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A TAXONOMY OF STRATEGIES FOR INDUSTRY 4.0 IMPLEMENTATION IN INDONESIA Wibowo, Budhi Sholeh
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 11, No 1 (2019): MEI
Publisher : Sekolah Tinggi Teknologi Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (323.801 KB)

Industry 4.0 tidak hanya membawa peluang besar namun juga berpotensi membawa imbas negatif bagi perkembangan industri di Indonesia. Makalah ini bertujuan untuk membangun taksonomi strategi penerapan Industry 4.0 di Indonesia melalui pemetaan 33 sektor manufaktur di Indonesia. Penelitian dilakukan berdasarkan statistik kinerja sektor industri besar yang diukur berdasarkan tujuh variabel yaitu: jumlah perusahaan, input, output, nilai tambah, biaya tenaga kerja, dan perubahan modal. Dengan menggunakan analisis klaster, kami mendapatkan bahwa penerapan Industry 4.0 di Indonesia dapat dibagi menjadi 4 strategi utama, yaitu: automasi, kolaborasi, biasa, dan bisnis model baru. Taksonomi strategi ini relevan bagi perencana kebijakan publik dalam menerapkan Industry 4.0 di Indonesia.

A TAXONOMY OF STRATEGIES FOR INDUSTRY 4.0 IMPLEMENTATION IN INDONESIA Budhi Sholeh Wibowo
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 11, No 1 (2019): Mei
Publisher : Institut Teknologi Dirgantara Adisutjipto

Industry 4.0 tidak hanya membawa peluang besar namun juga berpotensi membawa imbas negatif bagi perkembangan industri di Indonesia. Makalah ini bertujuan untuk membangun taksonomi strategi penerapan Industry 4.0 di Indonesia melalui pemetaan 33 sektor manufaktur di Indonesia. Penelitian dilakukan berdasarkan statistik kinerja sektor industri besar yang diukur berdasarkan tujuh variabel yaitu: jumlah perusahaan, input, output, nilai tambah, biaya tenaga kerja, dan perubahan modal. Dengan menggunakan analisis klaster, kami mendapatkan bahwa penerapan Industry 4.0 di Indonesia dapat dibagi menjadi 4 strategi utama, yaitu: automasi, kolaborasi, biasa, dan bisnis model baru. Taksonomi strategi ini relevan bagi perencana kebijakan publik dalam menerapkan Industry 4.0 di Indonesia.

A data-driven investigation of successful local film profiles in the Indonesian box office Budhi Sholeh Wibowo; Farizka Rubiana; Budi Hartono
Jurnal Manajemen Indonesia Vol 22 No 3 (2022): Jurnal Manajemen Indonesia
Publisher : Fakultas Ekonomi dan Bisnis, Telkom University.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmi.v22i3.4106

Many local film industries in developing economies are struggling to compete with foreign film hits. Surprisingly, despite the high exposure from imported films, the Indonesian film industry has maintained a robust domestic market in the last decade. This study aims to gather insights from this phenomenon by examining the key factors that distinguish the profiles of non-successful and successful local films at the Indonesian box office. The analysis was conducted based on the characteristics of 225 local films from 2017 to 2018. We employed a recent method to generate such profiles, namely the tree-based comparative analysis, which uses a machine learning model to augment the cross-case comparisons from a large pool of data. The study result suggests that the success of local films is mainly driven by the actor's popularity and the presence of foreign movie hits at the box office. Besides, we also found that the distinction between moderately successful and highly successful local films predominantly lies in story familiarity, suggesting the efficacy of the "brand extension" strategy in the Indonesian film industry. The study concludes by offering some managerial insights for producers and distributors to deliver successful films at the box office. Keywords— local film; Indonesian box office; success profiles; tree-based comparative analysis

Developing New Indonesia Circular Economy Indicators: A Lesson Learnt from European Union Siti Afiani Musyarofah; Alva Edy Tontowi; Nur Aini Masruroh; Budhi Sholeh Wibowo; IDAA Warmadewanthi; Arman Hakim Nasution; Mohamad Khoiru Rusydi; Gogor Arif Handiwibowo; Gita Widi Bhawika
IPTEK Journal of Proceedings Series No 1 (2023): The 1st International Conference on Community Services and Public Policy (ICCSP) 2022
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23546026.y2023i1.16368

Circular Economy (CE) right now has been a point of interest among countries in the world as a commitment of the Paris Agreement to solve global environmental problems, which are simultaneously beneficial to economics. However, presently there is no single indicator available that easily be used as a CE standard due to various stresses among the countries. There are different approaches among countries in developing CE indicators, although they are still within the scope of the environmental and economic aspects. CE indicators could be developed based on region covering several countries, government/country level, and company level. Those indicators refer to the region and government policy and market or users of the product and a society where its public area would receive waste that the company might produce. This review will discuss only European Union and Poland, representing regions and countries. A region like the European Union (EU) considers ten indicators for CE, consisting of 21 sub-indicators. These indicators include self-sufficiency in raw materials, procurement for the green public, waste generation, food waste, recycling rate, recovery of specific waste streams, recycled materials to raw materials demand contribution, raw material trade-in, investment, jobs, and gross value-added, patents of secondary and recycling raw materials. While Poland, as a member of the EU, developed 25 CE indicators based on the seven dimensions of the economic point of view, such as economic prosperity, zero waste, innovative, renewable energy- based economy, low carbon, smart economy, and spatially effective economy. Implementing a Comparative Analysis Method that compares one indicator to another, the results show that 6 of 10 indicators belonging to the EU overlap with four indicators of 25 belonging to Poland. Covering all indicators of both regions and countries, thus it would become 29 selected indicators that might be useful for developing Indonesia CE- Indicators, which are presently unavailable yet.

A FRAMEWORK FOR OBSERVATIONAL DATA-BASED RESPONSE SURFACE METHODOLOGY Hadiyat, Mochammad Arbi; Sopha, Bertha Maya; Wibowo, Budhi Sholeh
JEMIS (Journal of Engineering & Management in Industrial System) Vol 12, No 2 (2024): (in process)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

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

Response Surface Methodology (RSM) is an integrated tool for optimization purposes based on an experiment; it consists of three stages of analysis, i.e., the design of experiment (DoE), causality modeling, and response optimization. The designed experiment ensures the researcher fully controls all factors that potentially influence the response and simultaneously fulfills the orthogonal assumption among factors. On the other side, conducting DoE for a continuous production process raises difficulties since it should be interrupted during experiment runs. Meanwhile, the rapid development of production data acquisition systems provides stored records or observational data with potentially useful information for supporting process optimization. This paper proposes an alternative framework for adopting observational data for RSM analysis. Referring to three stages of classic RSM and adopting the instance selection concept in the data mining context, the proposed framework aimed to achieve an observational data condition similar to an orthogonal D-optimal DoE based on criteria of Variance Inflation Factor (VIF) and determinant of matrix containing factor levels. It starts by applying a genetic algorithm for iteratively selecting an orthogonal subset of observational data and generating new actual experiment points to satisfy an orthogonality criterion. Then, a linear RSM model is fitted and continued by adding new experiment points. Then a standard numerical optimization method is applied to search among factor levels that optimize the response. A simulated data-based case study was taken in this paper, aiming to maximize a response of a production process with some pre-determined factors. The proposed framework has been implemented successfully, orthogonality of the data subset is achieved, and an optimal solution is found. Both criteria show the acceptable result and raise some improvement opportunities

Temporal preferences for ambiance: A study of tourist expectations across the day Agustina, Rischa; Wibowo, Budhi Sholeh
Asian Management and Business Review Volume 5 Issue 1, 2025
Publisher : Master of Management, Department of Management, Faculty of Business and Economics Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/AMBR.vol5.iss1.art3

Existing studies have recognized the significance of ambiance in influencing tourist behavior and preferences. However, little attention has been given to exploring tourist preferences for specific ambiances throughout the day. This study aims to fill this gap by examining whether temporal preferences for ambiance exist in tourism. We used the Kansei Engineering method to identify the specific ambiance tourists expect at different times of day: morning, afternoon, and evening. A survey of 200 domestic tourists in Yogyakarta, Indonesia, was conducted using semantic differential questionnaires. The results suggest five distinct constructs of ambiance that reflect tourist expectations at different times of the day. The results confirm the existence of temporal preferences for ambiance across the day. Specifically, tourists visiting Yogyakarta prefer peaceful, nature-centric attractions in the morning, cultural experiences and popular places in the afternoon, and romantic ambiances in the evening. Further analysis reveals that this pattern aligns with natural circadian rhythms. This study provides valuable insights for stakeholders to improve tourist experiences by aligning offerings with these temporal preferences.

A FRAMEWORK FOR OBSERVATIONAL DATA-BASED RESPONSE SURFACE METHODOLOGY Hadiyat, Mochammad Arbi; Sopha, Bertha Maya; Wibowo, Budhi Sholeh
JEMIS (Journal of Engineering & Management in Industrial System) Vol. 12 No. 2 (2024)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

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

Response Surface Methodology (RSM) is an integrated tool for optimization purposes based on an experiment; it consists of three stages of analysis, i.e., the design of experiment (DoE), causality modeling, and response optimization. The designed experiment ensures the researcher fully controls all factors that potentially influence the response and simultaneously fulfills the orthogonal assumption among factors. On the other side, conducting DoE for a continuous production process raises difficulties since it should be interrupted during experiment runs. Meanwhile, the rapid development of production data acquisition systems provides stored records or observational data with potentially useful information for supporting process optimization. This paper proposes an alternative framework for adopting observational data for RSM analysis. Referring to three stages of classic RSM and adopting the instance selection concept in the data mining context, the proposed framework aimed to achieve an observational data condition similar to an orthogonal D-optimal DoE based on criteria of Variance Inflation Factor (VIF) and determinant of matrix containing factor levels. It starts by applying a genetic algorithm for iteratively selecting an orthogonal subset of observational data and generating new actual experiment points to satisfy an orthogonality criterion. Then, a linear RSM model is fitted and continued by adding new experiment points. Then a standard numerical optimization method is applied to search among factor levels that optimize the response. A simulated data-based case study was taken in this paper, aiming to maximize a response of a production process with some pre-determined factors. The proposed framework has been implemented successfully, orthogonality of the data subset is achieved, and an optimal solution is found. Both criteria show the acceptable result and raise some improvement opportunities

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