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All Journal OPSI STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Jurnal Sistem Teknik Industri Rahmatan Lil’alamin Journal of Community Services (RLA) Jurnal INFOTEL Spektrum Industri
Purnama, Dwi Adi
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Social Sciences Other

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Unlocking Indonesia's Maritime Potential: Optimizing Hub Port Development using a Principal Component Analysis and K-Means Clustering Purnama, Dwi Adi; Marifa, Putri Citra; Shinta, Riadho Clara
Jurnal Sistem Teknik Industri Vol. 27 No. 1 (2025): JSTI Volume 27 Number 1 January 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i1.18606

Abstract

Indonesia as a maritime country, most of the transportation in Indonesia is carried out by using sea transportation around 88%. However, the Logistics Performance Index (LPI) of Indonesia is alarming and declining from 3.15 in 2018 to 3.0 in 2023, particularly in Timeliness (3.7 to 3.0) and Tracking & Tracing (3.3 to 3.0). Therefore, it needs a comprehensive improvement strategy, especially to optimize the hub port connectivity. This study would like to establish the new hub port connectivity in Indonesia to increase the effectiveness and efficiency of the port. This study use Principle Component Analysis (PCA) to determine the variable, eliminate the correlation among variables to obtain the new variables as the clustering determinants factor, and use Clustering K-Means to group similar characteristics of the alternative port that can be used as the main port. The result of Principle Component Analysis (PCA) which has gained new variables are regional spatial system, national transportation system, national defense, operational cost, and port services. The result of K-Means Clustering, Tanjung Priok, Panjang, Tanjung Emas, Tanjung Perak, Palembang, Teluk Bayur, and Belawan are the main port or hub port connectivity to increase the effectiveness and efficiency in the sea transportation. Tanjung Priok and Panjang can connect Java and Sumatra, while Tanjung Emas and Tanjung Perak can link Java and South Kalimantan. Palembang, Teluk Bayur, and Belawan can also play important roles in their respective regions. By investing in infrastructure and improving connectivity, Indonesia can enhance the efficiency and competitiveness of its maritime trade.
Data Mining Menggunakan Association Rules-Market Basket Analysis untuk Peningkatan Kinerja Ritel Tradisional Purnama, Dwi Adi
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 9, No 3 (2025)
Publisher : Universitas Indraprasta PGRI Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/string.v9i3.28707

Abstract

Traditional retail, as well as micro, small, and medium-sized firms, play an important part in the Indonesian economy. However, with the rise of progressive business competition, such as competition from modern retail, traditional retail requires a strategy to better its business and performance. The purpose of this study is to identify consumer behavior in traditional retail based on data mining using Association rules-market basket analysis (AR-MBA). Data were gathered by collecting 150 shopping transactions. Furthermore, the pre-processing stage involved data cleansing, transformation, and reduction. The study's findings revealed that several association rules were established and validated. Based on these findings, various insights were obtained, including the fact that department 3 (snacks) is the most purchased item and is associated with items in other departments; there are association rules between powdered drinks and snacks, candy and snacks, toiletries, snacks, instant noodles and snacks, cigarettes and flavored drinks, and mineral water and flavored drinks. The findings are used to improve the performance and to expand the retail industry. This study recommends product stock management by increasing the number of products that consumers frequently purchase, product marketing strategies such as discounts, product bundling, and other promotions, and layout proposals based on association rules.
Peningkatan Softskills dan Hardskills pada Anak Panti Asuhan Nurul Haq, Yogyakarta Koeswandana, Noorfaiz Athallah; Purnama, Dwi Adi; Prasetyo, Eko; Agustin, Anggia Fitria; Laksita, Aisya Galuh; Sabila, Rahma; Nugroho, Wakhid Aji; Kamal, Muhammad Rijal; Istianah, Indah; Rahman, Dina Aulia; Octyaningsih, Zulvina
Rahmatan Lil 'Alamin Journal of Community Services Volume 5 Issue 1, 2025
Publisher : Department of Accounting, Faculty of Business and Economics, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/RLA.Vol5.iss1art4

Abstract

Pengembangan softskills dan hardskills merupakan langkah penting dalam membekali anak-anak panti asuhan untuk menghadapi tantangan kehidupan di masa depan. Penelitian ini bertujuan untuk mengidentifikasi kebutuhan, merancang, dan mengevaluasi program peningkatan softskills dan hardskills di Panti Asuhan Nurul Haq, Yogyakarta. Hasil menunjukkan bahwa program ini berhasil meningkatkan kepercayaan diri, kemampuan berkomunikasi, dan kerja sama tim sebagai bagian dari softskills. Di sisi lain, peningkatan keterampilan teknis seperti penguasaan teknologi dasar dan keterampilan praktis juga tercapai. Selain memberikan manfaat langsung kepada anak-anak panti, program ini membuka peluang untuk pengembangan model pembinaan serupa di panti asuhan lainnya. Penelitian ini menyimpulkan bahwa pengembangan softskills dan hardskills secara terintegrasi dapat memberikan dampak positif yang signifikan, baik dalam aspek sosial maupun ekonomi anak-anak panti. Diharapkan, program ini dapat menjadi langkah awal untuk menciptakan generasi muda yang lebih mandiri, kompetitif, dan mampu berkontribusi dalam masyarakat.
A machine learning-driven Six Sigma framework for enhancing the quality improvement and productivity in the Aircraft Manufacturing Purnama, Dwi Adi; Alfiqra, Alfiqra; Cahyo, Winda Nur
OPSI Vol 18 No 1 (2025): OPSI - June 2025
Publisher : Jurusan Teknik Industri, Fakultas Teknologi Industri UPN "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/opsi.v18i1.13960

Abstract

The aviation industry, a pillar of global transportation, is under constant pressure to increase productivity and efficiency while maintaining strict quality requirements.  Airctraft defects in production can result in significant financial losses, lead to costly rework, delays, and even safety risks. This study proposes a framework to improve productivity and efficiency in aircraft manufacturing and analyze quality control using machine learning, Six Sigma, and the QCDSME (Quality-Cost-Delivery-Safety-Morale) method. The DMAIC (Define-Measure-Analyze-Improve-Control) stage is a reference in the implementation steps of the Six Sigma method of the Airbus A320. The sigma value in this study was obtained on average for 40 periods of 4.61 sigma and a DPMO of 1225.69. At the analyze stage, a fishbone diagram is used to find the root cause of the problem.  Furthermore, a machine learning analysis was performed using the text mining method to identify the most common product components that frequently have defects in Airbus A320 and identify the main factors causing defects, by the human factor.  The enhance stage suggests a rise in overcoming challenges with the QCDSME method. Overall, it was discovered that the number of defects fell while the sigma improved and this method can enhance industry performance.
Bahasa Inggris Purnama, Dwi Adi
JURNAL INFOTEL Vol 17 No 3 (2025): August
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i3.1289

Abstract

The industry is currently faced with rapid technological developments, including the challenges of industry 5.0. Therefore, it is necessary to develop advanced technology to improve automation and digitalization in the industrial sector. One of them is mining information from social media data, which produces large amounts of data storage (big data). Thus, there is potential to use social media data as a basis for policies to improve company performance. This study takes a case study of the telecommunications industry in Indonesia, using the Principal Component Analysis (PCA) and Principal Component Regression (PCR) methods. Big data is obtained from social media review data with a period of 33 weeks from unstructured data on telecommunications service products in Indonesia. The text mining stage produces 30 selected words for further analysis with PCA to produce the main components. Based on the evaluation results, the main components formed show a good correlation with the company's performance in the stock market based on five stock index indicators (price-open, high, low, close, and volume); at least there is one main component equation that shows a strong correlation. This shows the potential for using a data mining approach based on social media reviews as a basis for decision-making to improve company performance. Furthermore, the dominant variables formed from PCA are considered to obtain a simple mathematical model.
Measuring Supply Chain Performance and Developing Competitive Strategy on Small Medium Enterprise Craft Industry using SCOR-AHP Model Purnama, Dwi Adi; Novianto, Didin Dwi; Haryanti, Nur Laily
Jurnal Sistem Teknik Industri Vol. 27 No. 3 (2025): JSTI Volume 27 Number 3 July 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i3.20336

Abstract

Small and medium enterprises (SMEs) require support to evolve into established organizations due to their strong flexibility to change. Nonetheless, numerous obstacles confront SMEs in their efforts to develop and compete. This study seeks to evaluate supply chain performance and the formulation of competitive strategies inside small and medium-sized enterprises (SMEs). This serves as an option for assessing supply chain performance while emphasizing the formulation of competitive strategies to enhance it, encompassing the management of material, information, and financial flows from both supply and demand perspectives. The evaluation of supply chain performance is conducted with the SCOR model, which relies on the identification of Key Performance Indicators (KPIs) derived from the outcomes of the SMEs business mapping process. Subsequently, multi-criteria decision making (MCDM) employing the Analytical Hierarchy Process (AHP) is utilized to assign weights to the KPI criteria for assessing supply chain performance and guiding competitive strategy creation. The study's results identified the indicators categorized into planning, production, sourcing, delivery, and returns. The measurement of supply chain performance suggests that the case study industry has a value of 84.11, signifying commendable performance. Moreover, competitive strategies, using Kraljic Matrix, Six Sigma, Lean Method, or mixed strategies, have been suggested to enhance supply chain performance and business competition, informed by the outcomes of the SCOR model and the MCDM approach.
Modeling Public Transportation Policy Using Macroscopic Social Media Data Mining Adi Purnama, Dwi; Anugrah Muzaffar Rana, Zahid; Pinkan Lumi, Distian; Tahta Haritza, Inggil; Fadhillah, M. Arif
Spektrum Industri Vol. 23 No. 2 (2025): Spektrum Industri - October 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/si.v23i2.327

Abstract

Transportation policies must be created by the government, especially in countries with high population expansion, transportation services are used more to meet daily necessities. Conventional surveys to gauge public opinion are costly and slow; social media offers a macro-level proxy that can complement official data. This study employs large-scale online data mining to build decision support for transportation policy. We collected 19,806 Indonesia-based Twitter posts referencing public transport, private transport, sustainable mobility, and electric vehicles. After preprocessing, we fine-tuned IndoRoBERTa for sentiment classification and applied Latent Dirichlet Allocation for topic modeling. The sentiment model achieved 81.17% accuracy, with precision, recall, and F1-scores all above 0.80. Positive discourse concentrated on private vehicles, public transit, multimodal travel, and environmentally responsible practices, with many users endorsing eco-friendly private cars. Negative discourse emphasized severe air pollution, frequently attributing risk to emissions from private automobiles in Jakarta. Translating these insights into policy, we propose expanding electric-vehicle charging infrastructure, implementing vehicle buy-back/retirement programs, establishing low-emission zones, and promoting biofuels. The results demonstrate that macroscopic social media analytics can surface actionable public preferences and pain points, enabling near-real-time monitoring to inform adaptive and equity-oriented transportation policies. This framework provides a scalable approach for governments in rapidly growing contexts to align service provision with community sentiment while advancing sustainability goals.
Co-Authors Agustin, Anggia Fitria Alfiqra, Alfiqra Anugrah Muzaffar Rana, Zahid Cahyo, Winda Nur Eko Prasetyo Fadhillah, M. Arif Haritza, Inggil Tahta Haryanti, Nur Laily Istianah, Indah Kamal, Muhammad Rijal Koeswandana, Noorfaiz Athallah Laksita, Aisya Galuh Marifa, Putri Citra Novianto, Didin Dwi Nugroho, Wakhid Aji Octyaningsih, Zulvina Pinkan Lumi, Distian Rahman, Dina Aulia Rana, Zahid Anugrah Muzaffar Sabila, Rahma Shinta, Riadho Clara Tahta Haritza, Inggil