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All Journal Jurnal Mantik Jurnal Teknik Industri Terintegrasi (JUTIN) Jurnal Inovasi Teknik Informatika JUSTER: Jurnal Sains dan Terapan Jurnal Pengabdian Masyarakat Bhinneka Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Ilmu Kesehatan MAKIA Journal of Engineering Science and Technology Management JES-TM Social and Community Service
Kasini, Kasini
Universitas Pahlawan TuankuTambusai
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Journal : Jurnal Teknik Industri Terintegrasi (JUTIN)

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Penerapan Algoritma K-Means untuk Pengelompokan Data Mahasiswa Baru Program Studi Teknik Informatika di Universitas Pahlawan Tuanku Tambusai Kasini, Kasini; Rusnedy, Hidayati; Tanjung, Lailatul Syifa; Munti, Novi Yona Sidratul
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 8 No. 1 (2025): January
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v8i1.41449

Abstract

Pahlawan Tuanku Tambusai University (UP) in Riau Province has an Informatics Engineering Study Program that accepts new students every year from various regions around Bangkinang. Incoming student data is processed to assist decision making, especially in the field of promotion. This study aims to apply the K-Means algorithm to Informatics Engineering Study Program student data, with attributes of student name and district of origin, to group regions based on promotion potential. The K-Means method is used to group data into three clusters: High Priority, Medium Priority, and Low Priority. The results of the analysis show that there are 22 regions included in the High Priority Cluster, 23 regions in the Medium Priority Cluster, and 43 regions in the Low Priority Cluster. Regions in the High Priority Cluster are the main priority for promotion strategies, while regions in the Medium Priority and Low Priority Clusters require a more focused promotion approach. This study provides an important contribution to the promotion strategy of the Informatics Engineering Study Program at UP by using a data mining approach to increase the visibility of the study program in the community
Penerapan Sistem Inferensi Fuzzy untuk Menentukan Jumlah Pembelian Produk Berdasarkan Data Persediaan dan Penjualan dengan Menggunakan Metode Mamdani (Studi: Kasus RM Habibi) Hidayati, Nani; Kasini, Kasini; Permata, Aprilia
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 7 No. 3 (2024): July
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v7i3.30604

Abstract

RM Habibi is a restaurant business that serves dishes to buyers and provides a place to enjoy the meal, as well as determining food and service costs. Although restaurants generally serve on site, there are also those that provide take away and delivery services as a form of service to buyers. Restaurants usually specialize in the types of food they provide and are their best sellers. Inventory problems are a problem that buyers always face. Inventory is needed because demand patterns are basically irregular. Inventory is carried out to ensure certainty that when needed the product is available. Fuzzy logic is one of the components that make up soft computing.  The application of the fuzzy inference system (FIS) with the mamdani method in the Demand, Supply and Sales prediction system can be concluded that the use of fuzzy logic can be used to predict demand, inventory and totals at the Habibi Restaurant. And test results with real data and surveys show results with a conformity level of up to 90%.
Co-Authors Adeswastoto, Hanantatur Alfredo Siagian Fitria Kurniati, Mei Fitria, Mei Kumala Sari, Resy Marwa, Safni Mufidah Herviany Nani Hidayati Nani Hidayati Nani Hidayati, Nani Nany Librianty novi yona sidratul munti Permata, Aprilia Raja Joko Musridho Rusnedy, Hidayati Sabrina Aulia Rahmah Safni Marwa Saleha Putri Delima Syifa Tanjung, Lailatul Tanjung, Lailatul Syifa Triyana Nurhidayah Yusmita, Yesi Zainal Abidin, Ahmad