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All Journal Bubungan Tinggi: Jurnal Pengabdian Masyarakat Jurnal UNITEK International Journal of Engineering, Science and Information Technology West Science Social and Humanities Studies Journal of Industrial Engineering and Management
Arlis Dewi Kuraesin
Universitas Teknologi Muhammadiyah Jakarta
Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering 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 Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Pemberdayaan Masyarakat Mengolah Kemangi Hasil Pekarangan Menjadi Minuman “Kemaruk” di Desa Sumberwaru Kecamatan Wringinanom Kabupaten Gresik Herni Setyawati; Nuris Kushayati; Christina Astutiningsih; Sri Budyartati; Arlis Dewi Kuraesin
Bubungan Tinggi: Jurnal Pengabdian Masyarakat Vol 5, No 1 (2023)
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/btjpm.v5i1.7670

Abstract

Desa Sumberwaru Kecamatan Wringinanom Kabupaten Gresik merupakan desa dengan mata pencaharian utamanya adalah petani dan buruh pabrik. Desa Sumberwaru berpotensi dengan lahan subur dan jumlah Sumber Daya Manusia (SDM) yang cukup untuk mendukung pengembangan Desa. Selain itu  pekarangan atau lahan kosong di sepanjang      jalan biasa ditanam berbagai tanaman diantaranya  kemangi. Selama ini pemanfaatan kemangi hanya digunakan dalam bentuk sayuran atau lalapan. Kurangnya pengetahuan  masyarakat tentang pengolahan minuman berbahan herbal, menjadikan mereka kurang maksimal dalam memanfaatkan hasil tanaman. Tujuan Pengabdian Kepada Masyarakat  ini untuk memberikan informasi, edukasi dan praktek secara langsung pemanfaatan bahan herbal yang ada di sekitar lingkungan tempat tinggal masyarakat. Melalui pemberian   edukasi dan pelatihan tentang cara pengolahan dan pemanfaatan tanaman herbal menjadi minuman fungsional kesehatan yang benar.  Tanaman kemangi dapat dikembangkan menjadi produk kesehatan  fungsional yang  bernilai ekonomis  lebih tinggi dengan cara meramu kemangi dengan jeruk nipis menjadi minuman  “Kemaruk”. Metode pelaksanaan  dilakukan melalui ceramah, demonstrasi dan workshop     , kepada Kader PKK sejumlah 29 orang di Kantor kelurahan setemt, pada hari Senin, tanggal 27 Juni 2022.  Evaluasi terhadap hasil pretest tentang pengolahan kemangi dengan tingkat pemahaman lebih dari 80% sebesar 20,7% meningkat menjadi 86,2%.  Indikator lain selama kegiatan 96,5%  warga  antusias, untuk mempraktekkan dan semua peserta mau meminum hasil buatannya..Sumberwaru Village, Wringinanom District, Gresik Regency, is a village whose main livelihoods are farmers and factory workers. Sumberwaru Village has the potential with fertile land and a sufficient number of Human Resources (HR) to support Village development. In addition, yards or vacant land along roads are usually planted with various plants, including basil. So far, basil is only used as vegetables or fresh vegetables. The lack of public knowledge about the processing of herbal-based drinks makes them less optimal in utilizing plant products. This Community Service aims to provide information, education and direct practice of using herbal ingredients around the community's living environment through education and training on how to process and utilize herbal plants to become healthy functional drinks. Basil plants can be developed into functional health products that have higher economic value by mixing basil with lime to become a "Kemaruk" drink. The implementation method was conducted through lectures, demonstrations and workshops, for 29 PKK cadres at the local village office, on Monday, 22 June 2022. Evaluation of the results of the pretest regarding the processing of basil with an understanding level of more than 80% by 20.7% increased to 86.2%. Another indicator was that 96.5% of residents were enthusiastic about practising it and 100% about consuming it. 
Peran Infrastruktur Hijau Perkotaan dalam Meningkatkan Kualitas Udara di Jakarta Muhammad Lukman Baihaqi Alfakihuddin; Asmuni Hasyim; Arlis Dewi Kuraesin; Boni Sena; Louise Elizabeth Radjawane
JURNAL UNITEK Vol. 17 No. 1 (2024): Januari - Juni
Publisher : Sekolah Tinggi Teknologi Dumai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52072/unitek.v17i1.776

Abstract

Tujuan dari penelitian ini adalah untuk menyoroti peran infrastruktur hijau perkotaan dalam mengurangi polusi udara yang berbahaya bagi kesehatan manusia dan dengan demikian meningkatkan kualitas udara di Jakarta. Metode penelitian ini adalah pengumpulan data, pengamatan penginderaan jauh, dan analisis data dengan memanfaatkan berbagai informasi yang disediakan oleh Badan Meteorologi, Klimatologi dan Geofisika (BMKG) dan beberapa situs terpercaya yang menyediakan informasi yang diperlukan terkait polusi udara di Jakarta. Pengamatan di Jakarta di lakukan pada dua puluh titik. Sedangkan pengamatan di kota Bogor di lakukan pada dua titik. Data yang diperoleh dari pengamatan jarak jauh di dua puluh lokasi di Jakarta menyebutkan, kualitas udara di Jakarta rata-rata berada pada level tidak sehat. Sedangkan data yang diperoleh berdasarkan hasil pengamatan di kota Bogor menunjukkan bahwa kualitas udara di Bogor masih sehat. Rata-rata kualitas udara di Jakarta adalah 131. Sedangkan rata-rata Rata-rata kualitas udara di Bogor adalah 31.
The Role of Transition Finance, Renewable Energy Investment, and Climate Risk Management on the Financial Performance of Energy Companies in Indonesia Sev Rahmiyanti; Iin Wijayanti; Khusnatul Zulva; Arlis Dewi Kuraesin; Kristanti Rahman
West Science Social and Humanities Studies Vol. 4 No. 03 (2026): West Science Social and Humanities Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsshs.v4i03.2701

Abstract

This study examines the role of transition financing, renewable energy investment, and climate risk management in influencing the financial performance of energy companies in Indonesia amid the global transition toward a low-carbon economy. A quantitative approach was employed using primary data collected from 75 managers and professionals in the energy sector through a structured questionnaire measured on a five-point Likert scale. The data were analyzed using SPSS version 25 through descriptive statistics, validity and reliability tests, classical assumption tests, and multiple linear regression analysis. The results indicate that transition financing has a positive and significant effect on financial performance, suggesting that access to sustainable financing mechanisms supports corporate financial stability during the energy transition. Renewable energy investment also shows a significant positive influence, indicating that investment in clean energy technologies enhances operational efficiency and long-term competitiveness. Furthermore, climate risk management significantly affects financial performance, highlighting the importance of identifying and mitigating climate-related risks to maintain corporate financial resilience. Simultaneously, the three variables significantly influence financial performance with an R² value of 0.480, indicating that 48% of the variation in financial performance can be explained by the model. These findings demonstrate that the integration of sustainable financial strategies and environmental risk management practices can improve the financial performance of energy companies, while also contributing empirical evidence to the literature on climate finance and corporate sustainability and offering practical insights for managers, investors, and policymakers in supporting the transition toward sustainable energy systems.
Human-Centered Artificial Intelligence Framework for Adaptive Inventory Decision Support under Supply Chain Uncertainty Arlis Dewi Kuraesin; Asyari Asyari
International Journal of Engineering, Science and Information Technology Vol 6, No 3 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i3.1905

Abstract

Supply chain uncertainty has increased the complexity of inventory decision-making due to demand fluctuations, supplier disruptions, and rapidly changing operational conditions. Although artificial intelligence (AI) has demonstrated strong potential in improving supply chain analytics, existing approaches often investigate prediction, explainability, optimization, and human involvement as separate components. This study proposes a Human-Centered Artificial Intelligence (HCAI) framework for adaptive inventory decision support under supply chain uncertainty by integrating AI-based demand prediction, Explainable Artificial Intelligence (XAI), adaptive inventory optimization, and human decision support within a unified framework. The Design Science Research Methodology (DSRM) was adopted to develop and evaluate the proposed framework using empirical inventory data collected from food distributors and rice warehouses in Pidie Regency and Bireuen Regency, Aceh, Indonesia. Forecasting models, including ARIMA, Exponential Smoothing, Random Forest, LSTM, and XGBoost, were evaluated using RMSE, MAE, and MAPE, with the best-performing model subsequently integrated with SHAP-based explanations and a Mixed-Integer Programming (MIP) optimization model. The evaluation results showed that XGBoost achieved the highest forecasting performance with a MAPE of 7.40%. The proposed framework reduced total inventory cost by 22.7%, improved service level from 88.5% to 96.8%, and decreased stockout rate from 11.5% to 3.2% compared with the conventional inventory policy. Furthermore, user evaluation involving 20 inventory practitioners indicated positive acceptance of the Human Decision Support Layer, with high scores for perceived usefulness, trust, and decision confidence. These findings demonstrate that integrating predictive intelligence, explainable AI, adaptive optimization, and human oversight enable transparent and adaptive inventory decision support under uncertain supply chain conditions. This study contributes to advancing Human-Centered AI applications in supply chain management by providing an integrated framework that bridges AI capability with human operational expertise
Knowledge Management Strategies for Enhancing Industrial Innovation Through Organizational Learning and Digital Col-laboration Platforms Santi Susanti; Fisla Wirda; Kraugusteeliana Kraugusteeliana; Arlis Dewi Kuraesin
Journal of Industrial Engineering and Management Vol 1, No 3 (2023)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/jaiem.v1i3.35

Abstract

Knowledge management in manufacturing depends on the visibility of practical knowledge, its retention, and its use in operational decisions. This study provides a descriptive account of an anonymized manufacturing survey containing 80 individual responses and 25 supplied instrument-result rows. The survey includes four individual knowledge-management ratings, three innovation-related ratings, one digital-collaboration rating, job satisfaction, respondent characteristics, and tenure. Item means are reported separately on the supplied 1–5 scale; no multi-item composite, association test, or causal model is constructed. Knowledge creation had the highest knowledge-management item mean (3.63), followed by storage (3.55), application (3.39), and sharing (3.29). Organizational innovation had the highest related item mean (3.68), while process innovation was 3.33. Digital collaboration averaged 3.59. The 80 respondents represented 12 departments; Maintenance and PPIC each contributed 10 respondents. The supplied instrument file reports 25 items as valid and reliable, with r calculated values from 0.430 to 0.885 against a 0.220 threshold and supplied Cronbach alpha values from 0.723 to 0.911. Four source-derived figures show item ratings, knowledge-management response distributions, department representation, and item-level validity results. The study contributes a reproducible reporting approach for operational knowledge-management surveys that separates descriptive evidence from claims about performance, innovation, or implementation effects.
Artificial Intelligence-Based Supply Chain Resilience for Strengthening Manufacturing Performance During Global Operational Disruptions Effectively Nurlaela Kumala Dewi; Afferdhy Ariffien; Santi Susanti; Arlis Dewi Kuraesin
Journal of Industrial Engineering and Management Vol 1, No 3 (2023)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/jaiem.v1i3.36

Abstract

Supply-chain resilience requires an organization to detect disruptions, coordinate a response, and restore service while preserving decision traceability. This study descriptively analyzes academic consumer-goods manufacturing records containing 12 quarterly supply-chain-performance observations from 2022 to 2024 and eight paired risk assessments. The performance series compares four conventional-period observations with eight artificial-intelligence-enhanced observations; the risk dataset compares probability, impact, and risk-priority-number values before and after an AI-enhanced mitigation label. Mean supply-chain-performance-index score increased from 62.77 to 85.06. Mean disruption count decreased from 7.50 to 3.38 per quarter, and mean recovery time decreased from 12.22 to 4.88 days. Mean fill rate increased from 84.98% to 93.02%, while mean perfect-order rate increased from 76.43% to 90.05%. Inventory days declined from 39.25 to 18.50, and supplier lead-time variance declined from 6.10 to 1.62 days. Total risk-priority number across eight categories decreased from 351 to 124. The two datasets are analyzed separately because the records do not identify a common intervention protocol, algorithm, control group, or matched operational conditions. The findings therefore describe differences associated with the supplied period and mitigation labels rather than a causal estimate of artificial-intelligence impact. The study contributes a reproducible reporting format that links quarterly resilience indicators, paired risk-priority analysis, and a practical review matrix for supply-chain governance
Co-Authors Afferdhy Ariffien Asyari Asyari Boni Sena Christina Astutiningsih Fisla Wirda Herni Setyawati Iin Wijayanti Khusnatul Zulva Kraugusteeliana Kraugusteeliana Kristanti Rahman Muhammad Asmuni Hasyim Muhammad Lukman Baihaqi Alfakihuddin Nuris Kushayati Nurlaela Kumala Dewi Radjawane, Louise Elizabeth Sev Rahmiyanti Sri Budyartati Susanti, Santi