results of a questionnaire distributed to students with 20 questions, so that this study results in that students feel successful in practicum course learning with an accuracy level of 100%, a precision level of 100%, and a recall level of 100% after being processed using rapidminer 5 software.
Algoritma Naive Bayes untuk Prediksi Keberhasilan Mahasiswa pada Mata Kuliah Praktikum Sutinah, Entin; Agustina, Nani; Martini, Martini
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 8 No. 2 : Tahun 2023
Publisher : LPPM UNIKA Santo Thomas

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

Abstract

The lecture system at BSI University has practicum courses, where the teaching and learning process is 20% theory and 80% practicum by learning software according to current technological developments. In the practicum-based teaching and learning process, there are several problems including understanding the content of the material delivered by the lecturer, communication between students in class and lecturers because there are many discussions, in practicum learning made in groups to make projects, this group cohesiveness is also an assessment in achieving predetermined targets, the learning atmosphere also supports the teaching and learning process, the process of lecturer assessment of students will be the final result of learning and teaching activities. In the practicum course, 4 credits are provided and this 4 credits time is still considered insufficient to complete quite a lot of material at each meeting, from these problems the author wants to know the prediction of student success rates in practicum course learning. This study uses the naive bayes method with a total sample of 130 samples from the results of a questionnaire distributed to students with 20 questions, so that this study results in that students feel successful in practicum course learning with an accuracy level of 100%, a precision level of 100%, and a recall level of 100% after being processed using rapidminer 5 software.
Penerapan Metode MOORA Pada Sistem Pendukung Keputusan Pemilihan Aplikasi Dompet Digital Agustina, Nani; Sutinah, Entin
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Vol 6, No 2 (2022): InfoTekJar Maret
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/infotekjar.v6i2.5012

Abstract

Suatu sistem yang dapat menentukan peringkat dengan cepat dalam proses seleksi dan mengetahui nilai tertinggi serta terendah dari suatu masalah yang terjadi bisa diartikan dengan Sistem pendukung keputusan. Pada penelitian ini menggunakan sistem pendukung keputusan untuk menyelesaikan studi kasus dalam menentukan keputusan pemilihan dompet digital yang digunakan sebagai alat pembayaran pada transaksi pembelian dikalangan mahasiswa Universitas BSI program studi Administrasi Bisnis dan Administrasi Perkantoran, dimana banyaknya dompet digital yang bisa digunakan oleh mahasiswa dengan banyaknya penawaran-penawaran yang menarik sehingga membuat bingung dalam memilih dompet digital yang efektif dan efisien untuk kalangan mahassiwa. Oleh karena itu dibuat suatu sistem yang dapat digunakan untuk mendukung keputusan tersebut dengan menggunakan empat kriteria yang digunakan yaitu kerjasama merchant, promo dan penawaran menarik, layanan customer service serta kemudahan aplikasi dalam membantu proses penentuan pemilihan dompet digital. Dimana sistem pendukung keputusan ini menggunakan metode MOORA berdasarkan nilai bobot kriteria yang sudah ditentukan. Pada penelitian ini dihasilkan pemilihan dompet digital dikalangan mahasiswa sesuai peringkat dalam penelitian yaitu GoPay, ShopeePay, OVO, Dana, dan LinkAja.
Implementasi Internet of Things (IoT) pada Sistem Pemantauan Kelembapan Udara di Perpustakaan UBSI Anwar, Rian Septian; Agustina, Nani; Indriyani, Novita
Journal of Students‘ Research in Computer Science Vol. 6 No. 2 (2025): November 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/3c074h77

Abstract

Libraries, particularly academic libraries like those at UBSI, store valuable collections of books, manuscripts, and digital archives. The preservation of these physical assets is constantly threatened by environmental factors, primarily fluctuating temperature and humidity. Uncontrolled high humidity accelerates the growth of mold and mildew, leading to irreversible damage to paper-based materials. Manual monitoring systems are often inefficient, costly, and susceptible to human error. This research aimed to develop and implement a real-time, Internet of Things (IoT)-based air humidity monitoring system to ensure optimal environmental conditions for collection preservation in the UBSI Library. The system utilizes the NodeMCU ESP8266 microcontroller and the SHT30 sensor, chosen for its high accuracy and stability, to continuously collect humidity data. This data is transmitted via Wi-Fi to a Firebase real-time database and visualized on a dynamic web dashboard. The prototype was tested for accuracy and reliability, showing minimal deviation (less than 3%) compared to commercial hygrometers. The results confirm that the IoT system successfully provides remote, continuous, and highly accurate monitoring, enabling prompt intervention by library staff when humidity levels exceed the safe threshold (50%–60%). This innovative approach significantly enhances collection preservation efficiency and reduces potential conservation costs. The system built not only successfully collects data, but also processes it into easily understood information, thus fulfilling the initial objective of overcoming the inefficiency of manual monitoring.
Co-Authors Amri, Samsul Asmoro, Randi Ashar Barkah, Novalia Dian Utami, Dian Entin Sutinah, Entin Huda, Inda Sofiatul Martini Martini Mustajib, Agus Novita Indriyani Rian Septian Anwar Sya’Roni