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All Journal Journal of Information Technology and Computer Science (JOINTECS) Jurnal INSYPRO (Information System and Processing) CogITo Smart Journal JURNAL INSTEK (Informatika Sains dan Teknologi) CCIT (Creative Communication and Innovative Technology) Journal Journal Software, Hardware and Information Technology Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Agents: Journal of Artificial Intelligence and Data Science DIPANEGARA KOMPUTER TEKNOLOGI INFORMATIKA (DIPAKOMTI) DIPANEGARA KOMPUTER SISTEM INFORMASI (DIPAKOMSI) Journal Entrepreneurship Digital
Salman, Nur
Universitas DIPA Makassar
Arts Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Tinjauan Sentimen Terhadap Ulasan Aplikasi Peminjaman Online dengan Metode Support Vector Machine (SVM) Ghani, ST. Aminah Dinayati; Nur Salman, Nur Salman; Farhan Wahyuta Kusuma, Farhan Wahyuta Kusuma
AGENTS: Journal of Artificial Intelligence and Data Science Vol 4 No 1 (2024): Vol 4 No 1 (2024): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/jagti.v4i1.74

Abstract

Online loans, abbreviated as "Pinjol," refer to the practice of lending money online through applications or websites without involving traditional financial institutions such as banks or other traditional creditors. Examples of applications in this field include AkuLaku and Kredivo. These apps operate in the e-commerce and credit provision sectors in Southeast Asia, including Indonesia. Despite their operational strengths, these applications have both advantages and disadvantages, leading to positive and negative reviews on platforms like the Play Store. The research aims to identify positive and negative reviews within these online loan applications that can influence users' decisions when choosing a particular app. SVM classification technique is employed to analyze positive and negative sentiments from these reviews. The accuracy results obtained after sentiment analysis for Kredivo are 81%, while for AkuLaku, it is 75%. A higher accuracy value indicates a better ability of the model to predict sentiments correctly. Visualization of impactful words based on word frequency is presented in the form of a Word Cloud. Therefore, based on the sentiment analysis conducted using the SVM model, the author suggests choosing the Kredivo app when selecting an online loan application, as the analysis indicates that Kredivo has better quality compared to AkuLaku.
Deteksi Dini Hama Jagung Berbasis Cloud Menggunakan CNN sebagai Strategi Pemberdayaan Petani di Kabupaten Gowa Nur Salman; Annah; Kafrawi; Michael Oktavianus; ST Aminah Dinayati; Abdul Ibrahim
JDISTIRA - Jurnal Pengabdian Inovasi dan Teknologi Kepada Masyarakat Vol. 6 No. 1 (2026)
Publisher : Yayasan Rahmatan Fidunya Wal Akhirah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58794/jdt.v6i1.1885

Abstract

Program Pengabdian kepada Masyarakat (PKM) ini dilaksanakan di Desa Garing, Kecamatan Tompobulu, Kabupaten Gowa, dengan tujuan memberdayakan petani jagung melalui pemanfaatan teknologi digital berbasis cloud untuk deteksi dini hama tanaman jagung. Permasalahan utama mitra adalah rendahnya produktivitas jagung akibat serangan hama ulat grayak serta keterbatasan pengetahuan dan literasi digital petani dalam melakukan deteksi dan pengendalian hama secara efektif. Kegiatan PKM dilaksanakan menggunakan pendekatan partisipatif (Participatory Rural Appraisal) melalui tahapan sosialisasi, pelatihan, penerapan teknologi, pendampingan, dan evaluasi. Solusi yang diterapkan berupa aplikasi deteksi dini hama berbasis Convolutional Neural Network (CNN) yang mampu mengidentifikasi gejala serangan hama melalui citra daun serta memberikan rekomendasi penanganan secara real-time. Berdasarkan hasil evaluasi, terjadi peningkatan kapasitas petani, di mana 80% anggota Kelompok Tani Sumber Jaya Satu mampu mengoperasikan aplikasi dan melakukan pencatatan usaha tani secara mandiri. Selain itu, produktivitas jagung meningkat hingga 20% dan penggunaan pestisida kimia menurun sebesar 30%. Hasil ini menunjukkan bahwa program PKM efektif dalam meningkatkan literasi digital, produktivitas pertanian, dan penerapan praktik pertanian berkelanjutan di Desa Garing.
Co-Authors Abdul Ibrahim Andi Irmayana Andika Andika Annah Arini Fitramayanti Asmah Akhriana Cucut Susanto Donny Liklikwatil , Rudy Farhan Wahyuta Kusuma, Farhan Wahyuta Kusuma Fatmasari , Fatmasari Husain T Husain T I Gusti Made Aprianta Nugraha Kafrawi Kalvin Ryan Maria Nova Sarembona michael oktavianus Muhammad Agus Muljanto Muhammad Nur Akbar Muhammad Salsabil Mustika Sari, Mustika Mustikasari Mustikasari Mustikasari Mustikasari Nasaruddin Nasaruddin Nurdin Nurdin Po Abas Sunarya Rauf, Abdul Rudy Donny Liklikwatil Siti Hajratul Aswa ST Aminah Dinayati ST. Aminah Dinayati Ghani Surya Iin