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STRATEGI PENGEMBANGAN PARIWISATA DI KABUPATEN TULUNGAGUNG Ida Gemawati Monda; Imam Fachruddin
Jurnal Mediasosian : Jurnal Ilmu Sosial dan Administrasi Negara Vol 2, No 2 (2018): September 2018
Publisher : Universitas Kadiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (322.58 KB) | DOI: 10.30737/mediasosian.v2i2.209

Abstract

This study aims to analyze the strategies that have been implemented by the local government of Tulungagung District in developing tourism. This study uses a qualitative approach to interpret the experiences of informants related to tourism development activities. At least, the strategy that has been used is to synergize all related institutions and optimize the role of tourism villages. The inhibiting factor that emerges is the geographical location of tourist attractions that are difficult and are disaster-prone areas, while a significant supporting factor is the presence of social media that can bring tourists without requiring substantial resources.
Early Detection of Seismic Signal Anomalies Using Raspberry Pi 5 and Lightweight Machine Learning Models Ahmad Kadarisman; Imam Fachruddin; Santoso Soekirno; Hanif Andi Nugraha; Benyamin Heryanto Rusanto; Martarizal
Joint Prosiding IPS dan Seminar Nasional Fisika Vol. 14 No. 1 (2026): Joint Prosiding IPS dan Seminar Nasional Fisika
Publisher : Program Studi Pendidikan Fisika dan Program Studi Fisika Universitas Negeri Jakarta, LPPM Universitas Negeri Jakarta, HFI Jakarta, HFI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/03.1401.FA14

Abstract

Data integrity is crucial for seismic monitoring systems, but is often compromised by anthropogenic or instrumental anomalies. This paper proposes a lightweight edge computing framework using Raspberry Pi 5 for real-time anomaly detection. MiniSEED data from the high-noise TOJI station were processed through segmentation, statistical or spectral feature extraction, and unsupervised models (isolation forest and autoencoder). The results show a detection latency of 78-113 ms with minimal resource consumption (<35% CPU, <200 MB RAM) and 82% correlation with ground-truth anomalies. This framework can be used on networked seismographs with limited resources such as those of the BMKG.
Development of Terminal and Ship Operational Integration System for Docking and Berthing Time Optimization Based on Historical Data Irfan Faozun; Larsen Barasa; Natanael Suranta; Ronald Simanjuntak; Imam Fachruddin
Green Engineering: International Journal of Engineering and Applied Science Vol. 3 No. 1 (2026): January: Green Engineering: International Journal of Engineering and Applied Sc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v3i1.262

Abstract

This research investigates the development of integrated operational systems connecting terminal and ship operations for docking and berthing time optimization through systematic analysis of historical data. Port efficiency depends critically on minimizing vessel turnaround time, with berth allocation, docking procedures, and cargo operations coordination determining overall port productivity and competitiveness. Through qualitative analysis involving port operators, terminal managers, ship agents, harbor masters, and operations research specialists, this study examines how historical operational data can inform intelligent coordination systems improving berthing efficiency. Results demonstrate that data-driven integration systems incorporating predictive analytics, automated scheduling, and coordinated workflows can reduce average berth turnaround time by 15-30%, improve berth utilization by 20-35%, and decrease operational conflicts by 40-60% through optimized allocation and proactive coordination. Key implementation challenges include data quality and availability, system integration complexity, organizational coordination barriers, and resistance to automated decision support. Findings reveal that historical data-based optimization represents transformative advancement from experience-based scheduling to evidence-driven operational planning supporting port efficiency enhancement, capacity maximization, and service reliability improvement. This research contributes to port operations literature by providing practical frameworks for data-driven berthing optimization applicable to diverse port operational contexts.