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All Journal JIKO (Jurnal Informatika dan Komputer) Literatus Innovation in Research of Informatics (INNOVATICS) JOURNAL SCIENTIFIC OF MANDALIKA (JSM) Innovative: Journal Of Social Science Research Notary Law Journal
Impron, Ali
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Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Urgensi Standarisasi Kualifikasi Karyawan Notaris di Indonesia Asufie, Khairunnisa Noor; Aripkah, Nur; Impron, Ali
Notary Law Journal Vol. 2 No. 3 (2023): July-September
Publisher : Program Studi Kenotariatan Fakultas Hukum Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32801/nolaj.v2i3.46

Abstract

Notaris adalah pejabat umum yang dalam pelaksanaan jabatannya memberikan pelayanan dalam ranah hukum perdata kepada masyarakat. Notaris dalam pelaksanaan jabatannya berkedudukan di Kantor Notaris pada wilayah kerjanya dengan dibantu oleh karyawan Notaris. Peran karyawan Notaris dalam pelaksanaan jabatan Notaris untuk membantu Notaris dalam pelaksanaan tata kelola administrasi kantor Notaris, seperti menjadi saksi pengesahan akta, mempersiapkan pembuatan akta, melakukan pengarsipan dokumen, menjaga kerahasian dokumen, dan beberapa tugas lainnya untuk membantu pelaksanaan jabatan Notaris. Undang-undang Nomor 2 Tahun 2014 Tentang Perubahan Undang-Undang Nomor 30 Tahun 2004 Tentang Peraturan Jabatan Notaris tidak memuat dengan jelas mengenai karyawan Notaris, sedangkan tidak dapat dipungkiri peran karyawan Notaris dibutuhkan dalam pelaksanaan jabatan Notaris. Perlunya kualifkasi tertentu yang dimiliki oleh karyawan Notaris agar dapat memaksimalkan peran Notaris dalam pelaksanaan jabatannya. Seorang karyawan Notaris setidaknya memiliki beberapa kriteria yang harus dimiliki untuk menjadi karyawan kantor Notaris karena berkaitan dengan pelaksanaan jabatan Notaris sebagai pejabat umum yang menuntut karyawan Notaris agar mampu menjaga kredibelitas dan integritas Notaris tempatnya bekerja. Notaris dalam pelaksanaan jabatannya bersifat independen tapi ini berkaitan dengan kewenangan pembuatan akta, sedangkan dalam pelaksanaan tata kelola kantor Notaris diperlukan peran dari karyawan kantor Notaris. Metode penelitian yang dipergunakan dalam penelitian ini adalah metode penelitian doktrinal dengan menggunakan pendekatan perundang-undangan (statue approach) dan pendekatan konseptual (conceptual approach).
Kecerdasan Buatan dalam Aspek Deforestasi dan Keberlanjutan Perkebunan: Pendekatan Bibliometrik Sutriani, Linda; Impron, Ali; Saragih, Veny Betsy; Anggraini, Syadza; Suraji, Suraji
LITERATUS Vol 6 No 2 (2024): Jurnal Ilmiah Internasional Sosial Budaya
Publisher : Neolectura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37010/lit.v6i2.1583

Abstract

This study examines the application of Artificial Intelligence (AI) in addressing deforestation and promoting sustainability in plantations using a bibliometric approach. Deforestation, a critical global issue, results from agricultural expansion, plantation development, and land-use changes, leading to significant environmental degradation. AI has been proposed as a powerful tool to monitor and manage deforestation more effectively, offering solutions such as satellite imagery analysis and predictive models. Through a bibliometric analysis spanning the last decade (2013–2023), this study uses VOSviewer to visualize co-citation networks, identifying key research trends and clusters related to AI in deforestation and plantation sustainability. The findings reveal that research is concentrated in regions like Indonesia and Brazil, where AI technologies like machine learning are employed to predict deforestation and enhance resource management. Emerging research areas include the integration of AI with the Internet of Things (IoT) and blockchain for improved data management and sustainability practices. This analysis provides insights into the growing role of AI in mitigating deforestation and offers recommendations for future research, including addressing ethical challenges and regulatory frameworks to further enhance sustainable plantation management.
IoT-Enabed Smart Mining:Pengelolaan Air Limbah di Industri Batubara Impron, Ali; Sutriani , Linda
Innovative: Journal Of Social Science Research Vol. 5 No. 1 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i1.16105

Abstract

Ensuring wastewater quality in coal mining operations is crucial to comply with environmental regulations. One of the key parameters is the pH level, which must be maintained within the range of 6-9. Currently, the monitoring process is manual, involving the use of litmus paper and visual comparison to estimate the pH level. The adjustment of pH is achieved by manually adding limestone until the desired range is met. This research proposes an automated solution leveraging Internet of Things (IoT) technology to streamline both monitoring and control processes. By integrating pH sensors into the water system and employing IoT-enabled relay controls for limestone dispensing, the system enables real-time pH monitoring and automatic limestone release. The proposed system aims to improve the efficiency and accuracy of wastewater treatment processes, aligning with the digitalization efforts and Industry 4.0 standards.
Analisis Pola Konsumsi Energi Listrik Rumah Tangga Berbasis Simulasi IoT Menggunakan Model Hybrid LSTM-Attention Impron, Ali
JURNAL INFORMATIKA DAN KOMPUTER Vol 9, No 2 (2025): Juni 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiko.v9i2.1922

Abstract

Pengelolaan energi listrik rumah tangga menjadi tantangan penting seiring meningkatnya kebutuhan energidan keterbatasan sumber daya. Penelitian ini mengusulkan pendekatan berbasis simulasi IoT untuk menganalisis pola konsumsi energi, mendeteksi anomali, dan memberikan rekomendasi efisiensi energi tanpa perangkat fisik, menggunakan model hybrid LSTM-Attention. Dataset simulasi (14.400 sampel) dibangun denganEnergyPlus, divalidasi terhadap data riil, dan diolah untuk mengevaluasi performa model. Hasil menunjukkan akurasi 96%, recall 0.95 untuk anomali, dan F1-score 0.96, melampaui baseline LSTM (91.5%). Mekanisme attention memprioritaskan power_usage_per_hour (bobot 0.47), meningkatkan deteksi anomali. Rekomendasi seperti penjadwalan ulang dan penggantian perangkat menghasilkan penghematan energi 20-40%. Dengan waktu pelatihan 1,5 jam pada Google Colab, pendekatan ini menawarkan solusi skalabel dan hemat biaya untuk pengelolaan energi berkelanjutan, dengan potensi pengujian riil dan peningkatan model di masa depan.
Analisis Sentimen Masyarakat Kalimantan Tengah Terhadap Perkebunan Kelapa Sawit Menggunakan TF-IDF dan Support Vector Machine Putra, Kurniawan Tri; Anggraini, Syadza; Sutriani, Linda; Suraji, Suraji; Impron, Ali
Journal Scientific of Mandalika (JSM) e-ISSN 2745-5955 | p-ISSN 2809-0543 Vol. 6 No. 5 (2025)
Publisher : Institut Penelitian dan Pengembangan Mandalika Indonesia (IP2MI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/10.36312/vol6iss5pp1115-1123

Abstract

The transformation towards Society 5.0 has had a significant impact on the rapid growth of data available worldwide, both useful and less directly beneficial, known as big data. This phenomenon provides opportunities for researchers to leverage big data as a valuable source of information, provided it is processed and analyzed using appropriate methods. One of the rapidly growing applications is sentiment analysis, which extracts insights from text data, such as that gathered from social media platforms. This study applies the TF-IDF feature extraction technique and the SVM (Support Vector Machine) classification method to perform sentiment analysis on Twitter text data. The results of the research show that the model built using the combination of TF-IDF and SVM achieved an accuracy of 86%, with precision, recall, and F1-Score values of 85% each. These findings indicate that the application of TF-IDF with SVM provides optimal performance in sentiment analysis, considering the word frequency within documents, and makes a significant contribution to processing big data for more accurate and effective sentiment analysis
Enhancing YOLOv5s with Attention Mechanisms for Object Detection in Complex Backgrounds Environment Impron, Ali; Lestari, Dina; Sutriani, Linda; Anggraini, Syadza; Rizal, Randi
Innovation in Research of Informatics (Innovatics) Vol 7, No 2 (2025): September 2025
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v7i2.16833

Abstract

Enhancing performance for object detection in complex environments is essential for real-world applications that represent complexities, such as stacking objects in the same location or environment. Models for detecting objects developed to this day still have difficulties in detecting objects with environments that have complex backgrounds. The reason is that the model often experiences a decrease in accuracy when the object to be detected is occlusion by other objects and is small in size. Therefore, in this study, a model improvement method was carried out in detecting objects in a complex environment. The algorithm used in this study is YOLOv5s. Optimization is carried out by adding a CBAM (Convolutional Block Attention Module) attention mechanism layer which is integrated with the C3 layer (C3CBAM) in the backbone of the YOLOv5s model architecture. In addition, a P2 feature map is also added to the architecture head. The optimization results carried out were quite satisfactory, namely there was an increase in the precision value by 1.6 %, at mAP@0.5 an increase of 1.4 %, and also mAP@50-95 increased by 0.1%. This proves that the enhancement method applied to YOLOv5s in this study can improve the performance of the model. However, with the addition of the attention mechanism layer, it turns out that it can increase the computational load. Therefore, for future research, a method can be applied to reduce computing load, one of the methods is knowledge distillation.
Co-Authors Asufie, Khairunnisa Noor Dina Lestari, Dina Linda Sutriani Nur Aripkah Putra, Kurniawan Tri Rizal, Randi suraji suraji Syadza Anggraini Veny Betsy Saragih