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All Journal International Journal of Advances in Applied Sciences Jurnal Ilmiah Teknik Industri International Journal of Artificial Intelligence Research Jurnal Sistem dan Manajemen Industri Jurnal Ekonomi & Keuangan Islam Journal of Dedicators Community Jurnal Kridatama Sains dan Teknologi Buletin Ilmiah Sarjana Teknik Elektro Journal of Applied Data Sciences Advance Sustainable Science, Engineering and Technology (ASSET) Spektrum Industri
Qurtubi Qurtubi, Qurtubi
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Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering 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 Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Transportation

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Journal : Advance Sustainable Science, Engineering and Technology (ASSET)

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Supplier Selection Modeling and Analysis in the Metal Casting Industry Using Analytical Hierarchy Process Firdantara, Zahra Nasywari; Qurtubi, Qurtubi; Setiawan, Danang
Advance Sustainable Science, Engineering and Technology Vol 6, No 2 (2024): February - April
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i2.18323

Abstract

This study presents a supplier selection problem of a raw material using an analytical hierarchy process. In the existing process, the delivery of raw materials experienced delays and impacted the production process. Therefore, this paper aims to determine the criteria for supplier selection and provide recommendations for the best vendor to be selected from the last request for quotation document. Analytical Hierarchy Process (AHP), as a multi-criteria approach, was utilized in this research, starting from determining criteria, the weight of criteria, and the final score for each supplier. Through discussions with the company’s expert, procurement department, and users, as well as a review of the previous studies, this research defined three criteria, each consisting of three sub-criteria. The AHP approach was utilized to evaluate and determine the weights for the three criteria, yielding the following results: quality (62%), price (28%), and delivery (10%). The identified criteria, sub-criteria, and respective weights are subsequently utilized in a supplier selection scenario. Three suppliers of mild steel raw materials were evaluated using the weights of the criteria and sub-criteria obtained. Supplier 1 was selected because of having the higher alternative value of 0.602. The use of AHP in supplier selection is often impractical and contains subjectivity. Therefore, further research can be performed by integrating AHP with other methods, such as weighted scoring, to facilitate further the vendor selection process and integration with other methods, such as fuzzy logic, to reduce subjectivity.
Utilizing Data Mining Techniques to Analysis Changes in Purchase Behavior of Batik’s Customers Setiawan, Danang; Alfiyani, Lisa; Sulistio, Joko; Qurtubi, Qurtubi
Advance Sustainable Science, Engineering and Technology Vol 6, No 2 (2024): February - April
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v6i2.18506

Abstract

Sales transaction data contains rich information potentially used to support company competitiveness. However, interpreting and utilizing transaction data in developing marketing strategies remains a challenge, even for big companies. Therefore, this research aims to develop marketing strategies using data mining techniques. A medium-sized company focusing on producing and selling traditional motif clothes (batik) will be used as a case study. The negative sales trend is the biggest issue currently faced by the company. Hypothetically, this problem is caused by imported products sold at lower prices or changing consumer behavior after pandemic covid. Currently, the company only implements simple analysis of its transaction data. The analysis of transaction data, conducted through five data mining stages, yielded a shift from purchasing small quantities to larger quantities, increased purchases during the final week of each month, and increased purchases on religious occasions. Furthermore, the analysis revealed that 31.29% of all transactions were attributed to loyal consumers, and 192 customers exhibited in Cluster 1 (high transaction quantities and high transaction values). Further investigation also revealed that customers categorized as loyal customers and Cluster 1 have different behaviors that can be used to develop further customer relationship programs. Future research can be conducted by employing data mining techniques to study the organization's assortment of products. Management discussions reveal that changes in consumer buying behavior extend to the selection of items and batik themes.
Co-Authors 'Azzam, Abdullah Alfiyani, Lisa Ali Parkhan Bachtiar, Machdum Danang Setiawan Elquthb, Jundi Nourfateha Fadlika, Raka Shidqi Fahrezha, Muhammad Faisol, Nasruddin Fatmariyanti, Yanti Febrianti, Melinska Ayu Firdantara, Zahra Nasywari Haswika, Haswika Iftitah, Nur Istiqomah, Khairunnisa Nurul Joko Sulistio, Joko Khairullah, Rafi Maghfiroh, Meilinda F.N. Mahardiningtyas, Syafira Maradjabessy, Prita Nurkhalisa Mufid, Nisrina Faiza Prakoso, Nur Abdillah Bagus Rachmadewi, Ira Promasanti Raihanto, Muhammad Satya Solekha, Putri Jasmine Sugarindra, Muchamad Supriyadi Supriyadi Trisnaningtias, Dicka Meilana Vembri Noor Helia, Vembri Noor Wahyudhi Sutrisno, Wahyudhi Widodo, Imam Djati Yanti, Roaida Yudhanata, Muhammad Fadhila Zaputra, Afriza Syawal