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All Journal JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Akademisi Vokasi Jurnal Penelitian Terapan Mahasiswa
Pio Pratama, I Wayan
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Humanities Computer Science & IT Economics, Econometrics & Finance Environmental Science Languange, Linguistic, Communication & Media Social Sciences

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Journal : Jurnal Akademisi Vokasi

 1 
Exploring Two Methods of Usability Testing: System Usability Scale And Retrospective Think-Aloud Pio Pratama, I Wayan; I Putu Eka Sudarsana, Eka Sudarsana; Angling Galih Cahaya Widiyanto, Angling
JURNAL AKADEMISI VOKASI Vol 2 No 1 (2023): Jurnal Akademisi Vokasi
Publisher : Pusat Penelitian dan Pengabdian Politeknik eLBajo Commodus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63604/javok.v2i1.26

Abstract

This research was conducted to measure the usability of a system using two methods, RTA (Retrospective Think Aloud) and SUS (System Usability Scale). An object used in this research was shazam. The subject were 5 people, who are smartphone users in the age range of 10 to 50 years old. Finally, in this research RTA method showed that the shazam application is effective with a completion rate of 94.3% and efficient with a time-based efficiency of 0.108 task/second. While SUS showed that Shazam is still categorized as a class B application.
IMPLEMENTASI SUPPORT VECTOR MACHINE DALAM PREDIKSI HARGA RUMAH Pio Pratama, I Wayan
JURNAL AKADEMISI VOKASI Vol 2 No 2 (2023): Jurnal Akademisi Vokasi
Publisher : Pusat Penelitian dan Pengabdian Politeknik eLBajo Commodus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63604/javok.v2i2.54

Abstract

This study aims to predict house prices in the United States based on features such as Avg. Area Income, Avg. Area House Age, Avg. Number of Rooms, and Area Population. The dataset used consists of several thousand entries without missing values. Through initial data exploration, a significant correlation was found between several features and house prices. Outliers were analyzed and considered in the modeling process. The Support Vector Machine (SVM) algorithm with various kernels was applied, where the Radial Basis Function (RBF) kernel showed the best performance, explaining about 70.78% of the variation in house prices. The results of this study highlight the potential of the SVM algorithm in property price prediction and provide insights for further property analysis.
Does Academic Preparedness Influence Performance? A Comparative Study Across Programs At Politeknik eLBajo Commodus Pio Pratama, I Wayan
JURNAL AKADEMISI VOKASI Vol 3 No 1 (2024): Jurnal Akademisi Vokasi
Publisher : Pusat Penelitian dan Pengabdian Politeknik eLBajo Commodus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63604/javok.v3i1.96

Abstract

This study investigates academic performance variations across study programs at Politeknik eLBajo Commodus, blending quantitative analysis with qualitative insights to provide a holistic view of student achievement. Employing an Analysis of Variance (ANOVA) on 'Tes Bakat Skolastik' scores, we sought to identify significant differences in academic performance among the programs. Additionally, casual interviews with students were conducted to explore their perceptions of program selection, academic preparedness, and the challenges encountered. Our methodology combined statistical rigor with a nuanced understanding of student experiences, offering a comprehensive analysis of the factors influencing academic success. The quantitative phase involved comparing mean scores across programs using ANOVA, while the qualitative phase entailed gathering subjective insights from students regarding their academic journey and preparation. The results revealed no statistically significant differences in performance across study programs, indicating a baseline uniformity in academic achievement. However, student interviews highlighted a significant gap in pre-admission knowledge about program expectations and personal academic readiness. These findings suggest the need for enhanced pre-enrollment assessments and orientation programs to better align student expectations with academic demands. In conclusion, this study underscores the importance of a holistic educational approach that encompasses both statistical analyses and the lived experiences of students, advocating for initiatives that support informed decision-making and academic preparedness at the tertiary level.
Co-Authors Angling Galih Cahaya Widiyanto, Angling Eka Sudarsana, I Putu Hersanius Kurnia Peong I Putu Eka Sudarsana, Eka Sudarsana Muhammad Innuddin Ondi Asroni