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All Journal Tamilis Synex: Multidimensional Collaboration
Mariani Regina Sisilia Lengkey
Unknown Affiliation
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences

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Optimalisasi Keuntungan Penjualan Menu Pada Meet Point Cafe Menggunakan Metode Simpleks Mariani Regina Sisilia Lengkey; Lamberth Anthoni Yores Rumbino; Nahema Yaroseray; J.Anggun Rumboirusi; Charles Sesera Isawa; Wedes F Iwanggin; Sely Jowey; Heru Sutejo
Tamilis Synex: Multidimensional Collaboration innovation in the digital era
Publisher : CV Edujavare Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70610/tls.v2i01.362

Abstract

Studi ini bertujuan untuk menentukan jumlah produk yang harus dijual untuk memaksimalkan keuntungan suatu usaha makanan dengan mempertimbangkan biaya produksi, harga jual, dan persediaan bahan baku yang tersedia. Dalam penyelesaian masalah ini, metode Simpleks digunakan untuk merumuskan program linear. Data biaya produksi, harga jual, dan persediaan bahan baku dari empat jenis produk (nasi goreng cakalang, ayam kalasan, es jeruk, dan es cappucino) disediakan. Langkah-langkah formulasi program linear mencakup penentuan variabel keputusan, fungsi tujuan (maksimalkan keuntungan), serta penentuan batasan persediaan bahan baku dan jumlah produk yang harus dijual. Setelah formulasi selesai, algoritma Simpleks diterapkan untuk mencari solusi optimal. Hasil analisis menunjukkan jumlah optimal produk yang harus dijual dari masing-masing jenis, beserta keuntungan maksimum yang dapat diperoleh. Keuntungan yang di dapatkan oleh Meet Point Cafe, Untuk menu nasi goreng cakalang memiliki keuntungan sebesar Rp.36500, untuk ayam kalasan Rp.35000, untuk es jeruk Rp.16125 dan untuk es cappuccino Rp.20000. itu adalah hasil dari menu meet point café untuk makanan dan minuman yang ada pada café tersebut.
PENERAPAN ALGORITMA NAIVE BAYES TERHADAP TARGET PENJUALAN HANDPHONE MENGGUNAKAN APLIKASI RAPID MINER J. Anggun Rumboirusi; Nahema Yaroseray; Kartensia Firli Rumboirusi; Jessica Dumpel; Lamberth Anthoni Yores Rumbino; Mariani Regina Sisilia Lengkey; Heru Sutejo
Tamilis Synex: Multidimensional Collaboration Analysis of the Influence of Performance on Company Value and Purchasing Decisions in the Digital Er
Publisher : CV Edujavare Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70610/tls.v2i1.625

Abstract

This research aims to analyze cellphone sales predictions using the Naive Bayes algorithm which is implemented through the RapidMiner application. The dataset used consists of sales data with various relevant features, such as product descriptions, categories, and sales labels (sold or not sold). The research process involves several main stages, namely data retrieval (Retrieve), dividing data into train and test (Split Data), applying the Naive Bayes model, and evaluating performance using metrics such as accuracy, precision, and recall. The test results show that the Naive Bayes model succeeded in achieving accuracy, precision and recall levels of 100%. This indicates that the model has very good performance in classifying test data. However, to ensure the validity of the model, an analysis was carried out on the possibility of overfitting and suggestions for improvements such as using a larger dataset and testing using cross-validation. This research proves that the Naive Bayes method can be an effective and efficient solution for analyzing sales data patterns, especially in cases with structured and clear data patterns. The implementation of the results of this research can be applied as a basis for decision making in marketing strategy and inventory management.
Co-Authors Charles Sesera Isawa Heru Sutejo J. Anggun Rumboirusi J.Anggun Rumboirusi Jessica Dumpel Kartensia Firli Rumboirusi Lamberth Anthoni Yores Rumbino Nahema Yaroseray Sely Jowey Wedes F Iwanggin