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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknologi Terapan Warta Pengabdian Andalas: Jurnal Ilmiah Pengembangan Dan Penerapan Ipteks Indonesian Journal of Industrial Engineering & Management
Attaqwa, Yusita
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Social Sciences Other

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Artificial intelligence and internet of things in manufacturing decision processes Wijaya, Santo; Hermanto Rudy, Lim; Debora, Fransisca; Ardila Rahma, Rana; Ramadhan, Arief; Attaqwa, Yusita
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i2.pp2185-2200

Abstract

This paper explores the influence of the internet of things (IoT) and artificial intelligence (AI) on the decision-making processes of modern manufacturing systems. With the proliferation of IoT devices and the development of AI technologies, manufacturing companies increasingly leverage these technologies to improve their decision-making abilities. This study aims to investigate the potential benefits, difficulties, and ramifications of integrating IoT and AI in manufacturing systems. The review employs the preferred reporting items for systematic reviews and meta-analyses (PRISMA) method with a systematic mapping process with four research questions. A total of 1282 articles were collected between 2017 and 2023, reviewed in accordance with the inclusion and exclusion criteria, and 66 articles were chosen. The research on IoT and AI technologies influentially affects other research in the production control layer manufacturing area based on the top-ten cited articles. In contrast, the research in this area focused on the operations management layer, specifically manufacturing analytics processes. This paper’s findings contribute to a greater understanding of the impact of IoT and AI on decision-making in modern multi-domain manufacturing systems and provide direction for future research in this field.
IMPLEMENTASI METODE QUALITY CONTROL CYCLE (QCC) UNTUK PENINGKATAN KAPASITAS PRODUKSI BODY CENTER PILLAR DI PERUSAHAAN OTOMOTIF Attaqwa, Yusita; Sari, Nita Winda; Kusmayadi, Didi
Jurnal Teknologi Terapan Vol 11, No 2 (2025): Jurnal Teknologi Terapan
Publisher : P3M Politeknik Negeri Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31884/jtt.v11i2.835

Abstract

This research was conducted at manufacturer of Toyota and Daihatsu brand cars. One of the products, the Body Center Pillar part, is the lowest productivity, where the target PPH is 50 pcs / hour, the actual PPH is 40 pcs / hour or still minus 10 pcs every hour. Necessary non valuable work that causes a high cycle time of 90 seconds, thus affecting production capacity. This study aims to determine the factors that cause Non-Valuable Work which results in a high Cycle Time of 90 seconds, which has an impact on low production capacity in line 6D-01-1 using the Quality Control Cycle (QCC) method. The subject of the study is the work process carried out by production operators where the productivity results are still low while the object of research is the measurement of process time or Cycle Time Part Body Center pillar consisting of 4M and 1E factors, namely: Machines, Materials, Methods, People, and Environment. After making some improvements of the engine factors and methods, use the Quality Control Cycle (QCC) method. Cycle Time decreased to 72 seconds so that PPH increased from 40 pcs to 50 pcs and production productivity in line 6D-01-1 increased.
A Systematic Review of the Simplex Method in Profit-Oriented Optimization for Manufacturing Industries Pasaribu, Enita; Hernadewita, Hernadewita; Debora, Fransisca; Attaqwa, Yusita
IJIEM - Indonesian Journal of Industrial Engineering and Management Vol 6, No 3: October 2025
Publisher : Program Pascasarjana Magister Teknik Industri Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijiem.v6i3.35105

Abstract

Companies involved in production activities consistently strive to achieve their strategic objectives, with profit maximization being one of the primary goals for maintaining competitiveness and ensuring long-term business sustainability. This goal can be pursued through optimal production planning, one of which involves the application of the Simplex Method (SM). The Simplex Method is a mathematical algorithm designed to solve Linear Programming (LP) problems, which focus on optimizing a linear objective function while accounting for various resource-related constraints. This paper presents a systematic literature review on the implementation of the Simplex Method for profit optimization in the manufacturing sector. A total of 30 relevant research articles published between 2019 and 2024 were analyzed, sourced from reputable academic databases such as Google Scholar and ScienceDirect. The findings demonstrate that the Simplex Method offers substantial benefits, including improved resource allocation, cost reduction, enhanced decision-making capabilities, increased productivity, and support for data-driven operational efficiency. These advantages underscore the method’s effectiveness as a quantitative decision-support tool in strategic industrial planning. The review also highlights the broad applicability of the Simplex Method across various countries and industrial sectors, particularly in food, automotive, chemical, and textile manufacturing. As the manufacturing landscape transitions into the era of Industry 4.0, it is strongly recommended that future research explores the integration of the Simplex Method with emerging technologies such as Big Data analytics, Artificial Intelligence (AI), Cyber-Physical Systems (CPS), and Hybrid Optimization Models to further enhance industrial competitiveness, adaptability, and sustainability. 
Developing Millennial Generation Skills Through a Technology-Based Agribusiness Training Program in Mekarsaluyu Village, Cimenyan District, West Java Regency Muhammad, Achmad; Sadikin, Supriyadi; Sudjana, Dede; Syukri, Khariful; Attaqwa, Yusita
Warta Pengabdian Andalas Vol 33 No 1 (2026)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jwa.33.1.128-139.2026

Abstract

This community service activity aims to increase the understanding, knowledge, and interest of the younger generation in Mekarsaluyu Village towards technology-based agribusiness. The method of implementing activities uses a socialization method that is carried out in a structured manner through the delivery of materials and interactive discussions. The target of the activity is students and youth of Mekarsaluyu Village who have not been actively involved in agricultural activities. The results of the activity showed an increase in participants' understanding and interest in the technology-based agriculture and agribusiness sectors. Through this activity, the young generation is expected to be able to play an active role in the sustainable development of village agricultural potential and encourage innovative and competitive agribusiness-based local economic growth.
Co-Authors Achmad Muhammad, Achmad Anugrafi, Reza Ardila Rahma, Rana Arief Ramadhan Fransisca Debora Hermanto Rudy, Lim Hernadewita Ismail, Fu’ad Kusmayadi, Didi Kusumo, Jati Pasaribu, Enita Ramadhanti, Azhara Sadikin, Supriyadi Santo Wijaya Sari, Nita Winda Sudjana, Dede Syukri, Khariful