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All Journal Techno.Com: Jurnal Teknologi Informasi Ranah: Jurnal Kajian Bahasa Dinamisia: Jurnal Pengabdian Kepada Masyarakat JURNAL INOVASI PENDIDIKAN DAN PEMBELAJARAN SEKOLAH DASAR JENTERA: Jurnal Kajian Sastra Building of Informatics, Technology and Science Charity : Jurnal Pengabdian Masyarakat Journal La Multiapp Prosiding Konferensi Nasional PKM-CSR Jurnal Pengabdian Masyarakat Bhinneka eProceedings of Engineering
Diyas Puspandari
Telkom University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Nursing Public Health Social Sciences Other

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Impact of Feature Extraction on Multi-Aspect Sentiment Classification for Livin'byMandiri Using BiLSTM Atikah, Balqis Sayyidahtul; Sibaroni, Yuliant; Puspandari, Diyas
Journal La Multiapp Vol. 5 No. 5 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i5.1541

Abstract

Mobile applications are currently experiencing very rapid development including applications in the financial sector. Livin'byMandiri is one of the mobile applications used to transact online without the need to go to the bank. This makes it very easy for customers to transact anywhere and anytime. Application reviews are user reviews that reflect the reputation of the application among the community, these application reviews can be found anywhere, so many companies use application reviews as a reference in developing their applications in the future. However, people's opinions on apps can vary and are influenced by many aspects. Therefore, aspect-based sentiment analysis can be applied to app reviews to get better results. This research focuses on analyzing the sentiment of Livin'byMandiri app reviews on the Google Play Store. In this research, the Bidirectional LSTM (Bi-LSTM) method is combined with TF-IDF and Word2Vec feature extraction. From the results of the experiments that have been carried out, the best accuracy results for the access aspect are 81.18% and F1-Score of 81.03%, the service aspect produces an accuracy of 82.82% and F1-Score of 82.74%, and for the convenience aspect produces an accuracy of 77.28% and F1-Score of 77.19%. In this experiment, it is also found that feature extraction has an effect on sentiment analysis, this is evidenced by an increase in accuracy of more than 1% for each aspect when TF-IDF feature extraction is added and also the combination of TF-IDF and Word2vec in the initial model built using only the Neural Network embedding layer.
Training on The Use of AI to Increase Teacher Competency in Preparing The Learning Process : Pelatihan Penggunaan AI untuk Peningkatan Kompetensi Guru-Guru dalam Menyiapkan Proses Pembelajaran Puspandari, Diyas; Prasetiyowati, Sri; Sibaroni, Yuliant
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 9 No. 1 (2025): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v9i1.20929

Abstract

Teachers, as educational personnel, are expected to enhance their competence in mastering information technology, which can later be utilized in classroom learning activities. However, in reality, teachers' knowledge and skills in mastering technology to support teaching and learning activities are still limited. Based on a survey conducted, teachers at SD Indriyasana, Baleendah, are eager to gain knowledge and skills in using open-source applications, such as Chat GPT, Gemini AI, and MajickPen AI, to support their tasks, both in teaching and administrative duties. Therefore, training and mentoring are needed in learning the use of these open-source applications to support teachers' activities. The aim of this training is to introduce and train teachers at SD Indriyasana, Baleendah, in using open-source applications based on artificial intelligence (AI), such as Chat GPT, Gemini AI, and MajickPen AI, to support teaching and administrative tasks. The method used involves training, direct practice by teachers, guided by speakers and instructors using AI-based open-source applications, namely ChatGPT, Gemini AI, and MajickPen. The implementation method includes the following steps: 1) user needs analysis, 2) literature study, 3) training module development, 4) module testing, 5) training implementation, 6) evaluation. The training results indicate that teachers acquired knowledge and practical experience in line with their needs, enabling them to use AI-based applications (Chat GPT, Gemini AI, and MajickPen AI) to support learning and administrative activities. It can be said that the training went well, as shown by the questionnaire results: 1) alignment of the training program with objectives (94%), 2) alignment of the program with partners' needs (71%), 3) adequacy of program implementation time (65%), 4) team’s ability to execute the program (88%), and 5) program sustainability (77%). This training activity is beneficial for both teachers and students because it can make learning more interesting and enjoyable for students. By utilizing AI-based applications, teachers can generate ideas for learning activities, create quizzes, or provide relevant and up-to-date teaching materials, thereby facilitating class preparation and easing teachers' administrative tasks.
Pelatihan Pengolahan Data Bagi Siswa SMK Negeri 3 Bandung Jurusan Manajemen Perkantoran dan Layanan Bisnis Palupi, Irma; Puspandari, Diyas; Fitriyani, Fitriyani
Charity : Jurnal Pengabdian Masyarakat Vol. 7 No. 1 (2024): Charity - Jurnal Pengabdian Masyarakat
Publisher : PPM Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Selaras dengan merdeka belajar yang diluncurkan Kemendikbud, yaitu SMK sebagai pusat keunggulan, diperlukan keselarasan dengan dunia kerja yang menuntut percepatan dalam menguasi keahlian baru untuk menciptakan inovasi dalam industri. Salah satu keahlian yang perlu dimiliki lulusan adalah keahlian terkait pengolahan data seiring produksi data di hampir semua aspek yang semakin rapid dan menyeluruh di segala bidang. Sesuai dengan permasalahan mitra SMKN 3 Bandung, maka solusi yang ditawarkan adalah mengadakan pelatihan analisis data untuk keperluan perusahaan dan riset kebutuhan produk pasar. Tools yang ditawarkan adalah teknik pengolahan data menggunakan python dan library terkait. Dalam pelatihan disampaikan cara mengolah data melalui contoh data yang sesuai, lalu siswa langsung mempraktikkan cara mengolah data. Luaran dari kegiatan ini adalah pengetahuan dan keterampilan siswa agar dapat mengimplementasikannya dalam dunia kerja yang akan dihadapinya.
Penerapan Data Sains untuk Analisis Preferensi Wisatawan dalam Pengembangan Paket Wisata Sibaroni, Yuliant; Prasetiyowati, Sri Suryani; Puspandari, Diyas
Jurnal Pengabdian Masyarakat Bhinneka Vol. 4 No. 3 (2026): Bulan Februari
Publisher : Bhinneka Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58266/jpmb.v4i3.1035

Abstract

Perkembangan teknologi informasi telah memberikan dampak signifikan pada industri pariwisata, terutama melalui media sosial yang memengaruhi preferensi wisatawan dalam memilih destinasi. Data digital dari aktivitas wisatawan di platform seperti Instagram, TikTok, dan YouTube dapat dimanfaatkan untuk memahami tren, minat, serta perilaku wisatawan. Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan keterampilan siswa SMKN 3 Bandung dalam menganalisis data preferensi wisatawan menggunakan pendekatan data sains. Metode yang digunakan meliputi penentuan fitur preferensi, pemodelan berbasis konten, segmentasi wisatawan dengan K-Means, serta pembangunan paket wisata menggunakan pendekatan heuristik. Data yang dianalisis berasal dari konten media sosial wisata Bandung dan sekitarnya, kemudian dibersihkan dan dikategorikan berdasarkan jenis destinasi. Hasil pelatihan menunjukkan peningkatan pengetahuan peserta melalui pre-test dan post-test, serta keberhasilan dalam merancang paket wisata inovatif yang sesuai dengan minat wisatawan, seperti “Bandung Serenity Escape” dan “Garut Hidden Paradise.” Evaluasi kegiatan memperlihatkan lebih dari 90% peserta merasa pelatihan bermanfaat dan relevan dengan kebutuhan mereka. Dengan demikian, penerapan data sains terbukti efektif dalam mendukung pengembangan paket wisata berbasis preferensi wisatawan dan memberikan kontribusi praktis bagi industri pariwisata lokal.
Co-Authors Anisa Herdiani Arip Widodo, Arip Atikah, Balqis Sayyidahtul Erwin Budi Setiawan Fitriyani Fitriyani Indra Nugrahayu Taufik Indriani Mentaruk Irma Palupi Mahardika, Reka Yuda Muhamad Fauzan Putra Novitasari, Ariqoh Prasetiyowati, Sri Sakti Dewantoro Shakina Rizkia Shyahrin, Mega Vebika Sri Suryani Prasetiyowati Yuliant Sibaroni