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I Dewa Gede Loka Maheswara
Sekolah Tinggi Meteorologi Klimatologi dan Geofisika
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Analisis Unsur Melawan Hukum Dalam Penyalahgunaan Wewenang Dan Diskresi Pejabat Negara I Dewa Gede Loka Maheswara; Andi Baso Sawerigading; Ghaitsa Afifah; Yusron Faiz Athallah; Shindyoko Wibowo
Academy of Education Journal Vol. 17 No. 2 (2026): Academy of Education Journal
Publisher : Fakultas Keguruan dan Ilmu Pendidikan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47200/aoej.v17i2.3617

Abstract

Abuse of authority constitutes one of the forms of corruption regulated under Article 3 of Law Number 31 of 1999 in conjunction with Law Number 20 of 2001 on the Eradication of Corruption Crimes. This study aims to analyze the application of the element of unlawfulness in the offense of abuse of authority through the Decision of the Jakarta Corruption Court Number 34/Pid.Sus-TPK/2025/PN.Jkt.Pst involving Thomas Trikasih Lembong. The study focuses on the application of the unlawfulness element, the boundary between policy discretion and abuse of authority, and the implications of the decision for legal certainty in public policymaking. This research employs a normative juridical method using statutory, conceptual, and case approaches. The findings indicate that the application of the unlawfulness element in the decision combines both formal and material approaches. Furthermore, the decision raises issues regarding criminal liability since the defendant was found guilty despite the absence of evidence showing personal gain. The study also reveals that the distinction between legitimate policy discretion and punishable abuse of authority remains unclear, potentially creating legal uncertainty for public officials in making strategic policy decisions.
Strategi Mitigasi Non-Struktural Bencana Hidrometeorologi Berbasis Edukasi dan Teknologi Informasi bagi Masyarakat Pesisir Sanur I Dewa Gede Loka Maheswara; Intan Bryliana Putri; I Made Prabawa Sandhi Gotama; Putu Aldi Tusan Pratama; Muhammad Jouhar Syah; I Wayan Jyesta Jaya Taruna; Shintia Dwi Cahya; John Pieter S. A; Azra Haiza Zaman; Gede Galang Temuju; Delfiana Yoventa Buti; Kadek Valerina Kitana Sanjaya; Adi Mulsandi; Abraham Frederik Mustamu; Dodo Gunawan
Jurnal Masyarakat Madani Indonesia Vol. 5 No. 2 (2026): Mei
Publisher : Alesha Media Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59025/4ekjje90

Abstract

Kegiatan pengabdian kepada masyarakat merupakan salah satu sarana penerapan ilmu pengetahuan secara langsung untuk memberikan manfaat nyata bagi masyarakat. Dalam rangka Kuliah Kerja Nyata (KKN) STMKG Unit 13, dilaksanakan tiga kegiatan pengabdian di kawasan Pantai Kelurahan Sanur sebagai respons terhadap tingginya kerentanan wilayah pesisir Denpasar Selatan di Provinsi Bali terhadap bencana hidrometeorologi. Kegiatan yang dilaksanakan meliputi sosialisasi hidrometeorologi, pelatihan penggunaan aplikasi SICUPEL, serta pemasangan plang informasi prakiraan cuaca maritim dan tinggi gelombang di wilayah Pantai Semawang. Metode yang diterapkan mengutamakan diskusi interaktif dua arah antara tim penyuluh dan nelayan, yang memungkinkan konfirmasi silang antara informasi prakiraan resmi BMKG dengan pengetahuan empiris nelayan di lapangan. Pendekatan ini terbukti efektif dalam membangun penerimaan peserta terhadap materi yang disampaikan, sekaligus memvalidasi fenomena hidrometeorologi lokal seperti angin kencang dari awan cumulonimbus yang selama ini hanya dipahami secara empiris oleh nelayan. Ketiga kegiatan yang dirancang berkontribusi dalam memperkuat literasi kebencanaan dan kesiapsiagaan masyarakat nelayan pesisir pantai Kelurahan Sanur terhadap potensi bencana hidrometeorologi.
PREDIKSI KATEGORI CURAH HUJAN BERBASIS MACHINE LEARNING UNTUK MENDUKUNG KETAHANAN PANGAN I Dewa Gede Loka Maheswara; Kanaya Kaizzi Larasati; Muhammad Nur Rizqi; Muhammad Fany Nurwibowo; Yosafat Donni Haryanto
INTI Nusa Mandiri Vol. 21 No. 1 (2026): INTI Periode Agustus 2026
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/inti.v21i1.8601

Abstract

Rainfall variability significantly influences food security in Central Tapanuli Regency, North Sumatra, a region where agriculture is strongly reliant on climatic patterns. This research evaluates and compares the classification performance of Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), and Random Forest (RF) for categorizing daily rainfall as supplementary information to strengthen food security. A total of 3,644 daily meteorological records obtained from FL Tobing Meteorological Station spanning 2015 to 2024 were utilized, encompassing seven predictor variables: minimum temperature, maximum temperature, average temperature, mean relative humidity, sunshine duration, peak wind speed, and average wind speed. To mitigate class imbalance, the original six rainfall categories were consolidated into four classes by merging the minority groups. The data were partitioned into training and testing subsets at an 80:20 ratio using stratified sampling, after which the Synthetic Minority Over-sampling Technique (SMOTE) was employed on the training set. Hyperparameter tuning was conducted through Grid Search combined with 5-fold cross-validation, and classification performance was assessed using accuracy, precision, recall, F1-score, and paired t-test analyses. The experimental results indicated that RF delivered superior performance, attaining an accuracy of 51.44% and a weighted F1-score of 0.5036, significantly outperforming both SVM and K-NN (p-value < 0.05). Feature importance analysis revealed that sunshine duration, average temperature, and maximum temperature were the most influential predictors. These outcomes demonstrate that RF holds considerable promise for advancing machine learning-driven rainfall category prediction systems capable of delivering early-stage information for agricultural planting schedules and preparedness against intense rainfall events in Central Tapanuli Regency
Co-Authors Abraham Frederik Mustamu Adi Mulsandi Andi Baso Sawerigading Azra Haiza Zaman Delfiana Yoventa Buti Dodo Gunawan Gede Galang Temuju Ghaitsa Afifah I Made Prabawa Sandhi Gotama I Wayan Jyesta Jaya Taruna Intan Bryliana Putri John Pieter S. A Kadek Valerina Kitana Sanjaya Kanaya Kaizzi Larasati Muhammad Fany Nurwibowo Muhammad Jouhar Syah Muhammad Nur Rizqi Putu Aldi Tusan Pratama Shindyoko Wibowo Shintia Dwi Cahya Yosafat Donni Haryanto Yusron Faiz Athallah