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Rismayanti
Universitas Harapan Medan
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Implementasi Data Mining Pada Hasil Penjualan Makanan Beku Menggunakan K Means Clustering Nenna Irsa Syahputri; Siti Sundari; Rismayanti
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 2 No. 2 (2023): Mei 2023
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v2i2.54

Abstract

Maintaining inventory stock so that there are no empty items is one way to maintain customer satisfaction. In today's competitive business world, we are required to always develop our business in order to survive in the competition, especially in sales competition, it requires entrepreneurs to find a pattern that can increase sales and marketing within the company, one of which is by utilizing sales data. Applying clustering data mining techniques so that it can help NCekma Frozen stores in determining strategies for determining frozen food stocks using the K Means algorithm.
Penerapan Data Mining dengan Metode Algoritma Apriori untuk Menentukan Pola Pembelian Froozen Food Siti sundari; Rismayanti; Khairunnisa
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 2 No. 2 (2023): Mei 2023
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v2i2.55

Abstract

Maintaining inventory stock so that there are no empty items is one way to maintain customer satisfaction. In today's competitive business world, we are required to always develop our business in order to survive in the competition, especially in sales competition, it requires entrepreneurs to find a pattern that can increase sales and marketing within the company, one of which is by utilizing sales data. Applying clustering data mining techniques so that it can help NCekma Frozen stores in determining strategies for determining frozen food stocks using the K Means algorithm.
APLIKASI ANAGLYPH 3D TATA CARA SHOLAT DAN DOA BERBASIS LIGHT VIRTUAL REALITY Ahmad Muammar Lubis; Sumi Khairani; Rismayanti
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 3 No. 2 (2024): Mei 2024
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v3i2.121

Abstract

Prayer is the second pillar of Islam and it is the pillar that is emphasized most after the two sentences of the shahada. Prayer is the connection between a servant and his Lord. Prayers are of two types, namely prayers of worship and prayers of supplication. Allah's closeness to His servants is divided into two types, namely; the closeness of His knowledge to every creature and the closeness to His servants in giving them every request, help and taufik. Learning prayer movements and prayers should be taught from an early age (children). Guidance from parents and teachers is the most important way to provide learning media. So far, conventional learning in the form of books makes children bored, so creativity or interactive learning methods are needed, one of which is multimedia-based learning.
Implementasi Metode K-Nearest Neighbor Untuk Klasifikasi Penyakit Tanaman Mentimun Pada Citra Daun Ratna Indah Juwita Harahap; Sumi Khairani; Rismayanti
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 3 No. 2 (2024): Mei 2024
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v3i2.123

Abstract

Cucumber is a vegetable that is widely consumed by Indonesian people. However, cucumber plants are susceptible to disease attack which causes substantial yield loss. Examples of disease in cucumber plants are downy mildew, powdery mildew, and cucumber mozaic virus. This disease can be recognized visually because it has a characteristic color and texture. Through an image, information can be learned about the cucumber plant disease. This study aims to build a disease classification system on cucumber leaf images so that it can provide information on the type of disease. The application of the system consisting of pre-processing, feature extraction, classification, and evaluation stages. The pre-processing stages resizes the RGB image and then converts it to Grayscale. The feature extraction stage uses the GLCM (Gray Level Co-Occurence) method. The classification stage uses the K-NN (K-Nearest Neighbor) algorithm. Evaluation stage is a confusion matrix. The results of the cucumber leaf disease classification test used the K-Nearest Neighbor algorithm, produced the best accuracy value by using the neighborhood value k=1 reaching 90%.
Co-Authors Ahmad Muammar Lubis Dharmawati Dian Alfa Ridho Elvira Hanum Nst Ema Wardiana Emma Yurispa Siregar Harahap, Herlina Hasibuan, Ade Zulkarnain Khairunnisa, Khairunnisa Muchriza Akbar Bancin Muhammad Fitra Hanafiah Muhammad Irsan Nur Ainun Nur Wulan Ratna Indah Juwita Harahap Siti Sundari Sumi Khairani Surya Ramadan Hasibuan Syahputri, Nenna Irsa Victor Alwi Hura Vira Anjani Yessi Fitri Annisah Lubis Yuyun Dwi Lestari