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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal IPTEK Bagi Masyarakat International Journal of Management Science and Information Technology (IJMSIT) TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Rohminatin Rohminatin
Universitas Royal
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mechanical Engineering Physics Public Health Social Sciences

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UI/UX Design: Digital Learning Platform Berbasis Minimum Viable Product (MVP) dan Design Thinking Edi Kurniawan; Nasrun Marpaung; Rohminatin Rohminatin; Nurul Rahmadani; Arya Armando Panjaitan
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2 (SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akun
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp84-89

Abstract

In the digital era, digital learning platforms have become an essential tool in the educational process. However, the success of a platform is not only determined by the availability of content but also by a satisfying user experience. To achieve this, developers often adopt the Minimum Viable Product (MVP) strategy, which allows them to release a product with minimal features to quickly obtain user feedback. Meanwhile, the Design Thinking approach provides a framework for deeply understanding user needs. This paper combines these two approaches to designing the UI/UX for the digital learning platform "Mentor on Demand", focusing on an optimized user experience where the usability testing results are obtained with scores for Students = 6 and Mentors = 5.9 both getting Pass Results.
SCM Prototype Design Using Economic Order Quantity (EOQ) Method to Improve Decor Material Inventory Performance Dina Triana; Muhammad Iqbal; Rohminatin Rohminatin
International Journal of Management Science and Information Technology Vol. 6 No. 1 (2026): January - June 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i1.7349

Abstract

The decoration industry is experiencing rapid growth along with the increasing public demand for decoration services for homes, cafes, commercial spaces, and various other aesthetic needs. This growth requires companies to have an effective inventory management system to ensure the availability of decorative materials and ensure optimal operational processes. However, actual conditions at Rahani Homedecor show that inventory management is still carried out manually, resulting in various problems, such as delays in stock recording, difficulties in monitoring stock availability, suboptimal procurement processes, and a high risk of excess or shortage of inventory. This study aims to design a Supply Chain Management (SCM) prototype using the Economic Order Quantity (EOQ) method to improve the performance of decorative material inventory management. The research method used is a descriptive qualitative approach through observation, interviews, and analysis of ongoing business processes. The EOQ method is applied to determine the optimal order quantity so that the procurement process can be carried out in a more planned and economical manner, while the SCM concept is used to integrate the flow of information between inventory, suppliers, and the purchasing process. The results show that the EOQ-based SCM prototype can help inventory management become more structured, organized, and easily controlled. The system developed facilitates user management of product data, supplier data, and purchasing transactions in a computerized manner, resulting in faster and more efficient work. Furthermore, the application of the EOQ method helps companies determine optimal order quantities based on inventory needs. Based on these results, it can be concluded that the application of SCM with the EOQ method can improve the effectiveness and efficiency of decorative material inventory management and support the smooth operation of the company.
Implementation of Supply Chain Management for Mineral Water Inventory Management at Putri Store Rahmadina Rahmadina; Novica Irawati; Rohminatin Rohminatin
Jurnal IPTEK Bagi Masyarakat Vol 6 No 1 (2026)
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/j-ibm.v6i1.1697

Abstract

Putri Store is a retail business that sells mineral water products with relatively high customer demand. However, its inventory management is still conducted manually, causing inaccurate stock records, delays in reordering, and frequent stockouts. Based on observations from August to October 2025, 26 stockout incidents were found across several mineral water products. This study aims to design and implement a web-based Supply Chain Management (SCM) system to improve inventory management effectiveness at Putri Store. The system was developed using the Waterfall method, consisting of requirements analysis, system design, implementation, testing, and evaluation. The system design used Unified Modeling Language (UML) and Entity Relationship Diagram (ERD), while implementation was carried out using PHP and MySQL. System testing was conducted using the Black Box Testing method on the main modules, including login, inventory management, supplier management, ordering, and reporting. The results showed that all system functions operated according to user requirements, achieving a 100% success rate. The developed system supports real-time inventory monitoring, integrates supplier data with the ordering process, and automatically generates inventory reports. Its implementation reduced stock search time from 10–15 minutes to 1–2 minutes and report generation time from 20–30 minutes to less than 5 minutes. User satisfaction reached 93.2%, with an average score of 4.66 out of 5. Therefore, the web-based SCM system effectively improves inventory accuracy, accelerates decision-making, and reduces stockout risks at Putri Store.
PENGARUH PENERAPAN SCM TERHADAP EFESIENSI PELAPORAN PENJUALAN DAN PENDAPATAN AGEN PADA STOKIS PT.HNI Rohminatin Rohminatin; Wan Mariatul Kifti; Amalia Amalia
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 7 No. 4 (2024): November 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i4.2291

Abstract

Persaingan bisnis yang ketat di era globalisasi menuntut perusahaan untuk menyusun strategi dan taktik bisnis yang efisien. Supply Chain Management (SCM) merupakan kunci sukses dalam memenangkan persaingan pasar, PT Herba Penawar Al-Wahida Indonesia, yang kemudian dikenal sebagai HNI-HPAI, merupakan salah satu perusahaan Bisnis Halal Network di Indonesia yang fokus pada produk-produk herbal. Dengan perkekmbangan teknologi PT. HNI HPAI menyadarai bahwa tidak boleh tertinggal sedikitpun agar bisa menjangkau semua anggotanya yang ada di seluruh Indonesia bahkan sampai ke luar negeri. Dengan penerapan teknologi E-SCM tentu sangat memudahkan para stokisnya dalam melakukan pelaporan penjualan, pembelian, pembayaran,  dan lagsung dapat mengetahui pendapatan,  kegiatan pelaporan bisa dilakukan Dimana saja yang terpenting terkoneksi dengan internet, dapat melalui mobile atau melalui website. Melalui penelitian ini dapat dilihat bahwa perkembangan teknologi dalam semua unsur terkhusus SCM (Suply Chani Management) sangat membantu dalam proses pencatatan penjualan, pendapatan serta uantu mengetahua stok persediaan produk.
ANALISIS MULTIVARIATE ADAPTIVE REGRESSION SPLINES DALAM PREDIKSI PENCAPAIAN TARGET PROFIT PERUSAHAAN DISTIBUTOR Suparmadi Suparmadi; Rohminatin Rohminatin; Rahmadita Rahmadita
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4244

Abstract

Abstract: An objective performance evaluation process that can describe the company's condition is through the achievement of targets from each factor that influences profit achievement. The many variables that influence this profit achievement require in-depth and systematic analysis to obtain complete, fast and accurate information. However, so far the Gerai Mustika distributor company has only focused on sales factors, and ignored other factors. Furthermore, the large amount of financial data that has been computerized so far at Gerai Mustika is only limited to weekly, monthly and annual reports, has not been optimally utilized to help management evaluate performance. The study aims to build a prediction model for achieving profit targets from company financial data using Multivariate Adaptive Regression Splines (MARS) based on machine learning. Based on the analysis results, the MARS model is proven to be superior to conventional multiple regression in predicting Gerai Mustika's profit, indicated by a higher R-squared value (0.756), as well as lower MAE and MAPE, so it is able to capture more complex data patterns and provide more accurate predictions; While multiple regression is still relevant for simple linear relationships, it is less than optimal in representing non-linear data variations. Keywords: Prediction; MARS Method; Distributor; Profit; Machine Learning Abstrak: Proses evaluasi kinerja yang objektif yang dapat menggambarkan konidisi perusahaan yaitu melalui pencapaian target-target dari seti ap faktor yang mempengaruhi pencapaian profit. Banyaknya veriabel yang mempengaruhi percapaian profit ini maka dibutuhkan analisa yang mendalam dan tersistem agar mendapatkan informasi yang utuh, cepat dan akurat. Akan tetapi, selama ini perusahan distributor Gerai Mustika hanya fokus pada faktor penjualan saja, dan mengabaikan factor yang lain. Selanjutnya, jumlah data keuangan yang besar yang telah terkomputerisasi selama ini di Gerai Mustika baru sebatas untuk laporan mingguan, bulanan dan tahunan saja, belum dimanfaatkan secara optimal untuk membantu manajemen mengevalausi kinerja. Penelitian bertujuan untuk membangun model prediksi pencapaian target profit dari data keuangan perusahaan menggunakan Multivariate Adaptive Regression Splines (MARS) berbasis machine learning. Berdasarkan hasil analisis, model MARS terbukti lebih unggul dibandingkan regresi berganda konvensional dalam memprediksi profit Gerai Mustika, ditunjukkan oleh nilai R-squared yang lebih tinggi (0,756), serta MAE dan MAPE yang lebih rendah, sehingga mampu menangkap pola data yang lebih kompleks dan memberikan prediksi yang lebih akurat; sementara regresi berganda masih relevan untuk hubungan linear sederhana, namun kurang optimal dalam merepresentasikan variasi data yang non-linear.Kata kunci: Prediksi;Metode_MARS;Distributor;Profit;Machine_Learning 
Co-Authors Amalia Amalia Arya Armando Panjaitan Dina Triana Edi Kurniawan Kifti, Wan Mariatul Muhammad Iqbal Nasrun Marpaung Novica Irawati Nurul Rahmadani Rahmadina Rahmadina Rahmadita Rahmadita Suparmadi Suparmadi