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All Journal INVOTEK: Jurnal Inovasi Vokasional dan Teknologi Jurnal Mantik JPKMI (Jurnal Pengabdian Kepada Masyarakat Indonesia)
Pratama, I Wayan Pio
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Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences Transportation

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Pelatihan Pemanfaatan Aplikasi Edpuzzle Sebagai Media Pembelajaran SMKN 3 Komodo Asroni, Ondi; Pratama, I Wayan Pio; Sudarsana, I Putu Eka; Harjo, Kristoforus Toni; Peong, Hersanius Kurnia
JPKMI (Jurnal Pengabdian Kepada Masyarakat Indonesia) Vol 5, No 1: February (2024)
Publisher : ICSE (Institute of Computer Science and Engineering)

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Abstract

Abstrak: Beberapa penelitian menunjukkan bahwa penerapan metodologi pembelajaran hybrid berbasis teknologi dapat secara signifikan meningkatkan pemahaman siswa dalam proses pendidikan. Pembelajaran hybrid membutuhkan para pendidik untuk memiliki keterampilan dalam penggunaan teknologi. Inisiatif pemerintah untuk meningkatkan literasi digital siswa menekankan pentingnya pendidikan yang terintegrasi dengan teknologi. Menurut survei yang dilakukan pada tahun 2021 oleh Kominfo dan Katadata, indeks literasi digital Indonesia mencapai 3,407 dari skala 1 hingga 4, menegaskan urgensi untuk memulai program pengabdian masyarakat di sekolah-sekolah, terutama di daerah 3T. SMKN 3 Komodo, yang terletak di Manggarai Barat, NTT, adalah salah satu institusi yang relevan. Wawancara dengan kepala SMKN 3 Komodo menunjukkan bahwa integrasi teknologi dalam proses belajar mengajar belum optimal. Oleh karena itu, program pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kualitas pendidikan dengan memanfaatkan aplikasi edpuzzle. Sesi pelatihan intensif dilakukan untuk 49 guru dan 9 tenaga kependidikan, dengan fokus pada penggunaan teknologi informasi dalam pembelajaran. Ini termasuk pelatihan langsung dalam membuat konten pembelajaran interaktif menggunakan aplikasi Edpuzzle. Hasilnya menunjukkan peningkatan pemahaman guru tentang teknologi pendidikan, menciptakan lingkungan belajar yang lebih interaktif dan menarik bagi siswa. Terdapat juga peningkatan yang signifikan dalam literasi digital siswa, mendorong partisipasi aktif dalam proses pembelajaran. Ini menegaskan pentingnya investasi dalam pengembangan kompetensi guru dan integrasi teknologi. Meskipun demikian, tantangan tetap ada dalam memperluas penggunaan teknologi di berbagai mata pelajaran, melakukan evaluasi terhadap efektivitas teknologi, dan mempromosikan kolaborasi antara lembaga pendidikan dan badan penelitian. Integrasi teknologi dalam pendidikan menghasilkan dampak positif dan membutuhkan fokus berkelanjutan pada pengembangan kompetensi guru, evaluasi teknologi, dan kerjasama antar lembaga untuk mempersiapkan siswa menghadapi tantangan teknologi di masa depan.Abstract: Several studies have shown that the implementation of technology-based hybrid learning methodologies can significantly enhance students' understanding in the educational process. Hybrid learning requires educators to have skills in utilizing technology. Government initiatives to improve students' digital literacy emphasize the importance of education integrated with technology. According to a 2021 survey conducted by Kominfo and Katadata, Indonesia's digital literacy index reached 3.407 on a scale of 1 to 4, underscoring the urgency to initiate community service programs in schools, especially in 3T areas. SMKN 3 Komodo, located in Manggarai Barat, NTT, is one relevant institution. Interviews with the head of SMKN 3 Komodo revealed that the integration of technology into the teaching-learning process is not yet optimal. Therefore, this community service program aims to enhance the quality of education by utilizing the Edpuzzle application. Intensive training sessions were conducted for 49 teachers and 9 educational staff, focusing on the use of information technology in learning. This included direct training in creating interactive learning content using the Edpuzzle application. The results showed an improvement in teachers' understanding of educational technology, creating a more interactive and engaging learning environment for students. There was also a significant increase in students' digital literacy, encouraging active participation in the learning process. This underscores the importance of investing in teacher competence development and technology integration. However, challenges remain in expanding the use of technology in various subjects, evaluating the effectiveness of technology, and promoting collaboration between educational institutions and research bodies. Technology integration in education has yielded positive impacts and requires sustained focus on teacher competency development, technology evaluation, and inter-institutional collaboration to prepare students to face future technological challenges.
Exploring the Depths of Market Basket Analysis: A Comprehensive Guide to Transaction Analysis with FP-Growth and Apriori Algorithms Pratama, I Wayan Pio
invotek Vol 23 No 2 (2023): INVOTEK: Jurnal Inovasi Vokasional dan Teknologi
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/invotek.v23i2.1094

Abstract

This research investigates the role of data science in understanding customer behavior and enhancing sales, focusing specifically on the application of Apriori and FP-Growth Algorithms at a retail store, Deli Point, in Labuan Bajo. It illuminates the impact of 'rubbish data' on transactional data analysis, emphasizing the need for robust data cleaning procedures to ensure accurate results. Utilizing the faster FP-Growth Algorithm, the study effectively analyzed customer purchasing patterns to identify optimal product combinations for sales improvement. It discovered that 'parsley local' and 'mint flores' items had the highest support with a value of 0.036, indicating that strategic placement of these items together could enhance sales. The rule between chicken leg bone, orange sunkist, and chicken breast boneless was found to have a high confidence value and a lift value higher than 1, implying a higher potential for these items to be sold when positioned near each other. This study contributes to understanding consumer behavior and provides insights for enhancing sales and competitiveness in the retail industry. An association rule involving 'chicken leg bone’, 'orange sunkist', and 'chicken breast boneless' demonstrated high confidence and a lift value above one, suggesting significant sales potential when these items are grouped together. This study not only contributes valuable insights into retail consumer behavior and effective product placement strategies but also underscores the transformative role of data science in optimizing sales and boosting competitiveness in the retail sector.
Uncertainty and stability analysis of data-driven inversion using support vector regression Pratama, I Wayan Pio
Jurnal Mantik Vol. 9 No. 4 (2026): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v9i4.6957

Abstract

This study examines learning-based inversion through the lens of inverse problem theory, focusing on uncertainty propagation, conditioning, and identifiability rather than pointwise prediction accuracy alone. Inverse estimation is formulated as a stochastic mapping in which observational noise is explicitly propagated through learned inverse models. A controlled one-dimensional nonlinear inverse problem is constructed using synthetic forward operators to systematically isolate noise-induced instability and non-uniqueness effects. For an injective nonlinear forward mapping, Support Vector Regression (SVR) with a radial basis function kernel and linear regression are trained to approximate the inverse operator from noisy observations. Monte Carlo noise propagation is employed to estimate bias and variance of inverse predictions and to compare empirical uncertainty amplification with theoretical predictions derived from local inverse conditioning. While SVR significantly outperforms linear regression in terms of inverse accuracy, the results demonstrate that inverse uncertainty is primarily governed by the conditioning of the forward operator and is modulated by model regularization. The analysis is extended to a non-injective forward operator to investigate identifiability loss in learning-based inversion. In this setting, both models collapse inherently multi-valued inverse mappings into unimodal and overconfident estimates, revealing implicit solution selection driven by data distribution and regularization. These findings show that low prediction error can be misleading in non-identifiable inverse problems. Overall, this work highlights the limitations of deterministic learning-based inversion and underscores the need for uncertainty-aware and distribution-preserving approaches when addressing ill-conditioned or non-injective inverse problems.
Co-Authors Hersanius Kurnia Peong Kristoforus Toni Harjo Ondi Asroni Sudarsana, I Putu Eka