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Go Story: Design and Evaluation Educational Mobile Learning Podcast using Human Centered Design Method and Gamification for History Biabdillah, Fajerin; Tolle, Herman; A. Bachtiar, Fitra
Journal of Information Technology and Computer Science Vol. 6 No. 3: December 2021
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (889.512 KB) | DOI: 10.25126/jitecs.202163345

Abstract

Technological developments, especially in the field of education, can help students learn more effectively and help the learning process. The learning method used in high school for history learning still uses conventional methods. The use of this conventional method often experiences problems such as students being less motivated in learning. One of the solutions proposed in this article is to design an android-based learning media that can support the activities of the learning process named go-story. Interface design for students as application users and (UI/UX) based on human centered design methodology and the concept of gamification. The human centered design approach and the concept of gamification will be used in the analysis and design process to maximize the usability and engagement of the application. The application will be implemented and tested on students to measure its effectiveness. The trials that have been carried out show the results of improvements
GROWTECH: PENYIRAMAN OTOMATIS BERBASIS INTERNET OF THINGS (IOT) MENGGUNAKAN NODEMCU V3 ESP8266 Ramadhan, Muhammad Cahyo Putra; Biabdillah, Fajerin; Wajiansyah, Agusma
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3S1 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3S1.7931

Abstract

Penelitian ini merancang dan mengimplementasikan sistem GrowTech berbasis Internet of Things (IoT) dengan NodeMCU V3 ESP8266 untuk meningkatkan efisiensi penyiraman tanaman. Sistem mengintegrasikan sensor kelembapan tanah, sensor suhu DS18B20, dan sensor kelembapan udara DHT11 yang terhubung ke aplikasi Blynk melalui Wi-Fi. Hasil pengujian menunjukkan sistem mampu memantau kondisi lingkungan tanaman secara real-time dan mengendalikan pompa air otomatis ketika kelembapan tanah turun di bawah 40%, serta menghentikan penyiraman saat mencapai 60–70%. Respon manual melalui aplikasi memiliki keterlambatan rata-rata hanya 1,2 detik. Implementasi pada skala rumah tangga terbukti efektif dalam mengurangi pemborosan air dan risiko kelebihan penyiraman. Potensi pengembangan diarahkan pada integrasi penyimpanan data berbasis cloud, algoritma prediksi kebutuhan air, serta penerapan pada skala perkebunan untuk mendukung pertanian cerdas dan berkelanjutan.
Perancangan dan Implementasi Fuzzy Inference System (FIS) Metode Tsukamoto pada Penentuan Penghuni Asrama Syahidi, Aulia Akhrian; Biabdillah, Fajerin; Bachtiar, Fitra Abdurrachman
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 6 No 1: Februari 2019
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3214.757 KB) | DOI: 10.25126/jtiik.2019611228

Abstract

Asrama mahasiswa dibangun sebagai tempat tinggal bagi sekelompok orang yang sedang manjalankan suatu tugas atau kegiatan yang sama. Untuk menentukan mahasiswa yang berhak menjadi penghuni asrama, maka dalam penelitian ini memberikan rekomendasi untuk menggunakan Metode Fuzzy Tsukamoto. Metode Fuzzy Tsukamoto dipilih karena ada beberapa kelebihan yang menonjol yaitu dapat mendefinisikan nilai yang kabur dari inputan penilaian, dapat membangun, dan mengaplikasikan pengalaman-pengalaman para pakar secara langsung tanpa harus melalui proses pelatihan. Hasil analisis menyimpulkan bahwa: (1) Cara kerja Metode Fuzzy Tsukamoto memiliki tiga bagian yaitu: fuzzifikasi, inferensi fuzzy, dan defuzzifikasi, (2) Implementasi Metode Fuzzy Tsukamoto dapat menghitung penentuan penerimaan penghuni asrama mahasiswa pada studi kasus asrama mahasiswa putera “Negara Dipa Amuntai Malang”, berdasarkan 19 data dengan membandingkan antara hasil penilaian pakar, hasil perhitungan Fuzzy Tsukamoto secara manual, dan hasil perhitungan Fuzzy Tsukamoto secara otomatis menggunakan sistem yang terprogram, telah diuji mempunyai tingkat akurasi keberhasilan sebesar 63.15% dengan predikat cukup. AbstractStudent dormitory is built as a residence for a group of people who are carrying out a task or the same activity. To determine the students who have the right to become boarders, in this study provide recommendations for using the Fuzzy Tsukamoto Method. Fuzzy Tsukamoto method was chosen because there are several prominent advantages that can define the value that is blurred from the assessment input, can build, and apply the experiences of experts directly without having to go through the training process. The results of the analysis concluded that: (1) The workings of the Fuzzy Tsukamoto Method have three parts: fuzzification, fuzzy inference, and defuzzification. (2) The implementation of the Fuzzy Tsukamoto method can calculate the determination of the admission of students in the student dormitory case study of male student dormitory “Negara Dipa Amuntai Malang,” based on 19 data by comparing the results of the expert assessment, the results of Fuzzy Tsukamoto calculation manually, and the results of Fuzzy Tsukamoto calculations automatically using a programmed system, has been tested to have a success accuracy level of 63.15% with sufficient predicate. 
Designing a Web Application for Recognizing Past Learning Using the Laravel Framework Jaya, Arsan Kumala; Hanif, Abdullah; Triadi, Fara; Biabdillah, Fajerin
Journal of Mathematics and Applied Statistics Vol. 2 No. 2 (2024): December 2024
Publisher : Yayasan Insan Literasi Cendekia (INLIC) Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35914/mathstat.v2i2.239

Abstract

This study aims to provide information on the application design process using the Laravel framework. This study aims to design a web application that can help higher education institutions manage students who take prior learning recognition (RPL) classes effectively and efficiently. The problem often faced by universities is the difficulty in recording the formal/non-formal education history of RPL students. This application is expected to provide a solution by providing features such as recording education history, training history, conference history, award history, organizational history, and employment history. The system development method used in the design is the System Development Life Cycle (SDLC) by utilizing the Laravel framework as a framework for the system development process. The expected results of this study are a web application that is user-friendly, reliable, and able to increase the efficiency of student data collection in universities.
Impulsive Purchase with Vision Transformer Prediction of Vehicular Perception System for Fast-Food Outlets in Urban Traffic Congestion Biabdillah, Fajerin; Ismayanti, Rika; Hartanto, Subhan; Jaya, Arsan Kumala
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 8 No. 4 (2025): October
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v8i4.53140

Abstract

Urban traffic congestion creates a unique environment where drivers are often captive audiences to roadside fast-food outlets and advertisements. This paper proposes a vision-driven impulsive purchase prediction system that simulates human-like vehicle vision using a Vision Transformer (ViT) model to detect fast-food outlet visibility, crowd levels, and promotional banner exposure in real-time. By integrating these visual cues, our system predicts the likelihood of impulsive stopping behavior (the “impulse score”) of drivers in heavy traffic. We collected and analyzed visual data from congested thoroughfares in major Indonesian cities (Jakarta, Surabaya, Bandung) known for severe traffic jams. The proposed ViT-based model was trained to identify key features such as recognizable outlet signage, drive-thru queue lengths, and promotional signage, mirroring the attention patterns of human drivers. Experimental results demonstrate that the model achieves high accuracy in detecting relevant cues and predicting impulsive purchase decisions, with a mean absolute percentage error (MAPE) of around 12% in forecasting impulse stop rates. This work is the first to leverage a transformer-driven computer vision approach for modeling consumer impulsivity in traffic, bridging automotive perception and marketing analytics. The findings suggest that smart vehicle systems and urban planners can benefit from such technology to anticipate consumer behavior in traffic, optimize roadside advertising, and manage congestion-related demand surges at fast-food outlets.