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All Journal Jurnal Akademisi Vokasi
I Wayan Pio Pratama
Politeknik eLBajo Commodus, Labuan Bajo
Humanities Computer Science & IT Economics, Econometrics & Finance Environmental Science Social Sciences

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IMPLEMENTASI SUPPORT VECTOR MACHINE DALAM PREDIKSI HARGA RUMAH I Wayan Pio Pratama
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.
ANALISIS DEMOGRAFIS DAN GEOGRAFIS MAHASISWA POLITEKNIK ELBAJO COMMODUS Kristoforus Toni Harjo; I Wayan Pio Pratama; I Putu Eka Sudarsana; Ondi Asroni; Hersanius Kurnia Peong; Angling G.C. Widiyanto; Firmanus Ardiman
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.v2i2.85

Abstract

This analysis examines the student enrollment patterns at Politeknik ELBajo Commodus, highlighting the geographic dynamics and their impact on student recruitment. Utilizing the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and calculating the physical distance between students' original schools and the Politeknik campus, the study reveals clear geographic clusters, with a high concentration of students near the Politeknik, as well as the identification of prospective students from underrepresented remote areas. The analysis results indicate that distance is a factor influencing enrollment decisions, with students living closer to the campus more likely to enroll. These findings underscore the need for tailored marketing and recruitment strategies, which not only strengthen relationships with schools in clustered areas but also create initiatives targeting remote areas. This research provides recommendations for the development of programs designed to attract students from various geographic backgrounds, as well as the importance of ongoing research to ensure the alignment of the applied strategies with the needs and preferences of prospective students. In conclusion, Politeknik ELBajo Commodus can enhance its recruitment strategies by adopting a more focused approach and a greater diversification in its student base. keywords: Geospatial Analysis, DBSCAN Clustering, Recruitment Strategies, Educational Marketing, Access to Education.
Does Academic Preparedness Influence Performance? A Comparative Study Across Programs At Politeknik eLBajo Commodus I Wayan Pio Pratama
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 G.C. Widiyanto Firmanus Ardiman Hersanius Kurnia Peong I Putu Eka Sudarsana Kristoforus Toni Harjo Ondi Asroni