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All Journal Abdimas Dewantara Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat JATI (Jurnal Mahasiswa Teknik Informatika) Algor Abdi-Dharma RUBINSTEIN
Hariyanto, Susanto
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Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Social Sciences Other

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Pelatihan Internet of Things (IoT) dalam peningkatan kompetensi siswa multimedia di SMK Perguruan Buddhi Akbar, Junaidi; Rino, Rino; Safitri, Ramona Dyah; Lasut, Desiyanna; Hariyanto, Susanto; Fenriana, Indah; Daniawan, Benny
ABDIMAS DEWANTARA Vol 7 No 1 (2024)
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/ad.v7i1.16938

Abstract

Pelatihan Internet of Things (IoT) menjadi bagian penting dalam pengembangan kompetensi siswa jurusan multimedia di SMK Perguruan Buddhi. Era digital menuntut adanya pemahaman mendalam terhadap integrasi teknologi dan IoT menjadi pondasi utama dalam menghadapi tantangan tersebut. Tujuan pelatihan ini untuk meningkatkan keterampilan teknis dan kreativitas melalui integrasi IoT. Metode pelatihan mencakup serangkaian persiapan, pelaksanaan dan evaluasi. Pelatihan dirancang khusus untuk memahamkan siswa pada konsep-konsep dasar IoT, pengembangan perangkat keras dan aplikasi berbasis IoT, pelatihan ini diikuti oleh 32 peserta, hasil dari pelatihan ini melalui responden peserta dengan mengisi angket kuesioner, dari segi pengenalan coding didapat nilai 100% peserta telah mengenal coding, segi pengenalan IoT didapat nilai 37% mengenal IoT dan 63% belum mengenal IoT, segi pemaparan materi IoT menarik atau jelas 97% dengan jelas dan 3% tidak jelas, segi ketertarikan belajar IoT lebih lanjut 72% dengan ingin melanjutkan dan 28% tidak ingin melanjutkan. Peserta antusias menyelesaikan project - project yang diberikan dalam mengikuti pelatihan, serta mereka mendapatkan pengetahuan dan kemampuan baru terkait dengan teknologi IoT dan implementasinya.   Internet of Things (IoT) training improving the competence of multimedia students SMK Perguruan Buddhi   Abstract: Internet of Things (IoT) training is an important part of developing the competence of students majoring in multimedia at SMK Perguruan Buddhi. The digital era requires a deep understanding of technology integration, and IoT is the main foundation for facing these challenges. This training aims to improve technical skills and creativity through IoT integration. The training method includes preparation, implementation, and evaluation. The training was specifically designed to familiarize students with the basic concepts of IoT, hardware development, and IoT-based applications. Thirty-two participants attended this training. The respondents, by filling out a questionnaire in terms of the introduction of coding obtained a value of 100% of participants knew coding, terms introduction to IoT obtained a value of 37% knew IoT and 63% did not know IoT, terms of exposure to IoT material interesting or clear 97% with clear and 3% not clear, terms of interest in learning further IoT 72% with want to continue and 28% do not want to continue. Participants were enthusiastic about completing the projects given in the training, and they gained new knowledge and skills related to IoT technology and its implementation.
Perancangan Virtual Assistant Chatbot Berbasis Website sebagai Alat Promosi dan Dukungan Pemasaran Hariyanto, Susanto; Fenriana, Indah; Putra, Dicky Surya Dwi; Lasut, Desiyanna
RUBINSTEIN Vol. 2 No. 1 (2023): RUBINSTEIN (juRnal mUltidisiplin BIsNis Sains TEknologI & humaNiora)
Publisher : LP3kM Buddhi Dharma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/rubin.v2i1.2658

Abstract

Penelitian ini memfokuskan pada pengembangan dan implementasi Chatbot sebagai alat penting dalam strategi pemasaran produk. Chatbot diimplementasikan sebagai asisten virtual interaktif, memberikan pengguna kemampuan untuk mengajukan pertanyaan dan menerima respons yang relevan berdasarkan pengetahuan terintegrasi. Metode pengembangan yang digunakan adalah metode SDLC dengan pendekatan waterfall, memberikan kerangka kerja yang terstruktur. Pengujian dilakukan menggunakan metode blackbox testing untuk memastikan fungsi-fungsi Chatbot berkinerja sesuai dengan kebutuhan promosi. Hasil pengujian menunjukkan kinerja stabil dan dapat diandalkan. Hal ini menandakan bahwa Chatbot dapat memberikan informasi yang akurat dan tepat waktu kepada pengguna, memudahkan tim pemasaran dalam berkomunikasi efektif. Flowchart dan tabel pengujian yang dikembangkan membantu memahami alur kerja sistem dan hasil pengujian dengan rinci. Analisis hasil pengujian mengindikasikan bahwa implementasi Chatbot sesuai dengan tujuan awal, memberikan manfaat signifikan dalam mendukung strategi pemasaran dan meningkatkan kualitas interaksi pengguna. Kesimpulan dari penelitian ini mencakup pengenalan potensi perbaikan, seperti perluasan knowledge base dan peningkatan kemampuan Chatbot dalam merespons pertanyaan yang kompleks. Saran untuk penelitian lebih lanjut melibatkan pengembangan grafis, integrasi suara, dan pemahaman bahasa gaul untuk meningkatkan daya tarik dan keterlibatan pengguna. Penelitian ini memberikan kontribusi dalam konteks penggunaan Chatbot sebagai alat promosi yang efektif, dengan harapan memberikan dampak positif pada kualitas pemasaran dan pengalaman pengguna secara keseluruhan.
Comparative Analysis of Support Vector Machine, Decision Tree, and Naive Bayes in Evaluating Machine Learning Effectiveness Hariyanto, Susanto; Indah Fenriana; Desiyanna Lasut; Febrian
RUBINSTEIN Vol. 4 No. 1 (2025): RUBINSTEIN (juRnal mUltidisiplin BIsNis Sains TEknologI & humaNiora)
Publisher : LP3kM Buddhi Dharma University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/rubin.v4i1.4041

Abstract

This study aims to analyze and compare the performance of three widely used machine learning algorithms for data classification: Support Vector Machine (SVM), Decision Tree, and Naïve Bayes. These algorithms employ distinct approaches in handling data, making it essential to evaluate their effectiveness and efficiency in classification tasks. In the digital era characterized by massive data growth, the selection of an appropriate classification algorithm is a critical determinant for accurate and efficient data-driven decision-making. The main contribution of this research is to provide a comprehensive understanding of the relative strengths and limitations of each algorithm under varying data conditions. This study not only highlights comparative performance outcomes but also emphasizes practical implications for researchers and data science practitioners in selecting algorithms suited to specific needs. In doing so, it addresses a research gap concerning integrated evaluations of data characteristics and algorithmic performance. The methodology adopts a quantitative approach through computational experiments using standardized datasets (Titanic, Spam Email, and Wine). The datasets were divided into training and testing sets and analyzed using Python with the scikit-learn library. Performance evaluation was conducted based on accuracy, precision, recall, and F1-score, validated through cross-validation techniques to ensure reliability of results. The findings indicate that SVM outperforms in terms of accuracy and recall on complex datasets, Naïve Bayes is more efficient in computational time particularly for text data, while Decision Tree stands out for model interpretability despite slightly lower accuracy. These results are expected to serve as a practical reference for selecting suitable algorithms according to data characteristics, thereby supporting more targeted and intelligent modeling strategies in the era of digital transformation.
Co-Authors Akbar, Junaidi Ananda Krisnahadi, Dominikus Andrean, Andrean Andrew Andrew, Andrew Arijanto, Rudy Candika Kirana Ariya Putri Christian, Fernando Daniawan, Benny Desiyanna Lasut Dethan, Jacob Febryadi Nithanel Dyah Safitri, Ramona Febrian Fennita, Fennita Fenriana, Indah Indah Fenriana Ivan Rio Setiadi Lasut, Desiyanna Putra, Dicky Surya Dwi Ramona Safitri, Ramona Rino Rino Saputra, Windi Tanjung, Naia Putri velistin, Fellix Widyadharta Ciady, Pedro Widyastuti Kusuma, Lianny Wijaya, Ardie William Setiawan, Charles Yusuf Kurnia