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All Journal Jurnal Ilmu Dasar BERKALA SAINSTEK JURNAL FISIKA Saintifika UNEJ e-Proceeding CogITo Smart Journal Jurnal Pendidikan Fisika dan Keilmuan (JPFK) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL GEOGRAFI Geografi dan Pengajarannya SAINTIFIKA Jurnal Pengabdian Masyarakat Nusantara

Puguh Hiskiawan

Department Of Physics, University Of Jember Jl. Kalimantan No. 37 Kampus Tegal Boto Jember 68121

Author-ID : 282331

Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Health Professions Industrial & Manufacturing Engineering Mathematics Medicine & Pharmacology Physics Social Sciences

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Pengaruh Pola Kontur Hasil Kontinuasi Atas Pada Data Geomagnetik Intepretasi Reduksi Kutub Puguh Hiskiawan
Jurnal Fisika Vol 5, No 2 (2015)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jf.v5i2.7421

Metode geomagnetik adalah salah satu metode geofisika yang digunakan untuk memeriksa struktur batuan di bawah permukaan bumi . Penelitian ini dipelajari dengan menggunakan pengaruh kontur kelanjutan atas didasarkan pada pengurangan data kutub . Penelitian ini menjelaskan untuk membandingkan pada pengukuran dan interpretasi data dengan beragam hasil kontur. Metode penelitian dilakukan studi lintasan-lintasan di daerah penelitian yang muncul geologi karakteristik fisik dalam pemantauan secara langsung dan pemantauan tidak langsung . Hasil penelitian ini disebut keuntungan dari nilai tertinggi yang masalah respon dari geomagnetik dan potensi konduktivitas contouring pada daerah diteliti paling tajam.

Pengaruh Pola Kontur Hasil Kontinuasi Atas pada Data Geomagnetik Intepretasi Reduksi Kutub Puguh Hiskiawan
saintifika Vol 18 No 1 (2016)
Publisher : FKIP Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (598.628 KB)

Attribute Geometrical Seismic for Fault Identifiction on Canada Exploration Field Agustiani, Reni; Hiskiawan, Puguh; Rano, Rano
Jurnal ILMU DASAR Vol 17 No 2 (2016)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

It has been performed data interpretation of 3D seismic data and drilling field exploration wellsBasin Nova ScotiaKanada to know structure fault on the field Missisauga Formation. Seismic dataused is 601 inline, crossline 482, and the data used drilling wells are two wells which there is a loggamma ray, sonic logs and log RHOB. Interpretation is done the analysis of the map in thestructure of time and analysis of seismic attribute maps based on the geometrical attribute serves todetermine their structure or structural faults of the data volume 3D. Based on the time structuremap well known that first well is in the region heights and second wells is in low region. Based oninterpretation of the map attributes known three faults are two major fault and one minor fault.Two faults are in the East Sea drilling wells and a small fracture that was on its western side. Thethree fults are directed from Northwest to the Southeast. Fault is expected to serve as ahydrocarbon trap in the area that will be accumulated in drilling wells. Keywords: geometrical attribute, Seismic data, drilling wells, time structure map.

PENDUGAAN INTRUSI AIR LAUT DENGAN METODE GEOLISTRIK RESISTIVITAS 1D DI PANTAI PAYANGAN DESA SUMBEREJO JEMBER Santoso, Teguh; Piyantari, Nurul; Hiskiawan, Puguh
BERKALA SAINSTEK Vol 1 No 1 (2013)
Publisher : Universitas Jember

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

Telah dilakukan penelitian di daerah Payangan Desa Sumberejo Kabupaten Jember dengan menggunakan metode geolistrik resistivitas 1-Dimensi konfigurasi Schlumberger untuk mengetahui litologi bawah permukaan terkait adanya pendugaan intrusi air laut di daerah tersebut. Dalam penelitian ini, setiap lintasan pengukuran mempunyai panjang 300 m. Data yang dihasilkan berbentuk nilai resistansi dan digunakan untuk mencari nilai resistivitas semu. Data tersebut kemudian diolah dengan menggunakan Software IPI2win dan Rockwork untuk mendapatkan pencitraan atau gambaran litologi batuan bawah permukaan. Dari hasil inversi menggunakan Software IPI2win dan Rockwork terlihat adanya intrusi air laut pada daerah tersebut. Hal tersebut dapat dilihat dari hasil pengolahan data keempat lintasan., pada lintasan 1, lintasan 2 dan lintasan 3 didominasi oleh batuan pasir dan kerikil, sehingga pada lintasan ini mudah ditembus oleh air laut. Sedangkan pada lintasan 4 berkemungkinan untuk tidak tertembus oleh air laut, hal ini dikarenakan pada lintasan ini terdapat lapisan lempung yang dapat dijadikan sumur oleh penduduk setempat.

A Hybrid Data Science Framework for Forecasting Bitcoin Prices using Traditional and AI Models Hiskiawan, Puguh; William, Jovan; Tio Jansel, Louis Feliepe
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10631

Bitcoin, a highly volatile and decentralized digital asset, presents considerable challenges for accurate price forecasting. This study proposes an applied data science framework that compares traditional statistical approaches with modern Artificial Intelligence (AI)-based models to predict Bitcoin’s daily closing price. Using BTC-USD historical data from January 2020 to December 2024, we converted prices into Indonesian Rupiah (IDR) to increase local relevance. Our forecasting horizon is 30 days, based on a 60-day lookback window. We evaluate six models: Linear Regression, ARIMA, and Prophet as traditional techniques, alongside Random Forest, XGBoost, and Long Short-Term Memory (LSTM) networks as AI approaches. All models were trained using lag-based or sequence-based time series features and evaluated using MAE, RMSE, R², MAPE, and SMAPE. Results show that AI models, particularly LSTM and XGBoost, offer better performance in capturing short-term non-linear dynamics compared to traditional models. LSTM provides high accuracy, though with greater computational demand, while XGBoost strikes a balance between speed and precision. Prophet and ARIMA remain effective for quick and interpretable forecasts but struggle with abrupt trend shift common in cryptocurrency markets. In addition to performance metrics, we include a robustness analysis based on median absolute error and outlier detection to assess model stability under extreme variations. Visual analytics—including forecast curves, error distributions, and uncertainty bounds—help interpret and communicate model behavior. This comprehensive evaluation offers practical insights for investors, analysts, and fintech practitioners, and the pipeline can be extended to other volatile assets.

PERFORMANCE EVALUATION OF 7TH GRADE STUDENTS FOR SOCIAL SCIENCE EDUCATION (IPS) UTILISING SUPPORT VECTOR MACHINE (SVM) METHOD Kristina, Jatim; Hiskiawan, Puguh
JURNAL GEOGRAFI Geografi dan Pengajarannya Vol 21 No 2 (2023): JURNAL GEOGRAFI Geografi dan Pengajarannya
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jggp.v21n2.p129-142

In this study, a Support Vector Machine (SVM) method was utilized to predict the 7th grade performance of social science education (IPS) within the following advanced levels and to delineated an evaluation of ongoing teaching plans for 7th grade teachers. The model dataset was built for 192 students, consisting of cognitive and psychomotor formative The dataset refers to three classification categories (Adequate, Qualified, and Skilled) employed in computational algorithms for processing using linear and non-linear (polynomial and gaussian). The SVM model performance evaluation results obtained a performance accuracy (ACC) of 84% (linear), 75% for polynomials, and gaussians (90%), respectively. The Mathew Correlation Coefficient (MCC) evaluation described a validated performance of 47% for linear, 40% and 20% for polynomial and gaussians, respectively. In conclusion, student performances can follow the learning optimally at the next level, while teachers can replicate the learning process for 7th grade in future classrooms.

Pelatihan Aplikasi Canva Berbasis AI sebagai Strategi Pengembangan SDM di KADIN Provinsi DKI Jakarta Agustian Sukarno, Ferry; Hiskiawan, Puguh; Christina, Livia; Tipani Tio, Cynthia
Jurnal Pengabdian Masyarakat Nusantara Vol 5 No 1 (2025): Desember 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/dimastara.v5i1.27291

Kegiatan pengabdian kepada masyarakat ini dilaksanakan dengan tujuan untuk meningkatkan literasi digital dan keterampilan pemanfaatan teknologi bagi pegawai Kamar Dagang dan Industri (KADIN) Provinsi DKI Jakarta. Sebagian besar pegawai KADIN termasuk dalam kelompok usia produktif menengah (35–50 tahun) yang memiliki pengalaman kerja tinggi, namun masih menghadapi tantangan dalam adaptasi terhadap perkembangan teknologi digital, khususnya aplikasi berbasis kecerdasan buatan. Untuk menjawab kebutuhan tersebut, Fakultas Teknologi dan Desain Universitas Bunda Mulia menyelenggarakan pelatihan penggunaan aplikasi Canva berbasis Artificial Intelligence (AI) sebagai sarana peningkatan kompetensi SDM. Pelatihan mencakup pemahaman konsep dasar AI dalam desain grafis, pengenalan fitur-fitur otomatis Canva, serta praktik langsung dalam pembuatan materi visual seperti media sosial, presentasi, dan promosi. Hasil kegiatan menunjukkan peningkatan kemampuan peserta dalam mengoperasikan Canva secara mandiri dan kreatif, dengan efisiensi waktu kerja yang lebih baik. Selain itu, pelatihan ini juga menumbuhkan kesadaran akan pentingnya literasi digital dan kolaborasi berbasis teknologi dalam mendukung transformasi digital di lingkungan kerja KADIN.

Assessing Information Security Readiness in Indonesian Fintech Companies Using KAMI Index 5.0 Framework Lestari, Merryana; Puspita, Maria Entina; Geasela, Yemima; Wijaya, Agustinus Fritz; Hiskiawan, Puguh; Vicky, Vicky
CogITo Smart Journal Vol. 11 No. 2 (2025): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v11i2.837.271-280

The development of Indonesian financial technology (fintech) has transformed the financial industry paradigm but has also introduced significant information security risks, particularly for technology-based companies. The fintech companies should establish IT governance through an Information Security Management System (ISMS) which adheres to international standards, ensuring the confidentiality, integrity, and availability of information. This work adopts a qualitative approach deploying observations, interviews, and literature reviews on Indonesian fintech companies, especially digital banking fields, payment gateways, and digital wallet platforms. This study is to identify information security risks and assess the readiness and feasibility of implementing ISO/IEC 27001:2022 using the KAMI Index 5.0, which evaluates domains such as policy, governance, risk management, access control, incident management, asset management, and personal data protection. The research findings indicate that the electronic system of fintech companies plays a strategic role in supporting sustainability and business growth, with an implementation score of 809 and a fairly good level of information security feasibility. In conclusion, this reflects the company’s readiness for further information security implementation. The system not only supports basic operations but also serves as a key element in achieving business objectives, both internally and externally, including regulators, banking partners, and customers.

Co-Authors A.A. Ketut Agung Cahyawan W Agustian Sukarno, Ferry Agustinus Fritz Wijaya Artoto Arkundato Christina, Livia Fitri Rizqi Azizah Geasela, Yemima Himmah Khasanah Illavi Praseti Pebrian Kristina, Jatim Merryana Lestari Nurul Piyantari Puspita, Maria Entina Rano Rano, Rano Reni Agustiani, Reni Ruliyanti Ruliyanti Sri Hartanto Supriyadi Supriyadi Supriyadi Supriyadi Teguh Santoso Tio Jansel, Louis Feliepe Tipani Tio, Cynthia Vicky, Vicky William, Jovan Yudhistira Adi Nugraha

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