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All Journal Desimal: Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Jurnal Matematika UNAND
Setiawan, Tabah Heri
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Enhancing Orchid Inventory Management with K-Means Clustering: A Case Study in Sales Optimization Ramadhani, Dwi; Setiawan, Tabah Heri; Basir, Choirul; Sari, Dewi Purnama
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 9 No. 1 (2024): Mathline: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v9i1.529

Abstract

In the ornamental industry, particularly in orchid sales, manual inventory management has presented significant challenges. These challenges include excessive stock accumulation, financial pressure due to overstocks, and limited land resources to store overstocks. Utilizing information technology, data mining, specifically the K-Means Clustering algorithm, emerges as a solution. This research aims to optimize orchid inventory management by grouping products into three clusters: "highly sellable," "sellable," and "less sellable." Historical sales data was used as the main dataset, considering parameters such as sales volume, demand patterns, and seasonality. The K-Means Clustering algorithm categorized the orchid products, with 97 products in the "highly sellable" cluster, 68 products in the "sellable" cluster, and 22 products in the "less sellable" cluster. This analysis offers insights. Orchids that are "highly marketable" require higher stock levels to meet demand. "Sellable" varieties require standard stock levels, while "less sellable" types should maintain lower stock levels to avoid overstocking. In conclusion, using k-means clustering for orchid inventory management can optimize sales strategies. Orchids in high demand receive adequate stock, ensuring customer satisfaction. Effective stock allocation improves financial stability by overcoming the problem of overstock in the ornamental industry.
CLUSTERING ANALYSIS OF PROVINCIAL IN INDONESIA BASED ON THE 2023 HUMAN DEVELOPMENT INDEX INDICATORS USING THE K-MEDOIDS ALGORITHM Sabrina, Syafa Marwa; Setiawan, Tabah Heri
Jurnal Matematika UNAND Vol 14, No 1 (2025)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.14.1.93-102.2025

Abstract

Indonesia memiliki visi Indonesia Emas pada tahun 2045, namun pencapaian Indeks Pembangunan Manusia (IPM) dalam 20 tahun terakhir menunjukkan tantangan untuk mewujudkan visi tersebut. Penelitian ini menggunakan algoritma k-medoids untuk melakukan clustering provinsi di Indonesia berdasarkan indikator IPM tahun 2023. K-medoids dipilih karena keunggulannya dalam menangani outlier. Berdasarkan hasil perbandingan dengan metode k-means dan fuzzy c-means, metode k-medoids juga terbukti merupakan metode terbaik karena cluster yang terbentuk pada k-medoids terpisah dengan baik dan memiliki struktur yang kuat. Hasil penelitian menghasilkan tiga cluster: C1 memiliki anggota provinsi dengan IPM sangat tinggi, C2 memiliki anggota provinsi dengan IPM tinggi, sementara C3 memiliki anggota provinsi dengan IPM sedang. Analisis ini diharapkan menjadi bahan evaluasi dan referensi bagi pengembangan metode clustering.
CLUSTERING ANALYSIS OF PROVINCIAL IN INDONESIA BASED ON THE 2023 HUMAN DEVELOPMENT INDEX INDICATORS USING THE K-MEDOIDS ALGORITHM Sabrina, Syafa Marwa; Setiawan, Tabah Heri
Jurnal Matematika UNAND Vol. 14 No. 1 (2025)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.14.1.93-102.2025

Abstract

Indonesia memiliki visi Indonesia Emas pada tahun 2045, namun pencapaian Indeks Pembangunan Manusia (IPM) dalam 20 tahun terakhir menunjukkan tantangan untuk mewujudkan visi tersebut. Penelitian ini menggunakan algoritma k-medoids untuk melakukan clustering provinsi di Indonesia berdasarkan indikator IPM tahun 2023. K-medoids dipilih karena keunggulannya dalam menangani outlier. Berdasarkan hasil perbandingan dengan metode k-means dan fuzzy c-means, metode k-medoids juga terbukti merupakan metode terbaik karena cluster yang terbentuk pada k-medoids terpisah dengan baik dan memiliki struktur yang kuat. Hasil penelitian menghasilkan tiga cluster: C1 memiliki anggota provinsi dengan IPM sangat tinggi, C2 memiliki anggota provinsi dengan IPM tinggi, sementara C3 memiliki anggota provinsi dengan IPM sedang. Analisis ini diharapkan menjadi bahan evaluasi dan referensi bagi pengembangan metode clustering.
Graph coloring for determining courier frequency Setiawan, Tabah Heri; Beltsazar, Ferdinand; Aden, Aden; Gunawan, Gani; Zarista, Ramzil Huda
Desimal: Jurnal Matematika Vol. 6 No. 3 (2023): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v6i3.18358

Abstract

The exponential growth of online transactions in Indonesia has intensified the competition among courier service providers to ensure efficient goods delivery, prompting the need for exceptional performance. However, this surge has also brought forth various challenges, including imbalanced courier allocation, intricate delivery routes, and sprawling coverage areas, resulting in delays and extended working hours for couriers. This research, conducted in Jakarta, centers on a logistics and courier service company grappling with a critical courier shortage, leading to overburdened personnel and extended work hours. To address this issue, we employed graph coloring, rooted in graph theory, as a novel approach to determine the ideal number of couriers based on the route and delivery area. Through graph coloring, delivery routes, and areas can be optimized so that each courier has the same average route length and area and does not exceed the threshold limit set by the company. The number of delivery routes and areas generated from graph coloring shows the number of couriers required for the company. The results of this research obtained 27 routes that show the need for the ideal courier frequency so that the delivery of goods can be on time without extending the courier's working hours.
TSUKAMOTO FUZZY IN OPTIMIZING THE CREDITWORTHINESS ASSESSMENT PROCESS AT SAVINGS AND LOAN COOPERATIVES Setiawan, Tabah Heri; Prihatini, Laras
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0775-0786

Abstract

Savings and Loan Cooperatives are ones of the non-bank institutions whose business activity is the provision of loan. In its business activities, problems often arise, namely non-performing loans which causes no turnover of funds which leads to losses. One of the causes of non-performing loans is the lack of objective creditworthiness assessment. The purpose of this study is to optimize the process of assessing the feasibility of loan applications at Savings and loan credit with assessment criteria: loan value, total income, loan term and collateral value. The tsukamoto fuzzy method was used in this study. Tsukamoto fuzzy method consists of four steps.: fuzzification, Forming fuzzy rules, application of implication functions using the MIN function and defuzzification using the weighted average calculation method. In this research, it was found that Tsukamoto's fuzzy method can be applied to the creditworthiness assessment process at the Saving and Credit Cooperatives. This is because the accuracy rate of the decision results from the tsukamoto method is 93.75%. A total of 60 data out of 64 data are in accordance with the eligibility decision at one of Saving and loan Cooperatives in West Java, Indonesia. Tsukamoto fuzzy method can optimize the credit assessment process in Savings and loan Cooperatives because the eligibility assessment process becomes more efficient and objective.
Co-Authors Aden, Aden Basir, Choirul Beltsazar, Ferdinand Dewi Purnama Sari DWI RAMADHANI Gani Gunawan Prihatini, Laras Sabrina, Syafa Marwa Zarista, Ramzil Huda