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All Journal MANAJEMEN HUTAN TROPIKA Journal of Tropical Forest Management Jurnal Manajemen dan Organisasi Jurnal Manajemen dan Agribisnis Jurnal Sosio Ekonomika Bisnis JURNAL SISTEM INFORMASI BISNIS Jurnal Manajemen Teknologi Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) JAM : Jurnal Aplikasi Manajemen Indonesian Journal of Business and Entrepreneurship (IJBE) Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Journal of Consumer Science Jurnal Manajemen Teori dan Terapan Journal of Information Systems Engineering and Business Intelligence Cosmogov: Jurnal Ilmu Pemerintahan Proceeding of the Electrical Engineering Computer Science and Informatics International Research Journal of Business Studies (E-Journal) Agregat: Jurnal Ekonomi dan Bisnis Journal of Regional and Rural Development Planning Jurnal Organisasi Dan Manajemen Buletin Ilmiah Litbang Perdagangan JURNAL MANAJEMEN INDUSTRI DAN LOGISTIK Applied Information System and Management Petir Aptisi Transactions on Technopreneurship (ATT) International Journal of Business Studies Jurnal Ilmiah Manajemen Kesatuan Journal of Applied Data Sciences Business Review and Case Studies International Journal of Engineering, Science and Information Technology Indonesian Journal of Multidisciplinary Science AGRARIS: Journal of Agribusiness and Rural Development Research Asian Journal of Social and Humanities International Research Journal of Business Studies
Arif Imam Suroso
School Of Business, IPB University, Jl. Raya Pajajaran, RT.03/RW.06, Babakan, Kecamatan Bogor Tengah, Kota Bogor, Jawa Barat 16128
Agriculture, Biological Sciences & Forestry Humanities 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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation

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Time Series Forecasting of Environmental Dynamics in Urban Ecotourism Forest Using Deep Learning Iskandar, Ade Rahmat; Suroso, Arif Imam; Hermadi, Irman; Prasetyo, Lilik Budi
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1029

Abstract

Time Series Forecasting of Environmental Dynamics in urban forests is quite challenging, unless new approaches such as deep learning and remote sensing are employed. Deep learning-based time series algorithms offer robust scientific capabilities for forecasting and assessing sustainability trends using sequential data. Among these, Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bidirectional LSTM (BiLSTM) have gained widespread adoption across various predictive modeling domains. In the present research, these algorithms are employed to analyze urban forest raster data derived from the Srengseng Ecotourism Forest, located in West Jakarta, Indonesia. The present study focuses on predicting the temporal patterns of key spatial indicators: Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and Forest Cover Density (FCD) in the Srengseng urban ecotourism forest area, spanning the years 2014 to 2024, through the application of LSTM, GRU, and BiLSTM deep learning architectures. The methodology used in this study is a combined approach involving remote sensing and deep learning. Spatial data were acquired through the delineation of a high-precision polygon of Srengseng Urban Forest using Google Earth Pro and Google Earth Engine (GEE). GeoTIFF datasets of NDVI, LST, and FCD for the years 2014–2024 were processed using Python-based modeling scripts. Model performance was evaluated through a comparative analysis of LSTM, GRU, and BiLSTM in predicting temporal trends in these ecological indicators. The results of this study show that the Bidirectional LSTM (BiLSTM) consistently demonstrated superior performance to predict all the data spatially, with scores of 0.94 for NDVI, 0.90 for FCD, and 0.85 for LST. Followed by LSTM that predicts NDVI (0.87), FCD (0.89), LST (0.83), as well as GRU, which can estimate spatial data NDVI (0.86), FCD (0.89), and LST (0.85). These results outperformed the predictive accuracy of both the standard LSTM and GRU models.
Analysis of the Impact of Customer Experience and Engagement on Satisfaction and Loyalty in the Body Shop's Omnichannel Ghifari, Nurul Afiifah; Suroso, Arif Imam; Hannan, Sufrin
Asian Journal of Social and Humanities Vol. 4 No. 4 (2026): Asian Journal of Social and Humanities
Publisher : Pelopor Publikasi Akademika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/ajosh.v4i4.665

Abstract

This study examines the impact of customer experience and engagement on customer satisfaction and loyalty within the omnichannel strategy employed by The Body Shop in Indonesia. As the cosmetic and personal care market experiences rapid growth, it is essential for companies to deliver an integrated experience across both online and offline channels. A seamless and consistent customer experience across various touchpoints can significantly enhance customer engagement, which in turn drives satisfaction and fosters loyalty. The research employs a quantitative approach with purposive sampling, analyzing data using Structural Equation Modeling-Partial Least Square (SEM-PLS). The results indicate that customer experience has a positive and significant effect on both engagement and satisfaction, which ultimately contributes to improved customer loyalty. The findings offer valuable insights for companies in shaping more effective omnichannel strategies, aiming to enhance customer satisfaction and loyalty in a sustainable manner. By understanding these dynamics, businesses can refine their approach to integrating online and offline experiences, ensuring they meet the evolving expectations of customers and strengthen long-term relationships. This research provides practical recommendations for companies in the cosmetic and personal care industry to remain competitive in an increasingly digital marketplace.
Successful Organizational Transformation Strategy of PT Wijaya Karya (PERSERO) TBK Yantama, Rian Rizki; Suroso, Arif Imam; Safari, Arief
Indonesian Journal of Multidisciplinary Science Vol. 5 No. 4 (2026): Indonesian Journal of Multidisciplinary Science
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/ijoms.v5i3.1227

Abstract

This study aims to examine the extent to which internal factors, external factors, transformation strategy, and organizational alignment influence the success of WIKA’s transformation agenda. An explanatory quantitative approach was employed using Structural Equation Modeling–Partial Least Squares (SEM-PLS), based on responses from 134 employees and structural officials directly involved in the transformation process. The study investigates five latent constructs: Internal Factors, External Factors, Transformation Strategy (sensing, seizing, and reconfiguring), Organizational Alignment (structural, process, cultural, and team-based consistency), and Transformation Success (financial and non-financial performance). Data analysis was conducted using SmartPLS through a comprehensive evaluation of both the measurement and structural models. The empirical results indicate that both internal and external factors serve as significant drivers of transformation strategy. Furthermore, transformation strategy exerts a substantial direct effect on organizational alignment, which functions as a critical mediating mechanism linking strategic direction to transformation success. Organizational alignment is also proven to have a strong direct impact on overall transformation performance, underscoring the importance of aligned structural design, cultural readiness, and human resource capabilities as prerequisites for successful change. This study enriches the theoretical discourse on organizational transformation in State-Owned Enterprises by integrating the perspectives of dynamic capabilities, strategic alignment, and change management. Practically, the findings offer actionable insights for WIKA and similar SOEs in formulating integrated, capability-oriented transformation roadmaps grounded in organizational culture.
Strategic Business Diversification and Competitive Positioning in Railway Infrastructure Maintenance Qorry, Akhmad Yani; Suroso, Arif Imam; Taryana, Asep
Jurnal Ilmiah Manajemen Kesatuan Vol. 14 No. 1 (2026): JIMKES Edisi January 2026
Publisher : LPPM Institut Bisnis dan Informatika Kesatuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37641/jimkes.v14i1.4642

Abstract

The growth of the national railway industry, the expansion of rail networks, and the increasing safety standards have driven the need for more modern, integrated, and sustainable railway infrastructure maintenance services. These conditions create opportunities to diversify into the railway infrastructure maintenance business. This study aims to formulate appropriate strategies for the company to enter the industry competitively. The research uses a descriptive qualitative approach supported by quantitative analysis. This research integrates the PESTLE framework, Porter’s five forces, VRIO, SWOT–TOWS, and the quantitative strategic planning matrix. Data were collected through expert interviews, questionnaires, and document analysis. The results show that the track maintenance industry has high entry barriers, significant dependence on OEMs, strong buyer power, and complex technological and certification requirements. However, opportunities emerge through long-term Public-Private Partnership (PPP) contracts, urban/HSR projects, maintenance digitalization, and technical specialization in track and slab-track segments. The priority strategies derived include forming OEM alliances, strengthening equipment capacity, establishing an internal certification academy, and adopting predictive maintenance to improve tender scores and SLA performance. These findings provide strategic direction to expand its portfolio and strengthen competitiveness in the railway maintenance sector.
Enhancing MSME Digital Marketing through Public-Private Partnerships with Fuzzy AHP Bahukeling, Trukan Sri; Suroso, Arif Imam; Buono, Agus; Nurhayati, Popong
Aptisi Transactions On Technopreneurship (ATT) Vol 8 No 1 (2026): March
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v8i1.667

Abstract

Public Private Partnership (PPP) is a contractual arrangement between government and private institutions to share resources, tools, and expertise for delivering public services. In Indonesia, PPPs have been widely applied in infrastructure sectors, but little attention has been given to their role in supporting micro, small, and medium enterprises (MSMEs) in adopting digital marketing. This study aims to build a PPP institutional scenario for implementing digital marketing in MSMEs and to formulate a priority strategy for strengthening PPP-based digital marketing policy. A mixed-method approach was employed, combining scenario planning with the Fuzzy Analytical Hierarchy Process (FAHP). Data were collected from 17 experts through in-depth interviews and analyzed using scenario modeling and fuzzy weighting techniques. The findings indicate that developing institutional guidelines, establishing a task force, fostering commitment, and creating PPP patterns are key strategies to enhance MSMEs’ digital adoption. The results highlight the importance of government investment in digital infrastructure, training programs, and supportive regulations. This research provides practical contributions for policymakers in strengthening PPP-based digital ecosystems and academic contributions by advancing scenario-based decision-making for sustainable MSME development.
HOW OPEN INNOVATION IMPLEMENTATION IN DIGITAL ENTERPRISES INFLUENCES INDONESIA GOVERNMENT POLICY Yuana, Rivira; Prasetio, Eko Agus; Syarief, Rizal; Suroso, Arif Imam; Arkeman, Yandra
CosmoGov: Jurnal Ilmu Pemerintahan Vol 8, No 2 (2022)
Publisher : Department of Government, FISIP, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/cosmogov.v8i2.42529

Abstract

The nature of new business innovation activities is increasingly scattered, multidisciplinary, cross-border, cross-institutional, and cross-temporal. The culture influences the commitment to open innovation. The organizational culture is a vital factor in the success of radical innovation and integrating internal organizational structures, policies, and partnerships. The paradigm shift from closed to open innovation has been used in various business relationships.The research objectives are determining the primary factor of open innovation success in Indonesia based on digital enterprise experiences and the extent to which the government's participation becomes meaningful and results in adaptive corporate policy.The study will be qualitative and inductive, utilizing multiple case studies. Due to the epidemic period, in-depth interviews with senior management were conducted through video conferences and private messaging. The research will employ a literature review and an expert interview to ascertain how digital enterprise cooperation contributes to long-term growth. The result shows how the O.I. strategy implemented in digital firms influences government policy.The Indonesian government may enlist the assistance of international organizations or multinational corporations to facilitate organizational reforms necessary to create an open innovation-friendly culture. Goverment businesses require specialized staff to reap the benefits of present legislation.gb777
Risk Mitigation of PGA Surgical Suture Distribution in Distribution Companies Alfonsia Febriyana; Hermanto Siregar; Arif Imam Suroso
Jurnal Aplikasi Bisnis dan Manajemen Vol. 11 No. 1 (2025): JABM, Vol. 11 No. 1, Januari 2025
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.11.1.1

Abstract

Background: The demand for PGA surgical suture is increasing, which was recorded from 2017-2019, reaching 148 million in the world and 1.2 million in Indonesia. This is in line with the increase in surgery. Currently, many foreign medical device products are supplied from imports, reaching 70%, and have high prices. PT XYZ is one of the medical device distributor companies that collaborates with companies in the European region as suppliers. The company often experiences problems in procuring product inventory because it depends on one supplier, which affects supply chain performance and creates various risks in its business processes.Purpose: This research focused on risk mitigation at PT XYZ.Design/methodology/approach: The HOR analysis and fishbone method.Findings/Result: Based on the HOR analysis and fishbone method, 3 priority sources of risk that must be mitigated are supplier errors, fluctuating demand, and limited storage space. Furthermore, the mitigation that must be done is to encourage suppliers to build factories in Indonesia, provide quarterly order forecasting, and hold regular meetings for evaluation and strategy making. Keywords: fishbone, house of risk, PGA surgical suture, risk, risk mitigation
Factors Influencing E-Commerce Purchases of Halal Cosmetics: A UTAUT2 Approach Fildza Shabrina Meta; Arif Imam Suroso; Asep Nurhalim
Jurnal Aplikasi Bisnis dan Manajemen Vol. 11 No. 2 (2025): JABM Vol. 11 No. 2, May 2025
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.11.2.536

Abstract

Background: The rapid growth of information technology has transformed business activities, particularly through e-commerce, which facilitates seamless transactions between producers and consumers. In Indonesia, internet penetration reached 78.19% in 2023, driving demand for halal cosmetics online and necessitating insights into consumer behavior to enhance market reach and trust.Purpose: This study identifies factors impacting consumer intentions in purchasing halal cosmetics online utilizing an extended UTAUT2 model with a Trust variable.Design/Methodology/Approach: This study utilizes a quantitative survey design to gather 260 responses from e-commerce users who purchase halal cosmetics. Structural Equation Modeling-Partial Least Squares (SEM-PLS) analyzed the relationship among variables.Findings: All performance expectancy, social influence, facilitating conditions, hedonic motivation, price value, habit, and trust are significant factors influencing the consumer intention and behavior. Among these, habits emerged as the most influential factor, indicating that habitual use is instrumental to the formation of purchasing behaviors.Conclusion: Based on these findings, it further suggests that the e-commerce platforms should put great effort into building consumer trust via robust security systems, thorough technical support, as well as personalized, fun shopping to ultimately help the halal cosmetics market to prosper.Originality/Value (State of the Art): This study incorporates Trust into the UTAUT2 model to improve understanding of strategies that will optimize halal e-commerce. Keywords: consumer behavior, e-commerce, halal cosmetics, trust, UTAUT2
Daily Production Prediction Model of Oil Wells Using Backpropagation Neural Network Arif Wicaksono; Arif Imam Suroso; Nur Hasanah
Jurnal Aplikasi Bisnis dan Manajemen Vol. 11 No. 3 (2025): JABM Vol. 11 No. 3, September 2025
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.11.3.804

Abstract

Background: Measuring well production is a crucial task in upstream oil and gas operations, where various tests and measurements are standard procedures and integral parts of operational activities. More frequent production measures are required to detect production declines in mature fields. However, existing daily production testing at the Langgak field, Central Sumatra Basin, cannot be routinely and periodically conducted due to several economic and technical challenges. Purpose: The objective of this article is to create a model for predicting daily crude oil well production.Design/methodology/approach: To achieve this goal, the study applies an artificial neural network (ANN) for forecasting daily crude oil well production, utilizing 17,394 daily production records from 26 wells. This sample size is well above recommended thresholds for neural network models, ensuring sufficient data for robust model training and validation. The backpropagation algorithm and the sigmoid function are employed as the learning algorithm to predict daily crude oil well production. Findings/Result: The optimal parameters for predicting daily crude oil well production were 20 hidden nodes and a learning rate of 0.05, converging at 481 epochs with a training time of 13 seconds.Conclusion: Model performance was indicated by high correlation coefficients (R) across training, validation, and testing phases, along with a low Mean Squared Error (MSE). The resulting regression equation, Output = 1 × Target + 0.00024, confirms a near-perfect alignment with the target function.Originality/Value (State of the art): Although this study employs the standard backpropagation neural network (BPNN) architecture an established method in oil production forecasting it contributes original value by rigorously applying 10-fold cross-validation on an 80:20 train-test split of the Langgak field dataset, thereby enhancing model reliability and offering validated insights for forecasting in mature oil fields; a foundation upon which future research can build using hybrid or more advanced neural architectures shown to yield superior accuracy. Keywords: artificial neural network, backpropagation, oil production forecasting, machine learning, yield prediction
Strategy for Developing Business Kebun Latte Restaurant As A Culinary Tourism Destination Rafi Dharmawan; Arif Imam Suroso; Sufrin Hannan
Jurnal Aplikasi Bisnis dan Manajemen Vol. 11 No. 3 (2025): JABM Vol. 11 No. 3, September 2025
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jabm.11.3.858

Abstract

Background: Kebun Latte Restaurant has a concept of a teak plantation atmosphere and offers a diverse menu, making it one of the top choices for culinary tourism. However, Kebun Latte Restaurant has experienced a decline in revenue over the past three years, and there are several revenue streams that have not been maximized. Given the modern lifestyle trends of today's society, the restaurant company must anticipate changes and implement business model development strategies to enhance competitiveness and ensure the company remains a sustainable choice as a culinary tourism destination..Purpose: This research aims to identify the condition of the company using the business model canvas, then formulate alternative strategies so as to produce priority strategy recommendations that are implemented as a new business model formulation for Kebun Latte restaurant.Design/methodology/approach: This research was conducted from August 2023 to September 2024 and involved five respondents who had five years of experience in the tourism industry, particularly in the restaurant sector. In addition, the information received was processed using the business model canvas method, IFE and EFE, IE Matrix, SWOT analysis and Analytical Hierarchy Process (AHP).Finding/Result: The results of the study show nine elements of the business model canvas at Kebun Latte. The SWOT analysis shows 10 alternative strategies, and based on the AHP analysis, there are three strategic priorities, namely: improving marketing by highlighting the Instagrammable outdoor concept, maintaining and improving product quality, and developing products towards sustainability. These results provide changes in the formulation of the new version of the business model canvas.Conclusion: The results of this study provide strategic priorities to be implemented by the company, including increasing marketing by emphasizing the concept of instagrammable outdoors, maintaining and improving product quality and developing products towards sustainability. This affects the development of the 6 elements of the business model canvas.Originality/value (State of the art): The new Kebun Latte restaurant business model has a competitive advantage as a culinary tourism destination, namely the existence of sustainable products supported by an instagrammable outdoor concept. Keywords: analytical hierarchy process, business model canvas, culinary tourism, swot, strategy development
Co-Authors Abdul Mufti Ade Rahmat Iskandar Adler Haymans Manurung Agus Buono Agustian, Fajar Aida Vitayala Hubeis Aji Hermawan Akbar, M Lucky Alfonsia Febriyana Alfy Sukma Amru Sahmono Boang Manalu Andi Tenri Abeng Anggraini Sukmawati Anggraini, Raden Isma Arief Ramadhan Arief Ramadhan Arif Wicaksono Arkeman, Yandra Arsyanur, Mustika Retno Asep Nurhalim Asep Taryana Azka Bazil Danish Rahmat Bachtiar, Muchamad Bahukeling, Trukan Sri Bambang Juanda Bandono, Bayu Bernadus, Benny Bimo Andono Budi Setiawan Chandra, Mohamad Citra, Suryati Oka Dede Wahidin Jafar Dewi Suryani Dewi, Nina Kurnia Dirdjosaputro, Sukiswo Edi Suryanto Eko Agus Prasetio Eko Agus Prasetio Endang Gumbira Sa'id Erliza Noor Euis Sunarti Fadhil Muhammad Fahrillah, Ahmad Ariq Fajar Agustian Ferdi Novalendo Fety Nurlia Muzayanah Fildza Shabrina Meta Ghifari, Nurul Afiifah Gunawan Gunawan Hadiwidjaja, Rini Dwiyani Hafizh, Muhammad Damar Hanindipto, Fasa Aditya Hansen Tandra Hansen Tandra Hariandja, Nancy Megawati Haryono, Adi Hendro Sasongko Heny Kuswanti Suwarsinah HERMANTO SIREGAR Hermanto Siregar Hilda Puspita Pratyaharani I Gusti Ayu Indira Maharani Idqan Fahmi Ilham Ananto Yuwono Illah Sailah Irman Hermadi Iyung Pahan Jaman, Jajam Haerul Joko Ratono Joko Ratono Joko Ratono, Joko Juniar Prayogi Juniar Prayogi Khairiyah Kamilah Kudang B. Seminar Kudang Boro Seminar LILIK BUDIPRASETYO Lilik Noor Yuliati Loeis, Minaldi Lukman M. Baga M, Misbahudddin M. Syamsul Maarif Maesaroh, Syti Sarah Marimin , Meilani, Lala Meuthia Rachmaniah Mohammad Syamsul Maarif Muhamad Syukur Mukhamad Najib MULYANI Musa Hubeis Neni Seliana Ninuk Purnaningsih Nugraha, Herry Nugraha, Windy Maudy Atiah Putri Nur Adhita Rahmawati Nur Hasanah Nur Hasanah NUR HASANAH Nurhidayat, Ridwan Pahan, Iyung Permasih, Desta Popong Nurhayati Prabantarikso, Mahelan Pramadia Satriawan Priastuti, Dila Qorry, Akhmad Yani Rafi Dharmawan Rahmana, Adhitya Rahmanto, Mohamad Ridwan Rini Dwiyani Hadiwidjaja Rinova Budiman Rita Nurmalina Rivira Yuana Rizal Broer Bahaweres Rizal Syarief Rizal Syarief Rizal Syarief Rizal Syarief Rizki, Yanis Aulia Rokhani Hasbullah Romayah, Siti Rotua Siahaan RR. Kathrin Irviana Ruth Johana Angelina Safari, Arief Saiful Bahri Seliana, Neni Setiadi Djohar Setiadi Djohar Setyo Wibowo Shalihati, Fithriyyah Siti Jahroh Siti Romayah Suci Ramadhani, Suci Sufrin Hannan Sufrin Hannan Sugiarto, Anto Tri Sugiharto Soeleman Suprehatin Suprehatin Supriyadi Supriyadi Sutriono Edi Tandra, Hansen Tendy Arya Pranata Trias Andati Ujang Sumarwan Utami, Yulistiana Endah Widhiani, Anita Primaswari Widia Citra Anggundari Yamin, Fadhilah Bt Mat Yandra Arkeman Yandra Arkeman Yani Nurhadryani Yantama, Rian Rizki YELLY REFITA Yuana, Rivira Yuni Sugiarti, Yuni Yunus Triyonggo Yunus Triyonggo, Yunus Yusman Syaukat Zahid, Rifqi Az