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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Syntax Literate: Jurnal Ilmiah Indonesia Communication in Biomathematical Sciences Jurnal ULTIMATICS Zero : Jurnal Sains, Matematika, dan Terapan Range : Jurnal Pendidikan Matematika Innovation in Research of Informatics (INNOVATICS) SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) Engineering, Mathematics and Computer Science Journal (EMACS) Juminten : Jurnal Manajemen Industri dan Teknologi Indonesian Community Journal Aptekmas : Jurnal Pengabdian Kepada Masyarakat eProceedings of Engineering Indonesian Journal of Statistics and Its Applications
Alifah, Amalia Nur
Telkom University
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Optimizing K-Means Clustering through Distance Metric Simulation for Strategic Enrollment Segmentation in Private Universities Permata, Regita Putri; Alifah, Amalia Nur; Sanjaya, I Made Wisnu Adi
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.33089

Abstract

K-Means clustering is a widely used unsupervised learning technique for identifying patterns and grouping data based on feature similarities. However, the effectiveness of K-Means significantly depends on the choice of distance metric. This study conducts a comprehensive simulation to evaluate and compare the performance of four distance metrics—Euclidean, Cityblock (Manhattan), Canberra, and Mahalanobis—in the context of strategic market segmentation for private universities. The dataset includes simulated and institutional data incorporating variables such as account creation, registration, graduation, student performance (social, science, and scholastic scores), income, and geographic distance. The results indicate that Euclidean and Cityblock distances yield efficient and interpretable clusters with low computational costs, whereas Mahalanobis distance, despite its capacity to model covariance, introduces computational overhead without proportional improvement in segmentation quality. Interestingly, Canberra distance produces compact clusters but offers no significant gain in separability. From the resulting segmentation, two clusters emerge as high-potential targets for marketing strategies: Cluster 0 (high-income and distant students) and Cluster 1 (diverse academic and socioeconomic profiles). The findings highlight the importance of aligning distance metric selection with specific clustering objectives and offer practical insights for data-driven strategic enrollment planning in private higher education institutions.
Drug Distribution Cost Optimization with Vogel, Russel, and Northwest Corner Approaches Ningtyas , Miranthy Pramita; Alifah, Amalia Nur; Fadhilah, Helisyah Nur
RANGE: Jurnal Pendidikan Matematika Vol. 7 No. 1 (2025): Range Juli 2025
Publisher : Pendidikan Matematika UNIMOR

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jpm.v7i1.9501

Abstract

The increase in annual turnover in a drug distribution company reflects positive growth but is often accompanied by a significant increase in operating costs that can reduce profit margins if not managed efficiently. This study aims to optimize distribution costs using a transportation method approach by comparing three initial solution methods, namely Vogel's Approximation Method (VAM), Russell Approximation Method (RAM), and Northwest Corner Method (NWC). The study was conducted at a drug distribution company with three central warehouses serving four distribution branches, based on distribution data for December 2024, which was arranged in the form of a transportation table. From the calculation results, the VAM method produced the lowest total distribution cost of IDR23,426,407. Evaluation of this solution was carried out using the Steppingstone method and the Modified Distribution Method (MODI) to determine whether the solution was optimal. The evaluation results show that all opportunity cost values ​​are positive, which means that no additional iterations or re-allocations are required so that the solution from the VAM method can be stated as an optimal solution. The novelty of this study lies in the integration of three initial solution methods with two optimal solution methods in one drug distribution case study, which has not been widely discussed in an integrated manner in previous studies. These findings provide strategic contributions to more precise and efficient logistics decision-making and support the sustainable operational growth of pharmaceutical distribution companies.
Rainfall Forecasting using Spatio-Temporal and Neural Network Study Case: Meteorological Data of Madura Island Savira, Ryanta Meylinda; Permata, Regita Putri; Alifah, Amalia Nur; Setiawan, Yohanes; Putra, Adzanil Rachmadhi
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.35091

Abstract

Rainfall forecasting is crucial in meteorological studies due to its significant impact on sectors such as agriculture, which is the main livelihood on Madura Island. This study aims to forecast rainfall on Madura Island using a hybrid approach that combines the Generalized Space-Time Autoregressive-X (GSTARX) model and Neural Network (NN). The data used consist of daily rainfall records from Bangkalan, Sampang, Pamekasan, and Sumenep, covering the period from January 2013 to December 2023. Data from January 2013 to September 2023 were used for training, while data from October to December 2023 were used for testing. The GSTARX model was employed to capture spatio-temporal patterns, while the NN was applied to learn the non-linear relationships in the residuals. The results show that the GSTARX model effectively captures rainfall patterns, though some differences remain compared to the actual data, with RMSE values of Bangkalan (1.514), Sampang (0.256), Pamekasan (0.477), and Sumenep (0.127). Meanwhile, the hybrid GSTARX-FFNN model achieved improved forecasting performance in Sampang (0.392), Pamekasan (0.679), and Sumenep (0.412), although Bangkalan recorded a higher RMSE (1.359). Overall, the GSTARX model proved more effective in forecasting rainfall on Madura Island, delivering smaller and more consistent prediction errors.
PENGEMBANGAN WEBSITE SURABAYA DESIGN CENTER (STUDI KASUS TAMAN WISATA KAYOON SURABAYA) Alifah, Amalia Nur; Rizky Fenaldo Maulana; Dominggo Bayu Baskara; Fajrul Falah Arrafi; Qothrunnadaa Nahdah Dzakiyyah; Ananda Taqhsya Dwiyana
Aptekmas Jurnal Pengabdian pada Masyarakat Vol 6 No 4 (2023): APTEKMAS Volume 6 Nomor 4 2023
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36257/apts.v6i4.8319

Abstract

In the ever-evolving digital era, the importance of digital marketing as a key tool in promoting businesses and services is increasingly apparent. The Kayoon area, which was originally the center of the decorative stone and jewelry trade in Surabaya, has experienced a decline in visits along with the impact of the COVID-19 pandemic. As a solution, the Surabaya City Government in collaboration with ADIDES and PK-KPBI ITS, along with ITTelkom Surabaya, initiated a revitalization by turning Kayoon into the Surabaya Design Centre (SDC). SDC aims to be an Urban Education area and a center for branding original handicraft products, but faces challenges in visibility and interaction in the digital era. To overcome this, a community service program is designed to assist SDC in improving the promotion of its business, products, and services digitally through website creation, social media, and Google Business registration. With the implementation of this digital marketing strategy, it is hoped that SDC can strengthen its reputation as a center of innovation and creativity, expand audience reach, and create new business opportunities within the design community. Thus, this community service program activity is expected to help the Kayoon community to get more benefits and new opportunities in this digital era.
Pengaruh Motivasi dan Kepuasan Kerja Terhadap Prestasi Kerja dengan Metode Regresi Study Case : PT.X Nicko Nur Rakhmaddian; Amalia Nur Alifah
JUMINTEN Vol. 3 No. 1 (2022): Juminten: Jurnal Manajemen Industri dan Teknologi
Publisher : Teknik Industri - UPN "Veteran" Jatim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/juminten.v3i1.390

Abstract

Pandemi covid-19 pada saat ini telah banyak mengakibatkan banyak sektor ekonomi mengalami penurunan penjualan. Sektor yang terdampak negatif dari Covid-19 salah satunya merupakan UMKM yang bergerak pada bidang kuliner. UMKM X adalahUMKM yang bergerak pada bidang kuliner dengan menjual produk utama berupa bubur ayam. UMKM X terdampak covid-19 sehingga mengalami penurunan penjualan dari tahun ketahun. Tujuan dari penelitian ini ialah mengetahui variable-variable Marketing Mix 4p (Price, Promotion, Product, dan Place) apa saja yang dapat mempengaruhi penjualan produk sehingga bisa menjadi dasar pengambilan keputusan untuk meningkatkan penjualan UMKM X. Metode yang digunakan terdiri dari analisis regresi linier berganda, uji simultan dan uji parsial. Output atau 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.
Klasifikasi Tingkat Kedalaman Kemiskinan di Indonesia Menggunakan Support Vector Machine dan Regresi Logistik Mufaidah, Astikhatul; Ni'mah, Rifdatun; Nur Alifah, Amalia
eProceedings of Engineering Vol. 12 No. 5 (2025): Oktober 2025
Publisher : eProceedings of Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak — Kemiskinan merupakan masalah kompleks yang masih menjadi tantangan utama di Indonesia, dengan dampak yang luas terhadap kesejahteraan masyarakat. Penelitian ini bertujuan untuk mengklasifikasikan tingkat kedalaman kemiskinan menggunakan dua model machine learning yakni Support Vector Machine (SVM) dan Regresi Logistik, serta mengidentifikasi faktor-faktor yang secara signifikan memengaruhinya. Dataset yang digunakan mencakup variabel sosial-ekonomi dari berbagai wilayah, seperti Bantuan Sosial, Rata-Rata Lama Sekolah, dan Jumlah Penduduk. Hasil analisis menunjukkan bahwa model SVM dan Regresi Logistik sama sama menghasilkan performa klasifikasi yang tinggi, dengan akurasi 99%. Regresi Logistik pada penelitian ini digunakan untuk mengetahui faktor-faktor yang berpengaruh secara signifikan terhadap tingkat kedalaman kemiskinan melalui pen- dekatan uji signifikansi statistik. Regresi Logistik menunjukkan bahwa tiga variabel yang paling signifikan adalah Bantuan Sosial, Pendapatan Asli Daerah, dan Rata-rata Lama Sekolah, Temuan ini diharapkan dapat menjadi dasar bagi pengembangan kebijakan yang lebih tepat sasaran dalam upaya pengentasan kemiskinan di Indonesia Kata kunci— Analisis Data, Indeks Kedalaman Kemiskinan, Kemiskinan, Regresi Logistik, Support Vector Machine
Developing and Managing MSME Websites to Improve Kampoeng Ilmu's Operational Performance Alifah, Amalia Nur; Rachmaniar, Desita Nur; Mustaqim, Tanzilal; Rafif, Sulthan
SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) Vol. 6 No. 2 (2025)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/spekta.v6i2.13871

Abstract

Background: MSMEs in Kampoeng Ilmu Surabaya continue to face obstacles in product marketing and digital adoption, which limit their operational growth. This program aims to address these issues by developing an integrated website and improving digital literacy among MSME partners to strengthen their online visibility and business sustainability. Contribution: The program contributes to the community by providing a digital platform (UMKMCerdas website) that enables MSMEs to independently manage product data, storefront profiles, and promotional information. It also enhances partners’ capacity to operate digital tools, supporting long-term empowerment and competitiveness. Method: The implementation consisted of five structured stages: needs analysis through interviews, website design with UI/UX and database planning, website development using PHP (Laravel), MySQL, Tailwind, and Filament, training and mentoring for MSME partners, and evaluation through continuous monitoring. A participatory approach was used to ensure active involvement and skill transfer to 82 MSME actors. Results: The integrated website successfully provides features such as bookstore profiles, product catalogs, Google Maps integration, WhatsApp contacts, and an admin dashboard. Post-training responses showed significant enhancement in partners’ confidence and ability to use digital tools for promoting their businesses and managing information. Conclusion: The program effectively strengthens the digital capabilities of Kampoeng Ilmu MSMEs, enabling them to manage business content independently and expand their market reach.
Co-Authors Adzanil Rachmadhi Putra Almira Ivah Edina Almuhayar, Mawanda Alviano, Muhammad Fadhil Ananda Taqhsya Dwiyana Andini, Galuh Ardhani, Calista Ghea Dani Suandi Dermawan, Dwi Bagus Desita Nur Rachmaniar Dominggo Bayu Baskara Edina, Almira Ivah Fajrul Falah Arrafi Fannisa Egista Naya Helisyah Nur Fadhilah Helisyah Nur Fadhilah Imroatul Khoiriyah Muwahidah Ira Prapti Ningrum Izzah, Nurul Larasati, Harashta Tatimma Mazi Prima Reza Mesak, Evellyn Verity Mufaidah, Astikhatul Muwahidah, Imroatul Khoiriyah Nicko Nur Rakhmaddian, Nicko Nur Ningrum, Ira Prapti Ningtyas , Miranthy Pramita Nurul Izzah Purwaningrum, Alfi Qothrunnadaa Nahdah Dzakiyyah Raditya, Helga Fadhil Rafif, Sulthan Regita Putri Permata Regita Putri Permata Reza, Mazi Prima Rifdatun Ni’mah Rizky Fenaldo Maulana Sanjaya, I Made Wisnu Adi Savira, Ryanta Meylinda Tanzilal Mustaqim Vivi Indah Rahmawati Wachda Yuniar Rochmah Yohanes Setiawan