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EDUKASI BUILDING INFORMATION MODELING (BIM) PADA KONTRAKTOR KECIL Jati Utomo Dwi Hatmoko; Mochamad Agung Wibowo; Frida Kristiani; Riqi Radian Khasani; Rizki Fatmawati; Geofanny Dominica Sihaloho
Jurnal Pasopati : Pengabdian Masyarakat dan Inovasi Pengembangan Teknologi Vol 2, No 3 (2020)
Publisher : Fakultas Teknik Universitas Diponegoro

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

Abstract

Sektor konstruksi merupakan salah satu sektor yang penting di Indonesia karena menyediakan berbagai infrastruktur dan prasarana bagi berbagai kegiatan ekonomi masyarakat. Data mutakhir badan usaha kontraktor konstruksi yang teregistrasi secara nasional tahun 2012 menunjukkan jumlah mayoritas pelaku industri konstruksi adalah kontraktor berkualifikasi kecil (87%), sehingga kualitas dari kinerja kontraktor kecil akan menjadi cerminan dari kualitas industri konstruksi Indonesia secara umum. Mayoritas dari kontraktor kecil tersebut mempunyai banyak permasalahan klasik antara lain menyangkut kapasitas, kompetensi, dan daya saing rendah dan keterbatasan akses permodalan, keterbatasan kompetensi SDM serta keterbatasan penguasaan teknologi dan sistem manajemen. Selain itu, kontraktor kecil masih banyak yang tidak bisa memenuhi target biaya, mutu dan waktu yang direncanakan. Maksud diadakannya sosialisasi Building Information Modeling (BIM) untuk kontraktor kecil adalah untuk memberikan dasar-dasar pengetahuan dan keterampilan tentang teknologi BIM. Tujuannya adalah untuk membuka wawasan peserta tentang prinsip-prinsip dan dasar-dasar mengenai teknologi BIM. Sasaran utama dari kegiatan pelatihan ini adalah para pemilik atau pengelola kontraktor kecil di daerah Semarang dan sekitarnya yang tercatat dalam asosiasi kontraktor di bawah naungan Lembaga Pengembangan Jasa Konstruksi (LPJK) Jawa Tengah. Metode yang akan digunakan dalam kegiatan ini adalah sebuah bentuk sosialisasi yang akan disampaikan melalui metode ceramah dan diskusi.  Kata kunci : kontraktor, BIM, sosialisasi
Pengukuran Kinerja Rantai Pasok Konstruksi Berkelanjutan dengan Pendekatan Model Supply Chain Operations Reference (SCOR) 12.0 Moh Nur Sholeh; Mochamad Agung Wibowo; Undayani Cita Sari
Jurnal Vokasi Indonesia Vol 8, No 2: July - December 2020
Publisher : Program Pendidikan Vokasi Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.7454/jvi.v8i2.159

Abstract

The challenge of construction supply chain management is to maintain supply and demand in the supply chain flow and ensure a sustainable supply chain in the framework of lean construction. This challenge must be captured as part of the solution of the development of the rapidly growing construction industry. At present a sustainableSCOR on the Supply Chain Operations Reference (SCOR) version 12.0 has been developed. SustainableSCOR is a concept of a sustainable supply chain performance measurement approach by considering environmental aspects. The aim of this study is to adopt a supply chain performance measurement model in the sustainable construction of SCOR 12.0. The research method adopts standards, categories, and matrices in sustainableSCOR to a constructionally validated definition to academics and practitioners. The discussion of the supply chain continues with the calculation of each matrix. The results showed that all sustainableSCOR categories, namely materials, recycled inputs, recovered inputs, energy, water, emissions, and waste can be adopted to measure sustainable supply chain performance in construction. The adoption of this performance measurement needs to be detailed into one of the construction materials, in this study is steel material.
FAKTOR PENERAPAN NORMATIF GREEN CONSTRUCTION PADA PEMBANGUNAN THE ALTON APARTEMEN Rani Pranita; Mochamad Agung Wibowo; Broto Sunaryo
Wahana Teknik Sipil: Jurnal Pengembangan Teknik Sipil Vol 27, No 1 (2022): Wahana Teknik Sipil
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/wahanats.v27i1.3672

Abstract

Green Construction is a continuous movement to create quality construction. The government in responding to the management of the implementation of green construction issues regulations that are expected to become development guidelines. This study aims to identify the application of green construction in the implementation of the construction of The Alton Apartement to achieve the performance that has been determined with a rationalistic positivistic approach. The research methodology uses qualitative methods with in-depth interviews with triangulation to determine its validity. The result is the level of normative application of green construction in the implementation of apartment construction projects, three levels of application are obtained which show the results of the identification of the normative application of green construction. The level of implementation of III was 37% where these aspects have been carried out in a sustainable manner. The level of implementation of II reached 41%, where the implementation has been carried out well. The level of implementation of I is at 22%, which means that the implementation in the field has not been implemented properly.
Supply Chain Performance Measurement Framework for Construction Materials: Micro Meso Macro Moh Nur Sholeh; Mochamad Agung Wibowo; Naniek Utami Handayani
Jurnal Optimasi Sistem Industri Vol. 19 No. 2 (2020): Published in October 2020
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (128.303 KB) | DOI: 10.25077/josi.v19.n2.p101-110.2020

Abstract

Productivity is a challenge in the construction industry, commonly initiated by fragmentation. In addition, some work levels have been identified, including the micro, meso, and macro. However, the construction supply chain is one of the possible solutions adopted to increase productivity. The purpose of this study, therefore, is to develop a framework for measuring supply chain construction performance at the micro, meso, and macro levels. These respective stages are tiered from the bottom to the top level as a supply chain management concept. Furthermore, a design for the supply chain performance measurement framework is created, followed by formulation with KPI, and the consequent application in the project. Therefore, performance is evaluated based on the construction materials, as a large resource. The results identified the supply chain performance at the micro-level as the basis for possible measures between contractor and supplier, using the SCOR. However, the emphasis was made on the strength of construction companies with large suppliers at the meso level. Meanwhile, the macro-level includes the accumulation of related measurements from micro as well as meso, and are consequently used to define the relationship between construction actors at the national level.
Multimodal Implicit Sentiment Analysis for Tourism Development: A Systematic Literature Review Yoannes Romando Sipayung; Mochamad Agung Wibowo; Ridwan Sanjaya
Journal of Information System and Informatics Vol 8 No 1 (2026): February
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i1.1436

Abstract

This study aims to examine the application of multimodal approaches in implicit sentiment detection within the tourism sector to support data-driven digital development strategies. This review identifies prevailing trends, methodologies, datasets, and scientific novelties in multimodal sentiment analysis capable of capturing hidden emotions, such as sarcasm and ambiguity, in tourist reviews. Using a systematic literature review approach, ten core studies published between 2020 and 2025 were analyzed to identify prevailing research trends, dominant methodological frameworks, commonly used datasets, and emerging scientific contributions. Results demonstrate that multimodal deep learning models—particularly those employing attention-based fusion and contrastive learning—consistently outperform unimodal approaches in recognizing nuanced tourist emotions that are not explicitly stated in text. Despite these advances, the review reveals a significant gap in tourism-specific and Indonesian-context studies, as well as an overreliance on general-purpose social media datasets. This review provides a conceptual and methodological foundation for implementing multimodal implicit sentiment analysis in tourism decision-making systems, enabling destination managers and policymakers to develop early warning mechanisms for tourist dissatisfaction, enhance destination quality assessment, and support more targeted and sustainable tourism development strategies.
A Hybrid Ensemble Stacking Framework Integrating Long Short-Term Memory and Random Forest for Bitcoin Price Forecasting Akhlis Munazilin; Mochamad Agung Wibowo; Rizky Parlika
Journal of Information System and Informatics Vol 8 No 2 (2026): April
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i2.1537

Abstract

Bitcoin is a non-linear and non-stationary digital asset that has become a highly volatile asset challenging the usual prediction models. In this paper, the authors present a problem-specific Hybrid Ensemble Stacking approach, the proposed approach, which combines the benefits of Long Short-Term Memory (LSTM) in terms of capturing long-term temporal variations with the power of Random Forest (RF) to process complex technical characteristics. The model follows a two-tier structure with a split ratio of 90:10 using BTC/USD historical data of Yahoo Finance and Binance (20102025) to combine the predictions of base learners with the use of a Linear Regression meta-learner. Findings show that pure LSTM has a low RMSE and MAE, but the Hybrid model has the best Mean Absolute Percentage Error (MAPE) of 3.54%. This means that the stacking mechanism will provide a more balanced error percentage, that is, it will enhance stability in forecasting at the phases of price discovery. It is novel in the sense that it uses macro-technical indicators to stabilize predictions in the face of market anomalies as a stacking scheme. These results have real-life implications on developers of financial systems in creating consistent crypto-asset risk management instruments.
Real-Time Explainable Concept Drift Detection for Eco-Driving in Mining Trucks using KSWIN and Event-Triggered SHAP Kusnawi; Mochamad Agung Wibowo; Ridwan Sanjaya
Journal of Information System and Informatics Vol 8 No 2 (2026): April
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i2.1551

Abstract

Fuel consumption represents a significant operational cost in mining, where real-time eco-driving optimization is hindered by dynamic and non-stationary operating conditions. Variations in operator behavior and environmental factors often induce concept drift, which diminishes the reliability of static machine learning models and constrains the effectiveness of conventional drift detection methods. This study proposes a distribution-aware, event-triggered Explainable Artificial Intelligence (XAI) framework for detecting and diagnosing fuel consumption anomalies in streaming telematics data. A Hoeffding Tree Regressor was evaluated using a prequential scheme on 1,927,867 real-world observations, achieving a Mean Absolute Error (MAE) of 19.43 under non-stationary conditions. Concept drift was monitored using the Kolmogorov–Smirnov Windowing (KSWIN) algorithm, which detected 1,874 drift events. Upon detection, an event-triggered SHAP module identified contributing factors, indicating that behavioral features such as engine speed and accelerator position were dominant contributors in early drift events. The primary contribution of this study is the integration of distribution-based drift detection with event-triggered explainability within a unified streaming framework, facilitating both anomaly detection and interpretable root-cause analysis.
Mapping the Global Landscape of Electronic Supply Chain Management (e-SCM): A Bibliometric and Visual Analysis Aditya Lapu Kalua; Mochamad Agung Wibowo; Luther Alexander Latumakulita
Journal of Information System and Informatics Vol 8 No 2 (2026): April
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i2.1525

Abstract

This study maps the intellectual structure of global electronic supply chain management (e-SCM) research through a bibliometric analysis of Scopus-indexed publications published between 2015 and 2025. The retrieval workflow began with the Scopus query TITLE-ABS-KEY ("supply chain management") and was followed by structured interface-based refinement using pub- lication period, subject area, and document type constraints to construct the final analytical corpus. Bibliometric performance indicators were analyzed using the Bibliometrix R- package, while science mapping and network visualization were conducted using VOSviewer. The findings show that the e-SCM literature is organized around five major thematic concen- trations: sustainability in supply chain management, environmental and circular-economy integration, operational decision support and risk analytics, sectoral and stakeholder coordi- nation, and the recent acceleration of blockchain, Industry 4.0, and digital transformation. Co-authorship and country-level mappings indicate a multicentric global research structure led by China, India, and the United Kingdom, while temporal overlay visualization shows a marked shift toward digitally enabled governance and resilience-oriented research during 2022–2023. These results provide an evidence-based synthesis of the evolution of the field and a replicable bibliometric foundation for future sector-specific studies in sustainability- sensitive supply networks.
Design and Evaluation of a Decision Support System for Classifying Tourism Site Crowding and Recommending Governance Responses in Bunaken National Park Aditya Kalua; Mochamad Agung Wibowo; Luther Alexander Latumakulita
Jurnal Testing dan Implementasi Sistem Informasi Vol. 4 No. 1 (2026): Jurnal Testing dan Implementasi Sistem Informasi
Publisher : Lembaga Riset dan Inovasi Almatani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/jtisi.v4i1.2232

Abstract

Effective governance of marine protected areas (MPAs) requires reliable mechanisms to translate multidimensional ecological and social data into coordinated institutional action. Despite widespread adoption of carrying capacity frameworks, a significant "implementation gap" persists between theoretical conservation thresholds and operational decision-making at the site level. This study addresses that gap by designing, implementing, and evaluating a Decision Support System (DSS) artifact tailored for Bunaken National Park (BNP), Indonesia. Grounded in Design Science Research (DSR) principles, the artifact employs a deterministic, rule-based classification engine that processes four normalized input dimensions visitor density, social carrying capacity, infrastructure load, and governance readiness to compute a Composite Crowding Index (CCI). The CCI is mapped through an explicit IF-THEN rule engine to four crowding categories (Low, Moderate, High, Extreme), each linked to a validated governance action package. A deterministic rule-based approach was chosen over probabilistic or machine-learning alternatives to ensure full decision traceability, which is a non-negotiable requirement for public-sector governance. System robustness was evaluated through structured scenario testing across 140 logic-coverage cases, assessed against four criteria: output consistency (100%), expert rule alignment (97.8%), decision traceability (100%), and processing efficiency (<1.15 seconds per scenario). The artifact successfully automates the mapping of site-level crowding status to discrete, auditable governance actions. The theoretical contribution lies in formalizing subjective management reasoning into a transparent, reproducible DSS that bridges sustainability science and institutional practice in high-pressure marine tourism environments.