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All Journal Jurnal Inti Talafa : Jurnal Teknik Informatika PEDAMAS (Pengabdian Kepada Masyarakat)
Ika Safitri Windiarti
Unknown Affiliation
Humanities Computer Science & IT Economics, Econometrics & Finance Education Energy Engineering Health Professions Law, Crime, Criminology & Criminal Justice Social Sciences

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MENGOPTIMALKAN PELAYANAN PENDIDIKAN MELALUI PERANCANGAN WEBSITE SEKOLAH BERBASIS WEB MOBILE (STUDI KASUS: SMP NEGERI 3 PALANGKA RAYA) Ika Safitri Windiarti; Jaya Anggatama; M. Haris Qamaruzzaman
PEDAMAS (PENGABDIAN KEPADA MASYARAKAT) Vol. 2 No. 01 (2024): JANUARI 2024
Publisher : MEDIA INOVASI PENDIDIKAN DAN PUBLIKASI

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

Abstract

Dalam era pemanfaatan internet yang meluas, kemajuan teknologi informasi menjadi krusial dalam memenuhi tuntutan akan penyampaian informasi yang cepat dan akurat. Kegiatan pengabdian masyarakat ini bertujuan meningkatkan aksesibilitas informasi terkait SMP Negeri 3 Palangka Raya melalui perancangan website sekolah berbasis Web Mobile. Metode pengumpulan data melibatkan observasi, dokumentasi, dan wawancara. Desain sistem menggunakan metode prototype dan UML, dengan pengujian sistem menggunakan black box testing. Hasil kegiatan pengabdian masyarakat menunjukkan bahwa website sekolah ini memberikan kontribusi signifikan terhadap kemudahan masyarakat dalam mengakses informasi seputar SMP Negeri 3 Palangka Raya. Dengan adanya website, aksesibilitas informasi sekolah menjadi lebih mudah, cepat, dan efisien. Peningkatan ini tidak hanya memberikan kontribusi pada ketersediaan informasi publik, tetapi juga mengoptimalkan pelayanan pendidikan di era digital. Masyarakat dapat dengan mudah memperoleh informasi yang relevan, membantu dalam pengambilan keputusan pendidikan, serta memberikan dukungan pada upaya peningkatan mutu pendidikan. Dengan demikian, kegiatan ini berperan dalam menghasilkan pelayanan pendidikan yang lebih optimal.
ANALISIS POLA PENYEBAB KARHUTLA KALIMANTAN TENGAH MENGGUNAKAN INDOBERT DAN CAUSAL PATTERN MINING Fahrizal Maulana; Kusrini; Ika Safitri Windiarti; Sutami
INTI TALAFA Vol. 18 No. 2 (2026)
Publisher : Program Studi Teknik Informatika Universitas Muhammadiyah Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32534/int.v18i2.8638

Abstract

Forest and land fires in Central Kalimantan are environmental problems influenced by natural factors and human activities, resulting in complex causal relationship patterns. This study aims to analyze wildfire cause patterns in Central Kalimantan using an IndoBERT-based NLP and AI approach integrated with causal pattern mining on online news articles. Data were collected through web scraping from six local and national news portals using nine Google search queries related to wildfires, resulting in 436 relevant articles as the main corpus. The methodological stages included text preprocessing, semantic representation using a 768-dimensional IndoBERT transformer model, topic discovery using BERTopic, and causal pattern analysis through co-occurrence analysis and contextual relation mining. The topic discovery results identified 10 main topics, with the topic “extreme dry season” dominating with 104 data points, followed by “hot weather and drought” (54 data points). Anthropogenic factors such as intentional land burning, land clearing activities, and human negligence were also identified as significant causes. Contextual relation mining results showed that the words “land” (1,473 occurrences), “smoke” (938), “dry season” (334), and “peatland” (288) were the most dominant causal contexts, while co-occurrence analysis generated 37,581 word pairs forming a causal network. Future studies are recommended to integrate spatial data, expand the dataset, and implement knowledge graphs to support real-time wildfire disaster intelligence systems.
ANALISIS POLA PENYEBAB KARHUTLA KALIMANTAN TENGAH MENGGUNAKAN INDOBERT DAN CAUSAL PATTERN MINING Fahrizal Maulana; Kusrini; Ika Safitri Windiarti; Sutami
INTI TALAFA Vol. 111 No. 111 (2026)
Publisher : Program Studi Teknik Informatika Universitas Muhammadiyah Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32534/int.v18i2.8638

Abstract

Forest and land fires in Central Kalimantan are environmental problems influenced by natural factors and human activities, resulting in complex causal relationship patterns. This study aims to analyze wildfire cause patterns in Central Kalimantan using an IndoBERT-based NLP and AI approach integrated with causal pattern mining on online news articles. Data were collected through web scraping from six local and national news portals using nine Google search queries related to wildfires, resulting in 436 relevant articles as the main corpus. The methodological stages included text preprocessing, semantic representation using a 768-dimensional IndoBERT transformer model, topic discovery using BERTopic, and causal pattern analysis through co-occurrence analysis and contextual relation mining. The topic discovery results identified 10 main topics, with the topic “extreme dry season” dominating with 104 data points, followed by “hot weather and drought” (54 data points). Anthropogenic factors such as intentional land burning, land clearing activities, and human negligence were also identified as significant causes. Contextual relation mining results showed that the words “land” (1,473 occurrences), “smoke” (938), “dry season” (334), and “peatland” (288) were the most dominant causal contexts, while co-occurrence analysis generated 37,581 word pairs forming a causal network. Future studies are recommended to integrate spatial data, expand the dataset, and implement knowledge graphs to support real-time wildfire disaster intelligence systems.
ANALISIS POLA PENYEBAB KARHUTLA KALIMANTAN TENGAH MENGGUNAKAN INDOBERT DAN CAUSAL PATTERN MINING Fahrizal Maulana; Kusrini; Ika Safitri Windiarti; Sutami
INTI TALAFA Vol. 333 No. 333 (2026)
Publisher : Program Studi Teknik Informatika Universitas Muhammadiyah Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32534/int.v18i2.8638

Abstract

Forest and land fires in Central Kalimantan are environmental problems influenced by natural factors and human activities, resulting in complex causal relationship patterns. This study aims to analyze wildfire cause patterns in Central Kalimantan using an IndoBERT-based NLP and AI approach integrated with causal pattern mining on online news articles. Data were collected through web scraping from six local and national news portals using nine Google search queries related to wildfires, resulting in 436 relevant articles as the main corpus. The methodological stages included text preprocessing, semantic representation using a 768-dimensional IndoBERT transformer model, topic discovery using BERTopic, and causal pattern analysis through co-occurrence analysis and contextual relation mining. The topic discovery results identified 10 main topics, with the topic “extreme dry season” dominating with 104 data points, followed by “hot weather and drought” (54 data points). Anthropogenic factors such as intentional land burning, land clearing activities, and human negligence were also identified as significant causes. Contextual relation mining results showed that the words “land” (1,473 occurrences), “smoke” (938), “dry season” (334), and “peatland” (288) were the most dominant causal contexts, while co-occurrence analysis generated 37,581 word pairs forming a causal network. Future studies are recommended to integrate spatial data, expand the dataset, and implement knowledge graphs to support real-time wildfire disaster intelligence systems.
Co-Authors Fahrizal Maulana Jaya Anggatama Kusrini Muhammad Haris Qamaruzzaman Sutami