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Mathematical Modeling and Sensitivity Analysis of the Existence of Male Calico Cats Population Based on Cross Breeding of All Coat Colour Types Suandi, Dani; Ningrum, Ira Prapti; Alifah, Amalia Nur; Izzah, Nurul; Reza, Mazi Prima; Muwahidah, Imroatul Khoiriyah
Communication in Biomathematical Sciences Vol 2, No 2 (2019)
Publisher : Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (510.829 KB) | DOI: 10.5614/cbms.2019.2.2.3

Abstract

The coat color of cats is normally governed by genes found on the X chromosome in both male chromosome XY and female chromosome XX. The meiosis failure in the process of gametogenesis leads to the birth of three-colored male cats caused by an excess of the X chromosome in the male chromosome type XY. The chromosome structure of three-color male cats, called male calico cats, appeared similar to the XXY Klinefelter?s syndrome in human. Mathematical modeling and investigation of the factors that influence the infrequency of male calico cats are our main objectives of this paper. In addition, we also discuss the possible contributions and strategies to overcome the scarcity of these cats. We construct a mathematical model based on a combination of genes in the chromosome that regulates the color of cat coat on the fertilization process. The mathematical model is given as a six-dimensional system of differential equations. Sensitivity analysis is used to investigate the important parameters in the existence of male calico cats. Our finding states that the probability of normal male cats meiosis is a crucial parameter in the maintenance of the existence of male calico cats. Furthermore, one of the strategies that we could recommend in maintaining the existence of male calico cats is minimizing the value of the successful meiosis probability of normal male cats.
Mathematical Modeling and Sensitivity Analysis of the Existence of Male Calico Cats Population Based on Cross Breeding of All Coat Colour Types Dani Suandi; Ira Prapti Ningrum; Amalia Nur Alifah; Nurul Izzah; Mazi Prima Reza; Imroatul Khoiriyah Muwahidah
Communication in Biomathematical Sciences Vol. 2 No. 2 (2019)
Publisher : Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2019.2.2.3

Abstract

The coat color of cats is normally governed by genes found on the X chromosome in both male chromosome XY and female chromosome XX. The meiosis failure in the process of gametogenesis leads to the birth of three-colored male cats caused by an excess of the X chromosome in the male chromosome type XY. The chromosome structure of three-color male cats, called male calico cats, appeared similar to the XXY Klinefelter's syndrome in human. Mathematical modeling and investigation of the factors that influence the infrequency of male calico cats are our main objectives of this paper. In addition, we also discuss the possible contributions and strategies to overcome the scarcity of these cats. We construct a mathematical model based on a combination of genes in the chromosome that regulates the color of cat coat on the fertilization process. The mathematical model is given as a six-dimensional system of differential equations. Sensitivity analysis is used to investigate the important parameters in the existence of male calico cats. Our finding states that the probability of normal male cats meiosis is a crucial parameter in the maintenance of the existence of male calico cats. Furthermore, one of the strategies that we could recommend in maintaining the existence of male calico cats is minimizing the value of the successful meiosis probability of normal male cats.
Pengaruh Marketing Mix Terhadap Keputusan Pembelian Bubur Ayam UMKM X di Surabaya Pada Era Pandemic Covid-19 Nicko Nur Rakhmaddian; Amalia Nur Alifah
JUMINTEN Vol 3 No 1 (2022): Juminten: Jurnal Manajemen Industri dan Teknologi
Publisher : UPN Veteran Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (330.772 KB) | DOI: 10.33005/juminten.v3i1.390

Abstract

Pandemi covid-19 pada saat ini telah banyak mengakibatkan banyak sektor ekonomi mengalami penurunan penjualan. Salah satu sektor yang terdampak negatif dari covid-19 adalah UMKM yang bergerak pada bidang kuliner. UMKM X adalah UMKM yang bergerak pada bidang kuliner dengan menjual produk utama berupa bubur ayam. UMKM X terdampak covid-19 sehingga mengalami penurunan penjualan dari tahun ketahun. Perlunya mengetahui variable-variable Marketing Mix 4p (Product, Price, Place, dan Promotion) apa saja yang dapat mempengaruhi penjualan produk akan dapat menjadi dasar pengambilan keputusan untuk meningkatkan penjualan. Metode yang digunakan pada penelitian ini menggunakan metode analisis regresi linier berganda, uji simultan dan uji parsial. Hasil dari penelitian didapatkan semua variable dari Marketing Mix mempengaruhi tingkat penjualan UMKM X terutama variable promosi dan variable place. Saran untuk UMKM X adalah lebih berfokus mengembangkan strategi promosi dan memperbaiki suasana tempat makan di UMKM X, seperti melakukan digitalisasi pemesanan produk dan membuat suasana tempat makan lebih nyaman, bersih dan tertata rapi.
Analisis Faktor Pengaruh Pendapatan UMKM Kota Surabaya dengan Metode Structural Equation Model Amalia Nur Alifah; Almira Ivah Edina
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (402.928 KB) | DOI: 10.36418/syntax-literate.v7i9.9389

Abstract

UMKM memiliki peran yang sangat penting, terutama bagi pertumbuhan perekonomian Kota Surabaya. Pandemi yang mulai terjadi di Indonesia khususnya Kota Surabaya membuat banyak UMKM ikut terdampak. Bahkan dampak tersebut sampai membuat banyak UMKM yang tidak dapat mempertahankan usaha miliknya serta tidak mampu bersaing dengan UMKM yang lain. Namun di sisi lain dengan adanya pandemi membuat beberapa UMKM justru malah omset penjuanlannya mengalami peningkatan secara signifikan. Pendapatan UMKM adalah salah satu aspek yang memiliki keterkaitan terhadap kebertahanan suatu UMKM. Untuk itu perlu dilakukan penelitian mengenai faktor apa sajakah yang mempengaruhi pendapatan UMKM di Kota Surabaya. Penelitian ini dilakukan dengan pendekatan penelitian kuantitatif dengan data primer. Metode yang digunakan pada penelitian ini adalah Structural Equation Modeling (SEM). Berdasarkan hasil analisis data pada penelitian ini diketahui bahwa factor kualitas, factor e-business, serta factor value chain merupakan factor-faktor yang memengaruhi tingkat pendapatan UMKM Kota Surabaya. Dengan demikian, agar setiap UMKM yang ada di Surabaya dapat bertahan, mampu bersaing, dan selalu berkembang, maka perlu untuk meningkatkan kualitas produk, memanfaatkan e-business dalam pemasaran produknya, serta memerhatikan value chain dari produknya.
Pemanfaatan Fitur Facebook sebagai Upaya dalam Meningkatkan Penjualan Produk UMKM di Ujungpangkah Kabupaten Gresik Regita Putri Permata; Amalia Nur Alifah; Helisyah Nur Fadhilah
I-Com: Indonesian Community Journal Vol 3 No 4 (2023): I-Com: Indonesian Community Journal (Desember 2023)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/icom.v3i4.3241

Abstract

Masih rendahnya kemampuan pelaku usaha dalam mengelola dan mengembangkan produk usahanya di Pangkah Wetan Gresik disebabkan terbatasnya pengetahuan tentang digitalisasi dan kemampuan dalam memasarkan produk secara online. Hal ini menjadi permasalahan yang dihadapi akibat terbatasnya literasi digital dalam menunjang kegiatan wirausaha berbasis potensi unggulan local. Kegiatan pengabdian ini bertujuan untuk meningkatkan literasi digital bagi para pelaku usaha UMKM dengan memanfaatkan fitur sosial media salah satunya Facebook Marketplace sebagai lapak jual online. Penjualan secara online dapat meningkatkan jumlah pelanggan dan meningkatkan omset. Metode pengabdian dilaksanakan melalui kegiatan pelatihan dengan pendekatan kooperatif-partisipatif. Hasil pengabdian menunjukkan foto produk olahan diunggah dan dijual melalui Facebook Marketplace. Hasil penelitian menunjukkan bahwa sebanyak 62,5% sudah menginstall dan mencoba membuka dan mempraktekkan Facebook Marketplace serta rata-rata postest meningkat dari 5.4 menjadi 6.5 dari skor rata-rata pretest, artinya pemahaman peserta meningkat mengenai Facebook Marketplace setelah diadakan sosialisasi literasi digital. Kegiatan ini diharapkan untuk meningkatkan penjualan dan jangkauan dari pemasaran produk UMKM.
Enhancing Maintenance Efficiency Through K-Means Clustering at PT Semen Indonesia Alviano, Muhammad Fadhil; Alifah, Amalia Nur; Ardhani, Calista Ghea; Raditya, Helga Fadhil; Larasati, Harashta Tatimma
Innovation in Research of Informatics (Innovatics) Vol 6, No 2 (2024): September 2024
Publisher : Department of Informatics, Siliwangi University, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/innovatics.v6i2.12520

Abstract

PT Semen Indonesia, an industrial company based in Gresik, East Java, is committed to enhancing operational efficiency and managing maintenance costs effectively. By analyzing patterns in maintenance frequency, total costs, and maintenance duration across their various plants, the company can identify work units that require more intensive attention or that can be optimized for greater efficiency. To achieve this, PT Semen Indonesia employs K-Means clustering analysis to gain deeper insights into the maintenance data, identifying patterns that can help improve operational efficiency and develop more targeted maintenance strategies based on the identified clusters. The clustering of planner groups is carried out using variables such as the number of maintenance activities, total costs, and duration of maintenance tasks. As a result of the K-Means clustering, the planner groups have been divided into two clusters: Cluster 1, which consists of planner groups that perform more efficiently, and Cluster 2, which includes those with less efficient performance. Based on these clustering results, PT Semen Indonesia should conduct further evaluation or review of the planner groups in Cluster 2.
Unlocking Pharma Market Segmentation for Strategic Growth Through Advanced Data Intelligence Purwaningrum, Alfi; Alifah, Amalia Nur; Dermawan, Dwi Bagus; Andini, Galuh
Engineering, MAthematics and Computer Science Journal (EMACS) Vol. 7 No. 1 (2025): EMACS
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/emacsjournal.v7i1.12199

Abstract

Business competition compels companies to understand customer characteristics in order to maintain and enhance their competitiveness, especially in the pharmaceutical industry, which involves various customer segments such as hospitals, pharmacies, patients, and end consumers with diverse needs. Customer segmentation becomes crucial in developing effective strategies, with K-Means algorithm being one of the commonly used methods due to its simplicity and efficiency in clustering large datasets. This study combines the K-Means Clustering algorithm with the elbow method to determine the optimal number of clusters in segmenting the customer profiles of a pharmaceutical company. The analysis results reveal two main clusters: the first cluster is dominated by hospitals with higher medication purchase volumes and longer delivery distances, ranging from 8 to 131 km, while the second cluster is dominated by pharmacies with smaller purchase volumes and shorter delivery distances. These findings enable the pharmaceutical company to better understand customer characteristics and design more effective strategies to compete in the market. It is recommended that the company adjusts its marketing strategies and products based on the needs of each cluster, enhances customer relationships through loyalty programs, and optimizes distribution routes to improve operational efficiency.
Ordinal Logistic Regression Model of Micro, Small, and Medium-Sized Enterprises Income: A Case Study of Micro, Small and Medium-Sized Enterprises in Surabaya Alifah, Amalia Nur; Edina, Almira Ivah; Almuhayar, Mawanda
Indonesian Journal of Statistics and Applications Vol 8 No 2 (2024)
Publisher : Statistics and Data Science Program Study, IPB University, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v8i2p143-154

Abstract

Micro, Small, and Medium Enterprises (MSMEs) is a business sector that is able to make a significant contribution to economic recovery in Indonesia. In Surabaya, there are many MSMEs with various fields, both food and non-food sectors which include services, trade, etc. MSMEs actually have great potential to boost the economic growth of the people of Surabaya. Especially during the COVID-19 pandemic, MSMEs owners must be able to strategize how their income can be stable or even bigger. Therefore, it is very important to know what factors can boost MSMEs income in Surabaya. In this study, it will be examined what factors can affect the income of MSMEs in Surabaya. The method used in this study is Ordinal Logistic Regression which aims to determine which independent variables or factors affect the dependent variable which in this case is MSMEs income. Based on the results of the analysis, it can be seen that the variables that affect MSMEs income are MSMEs Location, MSME Activities, and MSME Outreach. Keywords: ordinal logistic regression, MSMEs, income.
Integrating Self-Organizing Maps and K-Means in a Multidimensional Approach to Enhance Private University Market Segmentation Alifah, Amalia Nur; Rochmah, Wachda Yuniar; Mesak, Evellyn Verity
ZERO: Jurnal Sains, Matematika dan Terapan Vol 9, No 1 (2025): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v9i1.24430

Abstract

Educational institutions face challenges in attracting prospective students while maintaining academic quality and resource efficiency. This study applies a hybrid approach that integrates Self-Organizing Maps (SOM) and K-Means to cluster schools based on four attributes, namely the number of accounts, average UTBK scores, geographical distance, and parental income. The analysis's findings produce three distinct clusters. With a high degree of attribute variation, Cluster 2 (279 schools) is a dominant group that suggests the possibility of extensive marketing campaigns. Clusters 1 (45 schools) and 3 (81 schools), on the other hand, are more uniform and call for a more specialized and focused strategy. These results imply that a data-driven approach can help institutions create interventions that are specific to each segment's profile and increase the efficacy of educational marketing strategies. In order to improve segmentation accuracy in the future, this study creates opportunities for investigating new features and dynamic clustering techniques.
Association Rule Mining of Consumer Behavior at MOY Supermarket Using Apriori Algorithm Alifah, Amalia Nur
ULTIMATICS Vol 17 No 1 (2025): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v17i1.3745

Abstract

MOY Frozen Food is a retail business located in Kediri Regency, specializing in the sale of frozen food, beverages, and basic necessities. In recent years, the retail industry has faced numerous challenges, including shifts in consumer behavior, technological advancements, and increasing competition. This study addresses the issue of identifying which products are frequently purchased together and determining appropriate recommendations for consumers. To achieve this goal, association rules are employed to discover correlations and co-occurrences among data sets, which facilitate the identification of product relationships within a single transaction. Using the Apriori algorithm with a minimum support threshold of 0.01 and a confidence level of 0.5, implemented in Python, this research successfully generates association rules. The insights derived from these association rules can be leveraged to develop various sales strategies, ultimately enhancing product sales at MOY Frozen Food.