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All Journal Syntax Literate: Jurnal Ilmiah Indonesia INTECOMS: Journal of Information Technology and Computer Science
Soewardi, Hartomo
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Humanities Computer Science & IT Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Analisis Risiko Rantai Pasok Cabai Dengan Metode Failure Mode and Effect Analysis (FMEA) Pada PT. XYZ Putri, Lutfiah; Soewardi, Hartomo; Apriani, Ratna Agil; Azizah, Nabila Aulia; Basuki, Demas Emirbuwono
INTECOMS: Journal of Information Technology and Computer Science Vol 7 No 4 (2024): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v7i4.10717

Abstract

PT.XYZ adalah salah satu perusahaan di kota Makassar yang bergerak dibidang pengiriman cabai ke beberapa daerah seperti Timika, Jayapura, Tarakan, Palu, dan Mamuju yang bekerja sama dengan suplayer, dan beberapa daerah pemasok cabai seperti Jeneponto, Malino, Barombong dan Enrekang. Cabai merupakan komoditas penting dalam sector pertanian dan ketergantungan masyarakat terhadap cabai membuat stabilitas pasokan menjadi kunci dalam memastikan kelangsungan oporasional. Hilangnya kualitas pada cabai di sebabkan oleh beberapa faktor seperti cuaca, cabai terlalu masak atau berair, cabai di simpan terlalu lama, dan penanganan pengiriman. Oleh karena itu, tujuan penelitian ini untuk menganalisis faktor resiko pengiriman cabai untuk menghindari terjadinya kerusakan pada cabai, metode yang digunakan adalah metode Failure Mode and Effect Analysis (FMEA) yaitu suatu metode yang terstruktur dan sistematis untuk mengidentifikasi dan mengetahui tingkat risiko penyebab kualitas suatu produk. Hasil penelitian dalam menganalisis risiko rantai pasok cabai ini terdapat bahwa pada petani RPN tertinggi penyebab kabusukan pada cabai yaitu memanen buah yang terlalu masak dengan nilai RPN 72, dan pada Pengumpul RPN tertinggi penyebab kabusukan pada cabai yaitu cabai terkena air dengan nilai RPN 294, sedangkan RPN tertinggi penyebab kabusukan pada penyortiran yaitu memisahkan cabai yang busuk dan cabai yang masih segar dengan nilai RPN 112.
Development of Ergo-Bundling System for Food Retailer based on Data Mining Fattah, Bulan Rahma; Soewardi, Hartomo
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v9i9.16103

Abstract

In retail, a major challenge is quickly selling perishable food items like cakes or pastries within a limited time. If unsold, these products lead to losses, even with discount promotions. Retailers must forecast stock accurately and develop more effective strategies to meet consumer demand within the required timeframe. One suggested strategy is bundling, where high-demand products are combined with less popular ones. However, when done manually, this approach often fails to align with consumer preferences. This study aims to develop an automated bundling system using data mining techniques. Market Basket Analysis is used to understand consumer purchasing patterns, while Association Rules with the Apriori Algorithm help identify relationships between different products. These methods reveal which items are frequently bought together, making bundling strategies more effective. The system will be designed with usability and ergonomic principles, ensuring it is user-friendly. The implications of this system include improved stock management, more accurate bundling, and better alignment with customer preferences, ultimately increasing satisfaction. Additionally, automation reduces errors and inconsistencies that occur with manual bundling. The expected outcome is a more efficient, effective, and comfortable system for food retailers, leading to higher sales, reduced losses, and greater overall customer satisfaction.
Co-Authors Apriani, Ratna Agil Azizah, Nabila Aulia Basuki, Demas Emirbuwono Fattah, Bulan Rahma Putri, Lutfiah