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PENERAPAN METODE AHP DALAM SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN PRODUK FURNITUR KAYU JATI (STUDI KASUS AGUNG JAYA MEBEL) Agung Dwi Prasojo; Hendarman Lubis; Allan Desi Alexander
Jurnal Informatika dan Teknik Elektro Terapan Vol 11, No 3 (2023)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v11i3.3242

Agung Jaya Mebel adalah usaha dagang yang memasarkan produk furnitur berbahan kayu jati merah di Bekasi. Namun, banyaknya jenis furnitur yang tersedia membuat pelanggan kesulitan dalam memilih produk yang tepat karena adanya berbagai variasi motif, kualitas dan ukuran terutama bagi pelanggan yang berasal dari luar kota yang ingin mencari produk ditoko tersebut. Untuk mengatasi tantangan tersebut, diperlukan suatu sistem yang dapat mengambil keputusan berdasarkan metode yang dapat memperhitungkan bobot relatif dari kriteria yang berbeda. Analytical Hierarchy Process adalah suatu metode yang digunakan untuk mengevaluasi dan membandingkan alternatif berdasarkan kriteria yang relevan. Hal ini memungkinkan pengembangan skor numerik untuk menentukan peringkat alternatif dari setiap alternatif yang memenuhi kriteria tertentu. Dalam pemilihan furnitur ini, AHP digunakan untuk mengevaluasi dan membandingkan furnitur berdasarkan kriteria yang relevan seperti harga, ukuran, kualitas kayu dan kualitas ukiran, yang diterapkan dalam aplikasi sistem pendukung keputusan yang dibangun dengan PHP MySQL. Hal ini diharapkan akan meningkatkan kepuasan pelanggan serta memastikan bahwa furnitur yang dipilih sesuai dengan kebutuhan dan harapan mereka. Hasil dari sistem pendukung keputusan ini berupa nilai prioritas dari seluruh kriteria dan alternatif serta memberikan informasi rekomendasi produk ketika nilai total >= 0,45.

Analisis Cluster K-Means dengan Metode Elbow untuk Menentukan Pola Penjualan Produk Traffic Room Summarecon Mal Bekasi Prasetya, Ajie; Salkiawati , Ratna; Alexander , Allan D
Journal of Students‘ Research in Computer Science Vol. 4 No. 1 (2023): Mei 2023
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/pytp8448

An effective sales strategy in the fashion retail business is essential to determine the success of the company or store. Like the Traffic Room store, which is a vintage fashion retail store that sells a variety of products. Although there are many products on sale, this store has not utilized sales data to determine product sales patterns, causing negative impacts such as there are still many products that are in short supply and products are not sold with predetermined targets. So the purpose of this study is t o determine product sales patterns in order to improve product inventory. To solve this problem, the analysis used is the K-Means algorithm to find product sales patterns assisted by the elbow method in determining the optimal cluster. As well as the flow in this research process is the CRISP-DM method with steps namely business understanding, data understanding, data preparation, modeling, evaluation and deployment. The results of this study obtained 4 clusters, namely cluster 2 or very in demand there are 2 products, cluster 3 or in demand there are 5 products, cluster 1 or quite in demand there are 5 products and cluster 4 or less in demand there are 3 products. The evaluation results get the optimal Sum of Square Error (SSE) value of 594,366.733 or 65.5%. From the evaluation results, it means that the performance of the K-Means algorithm used is good.

Analisis Cluster K-Means dengan Metode Elbow untuk Menentukan Pola Penjualan Produk Traffic Room Summarecon Mal Bekasi Prasetya, Ajie; Salkiawati , Ratna; Alexander , Allan D
Journal of Students‘ Research in Computer Science Vol. 4 No. 1 (2023): Mei 2023
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/5xve0445

An effective sales strategy in the fashion retail business is essential to determine the success of the company or store. Like the Traffic Room store, which is a vintage fashion retail store that sells a variety of products. Although there are many products on sale, this store has not utilized sales data to determine product sales patterns, causing negative impacts such as there are still many products that are in short supply and products are not sold with predetermined targets. So the purpose of this study is t o determine product sales patterns in order to improve product inventory. To solve this problem, the analysis used is the K-Means algorithm to find product sales patterns assisted by the elbow method in determining the optimal cluster. As well as the flow in this research process is the CRISP-DM method with steps namely business understanding, data understanding, data preparation, modeling, evaluation and deployment. The results of this study obtained 4 clusters, namely cluster 2 or very in demand there are 2 products, cluster 3 or in demand there are 5 products, cluster 1 or quite in demand there are 5 products and cluster 4 or less in demand there are 3 products. The evaluation results get the optimal Sum of Square Error (SSE) value of 594,366.733 or 65.5%. From the evaluation results, it means that the performance of the K-Means algorithm used is good.

Klasifikasi Citra Jenis Tanaman Jamur Layak Konsumsi Menggunakan Algoritma Multiclass Support Vector Machine Chusna, Nuke L.; Shalahudin, Mohammad Imam; Riyanto, Umbar; Alexander, Allan Desi
Building of Informatics, Technology and Science (BITS) Vol 4 No 1 (2022): June 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Mushrooms are plants that have high nutritional content and have various benefits for the health of the human body. However, not everyone knows the types of mushrooms that are suitable for consumption. The types of mushrooms have their own characteristics when viewed from the image. For this reason, a system is needed by utilizing digital image processing to classify types of mushrooms suitable for consumption, so that people can find out which types of mushrooms are suitable for consumption. This research is to classify types of mushrooms suitable for consumption using the Multiclass SVM algorithm with first-order feature extraction, which performs feature extraction based on the characteristics of the image histogram. The result of feature extraction is used as input for classification in Multiclass SVM. Multiclass SVM can map data points to dimensionless space to obtain hyperplane linear separation between each class. The developed method is implemented in Matlab, in order to produce a system in the form of a GUI so that it can be used by general users easily. Based on the test results, the average accuracy is 83%.

Implementation of a Combination of Rank Reciprocal and Additive Ratio Assessment Approaches for 3D Printer Selection Fatmayati, Fryda; Soares, Teotino Gomes; Tonggiroh, Mursalim; Alexander, Allan Desi
Bulletin of Informatics and Data Science Vol 2, No 2 (2023): November 2023
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v2i2.83

With the wide selection of 3D printers available on the market, the challenge arises for consumers and businesses to choose the device that best suits their specific needs. To determine the choice, the decision-maker must know one by one the specifications of the 3D printer to be purchased, which results in making difficult decisions and requiring a long time. This research aims to implement a combination of the Rank Reciprocal and additive ratio assessment (ARAS) approaches to make it easier to determine decisions for selecting a 3D printer. The Reciprocal Rank approach provides weight values by utilizing the reciprocal or inverse principle. Meanwhile, the ARAS approach is used to obtain the best alternative by evaluating alternative rankings based on their utility function. From the case studies that have been carried out, the highest to lowest utility values are Anycubic 4Max Pro (A2) getting a score of 0.8289, Creality Ender-3 Pro (A1) getting a score of 0.6174, Anet 3D Printer ET4 Pro (A3) getting a score of 0.5510, and Mingda Magician X2 (A4) getting a score of 0.5116. The output produced by the system in the case study carried out produces the same value as the manual calculation, meaning that the ARAS method calculation in the system is declared valid. Based on usability testing, it got a score of 90%, which shows the system is suitable for use

Determining Sales Patterns Using the Apriori Algorithm: A Case Study of Unlocked Cafe's Website Applications Sari, Rafika; Helmy, Nur; Alexander, Allan Desi
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 1 (2024): March 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i1.8908

In the business world, the sales process is the key to a company's success. Business processes will involve a lot of transaction data which will increase over time. This accumulation of data will not provide meaningful information if it is not processed and utilized properly. Correct decision making is obtained from accurate and informative data. This research was conducted to analyze, simulate and digitize data in the form of a website-based system which can be used as recommendations in making business decisions. The application of the Apriori algorithm supports system development in determining sales patterns by providing an overview of sales patterns for products of interest so that sales association rules are obtained. This research dataset was taken from transactions at the Unlocked Café & Coffee shop. The result of this research is an application designed according to the needs of business owners in the form of selecting itemsets by applying the Apriori algorithm to produce output in the form of product stock reference data and product sales patterns.

Perancangan Sistem Informasi Helpdesk Menggunakan Website Design Methode Dalam Mendukung Tata Kelola Teknologi Informasi Pamnungkas, R Wisnu Prio; Alexander, Allan D; Reza, Ali
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Information Technology is important in increasing efficiency and efficiency in achieving company goals. Is a regionally owned company that in carrying out the functions and duties of clean water services for customer needs is never separated from the company's services to customers. Thus the helpdesk application is designed as a Single Point of Contact to focus on customer service issues. The purpose of this research is to analyze and manage the helpdesk application with a display design using the website design method. Built with PHP and MySql database, the application aims at implementing ITIL, which is useful for managing and assisting any problems (reporting) and service requests (requirements) to be sent to the unit that manages the handling schedule based on priority weights.

Perancangan Sistem Informasi Helpdesk Menggunakan Website Design Methode Dalam Mendukung Tata Kelola Teknologi Informasi Pamnungkas, R Wisnu Prio; Alexander, Allan D; Reza, Ali
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 3, No 2 (2019): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v3i2.141

Information Technology is important in increasing efficiency and efficiency in achieving company goals. Is a regionally owned company that in carrying out the functions and duties of clean water services for customer needs is never separated from the company's services to customers. Thus the helpdesk application is designed as a Single Point of Contact to focus on customer service issues. The purpose of this research is to analyze and manage the helpdesk application with a display design using the website design method. Built with PHP and MySql database, the application aims at implementing ITIL, which is useful for managing and assisting any problems (reporting) and service requests (requirements) to be sent to the unit that manages the handling schedule based on priority weights.

Model Prediksi Penyakit Jantung dengan Penanganan Outlier Menggunakan Interquartile Range dan Extreme Gradient Boosting Azhari, Lukman; Wulandari, Novi; Adiningrat, Feru; Alexander, Allan Desi
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): Januari 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6390

Heart disease remains one of the leading causes of death worldwide, with increasing prevalence rates, including in Indonesia. Delayed detection and diagnosis are the main challenges in treating this disease, as most cases are only identified after patients experience serious symptoms or heart attacks. Medical data often containing outliers and noise adds to the complexity of developing accurate predictive models. This study aims to develop a heart disease prediction model using a combination of the Interquartile Range (IQR) method for outlier handling and the Extreme Gradient Boosting (XGBoost) algorithm for predictive modeling. The IQR method is applied at the pre-processing stage to identify and eliminate outliers robustly without reducing data integrity, while XGBoost is used to build an efficient prediction model through an ensemble learning approach. The results showed significant improvements in model performance, with accuracy increasing from 75.41% to 89.47% and AUC-ROC from 0.8615 to 0.9450. The model demonstrates balanced predictive capabilities with precision of 95.24% and recall of 80.00% for cases without disease, and precision of 86.11% and recall of 96.88% for cases with disease. The developed model makes significant contributions by improving data quality through robust outlier handling using the IQR method, building a more accurate prediction model by leveraging the advantages of the XGBoost algorithm in the ensemble learning approach.

Implementasi Fuzzy Logic Pada Sistem Kontrol pH Air Mineral Berbasis IOT Joniwarta; Priatna, Wowon; Hamdani, Asep R.; Alexander, Allan D.
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i4.3356

Implementation of Fuzzy Logic in the IOT-Based Mineral Water pH Control System for various existing bottled mineral water products, this system can measure the pH value, to find out if the value is still within the limits suitable for consumption or not based on government regulations. The public finds it challenging to understand the level of the pH value of the product because the current state of information regarding the pH level of mineral water generally is not listed in the mineral water bottle circulating on the market. Hardware design, application design, and hardware and software integration were the three steps of this research project. The pH value will be read by this control system from the output of the sensors then the data is collected into a data set. The data will be examined for trends using fuzzy logic, which will be used to classify the maximum and minimum pH levels, acidity levels, and base levels. The study's findings show that an internet-based web of things can access the mineral water pH control system to ascertain each mineral water product's pH value and temperature. This information can then be used by consumers to ascertain the pH level of each mineral water product.

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