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Tesa Nur Padilah
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Clustering Data Penduduk Miskin Dampak Covid-19 Menggunakan Algoritma K-Medoids Novi Widiawati; Betha Nurina Sari; Tesa Nur Padilah
Journal of Applied Informatics and Computing Vol 6 No 1 (2022): July 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i1.3266

Abstract

Kemiskinan merupakan masalah yang mendasar, kemiskinan bisa berakibat pada terhambatnya pembangunan nasional. Ada beberapa aspek yang berkaitan dengan kemiskinan yaitu faktor ekonomi, politik, dan psikososial. Secara ekonomi, kemiskinan diartikan sebagai kurangnya sumber daya untuk memenuhi kebutuhan hidup dan meningkatkan kesejahteraan. Pada penelitian ini data yang digunakan pada tahun 2020 yang bersumber dari Badan Pusat Statistika. Dalam upaya menemukan kasus kemiskinan dampak covid-19 dapat menggunakan Data Mining. Tujuan dari penelitian ini untuk mengelompokkan kabupaten/kota yang memiliki kemiskinan dampak covid-19 dengan tingkat tinggi dan rendah di Indonesia. Penelitian yang akan dilakukan dengan langkah data mining yaitu CRISP-DM (Cross Industry Standart for Data Mining) yang terdiri dari 6 fase yaitu pemahaman bisnis (business understanding), pemahaman data (data understanding), pengolahan data (data preparation), pemodelan (modelling), evaluasi (evaluation), dan penyebaran (deployment). Algoritme yang digunakan pada penelitian ini yaitu K-Medoids. Pengukuran menggunakan bahasa R dengan bantuan fungsi Pamk sehingga hasil yang didapatkan pada dataset Penduduk Miskin Tahun 2020 memiliki cluster optimal sebanyak 2 cluster. Cluster1 dengan jumlah 121 kabupaten/kota dengan kategori tinggi, sedangkan cluster2 dengan jumlah 427 dengan kategori rendah. Hasil dari evaluasi nilai Silhouette Coefficinet sebesar 0,4735719 .
Optimasi Algoritma K-Means Menggunakan Metode Elbow dalam Pengelompokan Penyakit Demam Berdarah Dengue (DBD) di Jawa Barat Dea Amelia; Tesa Nur Padilah; Asep Jamaludin
Jurnal Ilmiah Wahana Pendidikan Vol 8 No 11 (2022): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (332.172 KB) | DOI: 10.5281/zenodo.6831380

Abstract

Dengue hemorrhagic fever (DHF) is an acute febrile infectious disease that usually occurs in tropical and subtropical areas of the world and is caused by a virus transmitted by the Aedes mosquito, namely Aedes aegypti and Aedes albopictus. Dengue fever is one of the endemic diseases that almost occurs throughout the world. Indonesia is the country with the highest dengue fever cases in Southeast Asia. One of the provinces with the most cases of dengue fever is West Java. Every year cases of dengue fever have increased and decreased, so cases cannot be controlled properly. This must be a concern for the West Java Government in handling this Dengue Fever disease. To help the Government of West Java, this research conducted a grouping of dengue fever in West Java in 2016-2021. This research uses the Knowledge Discovery in Database (KDD) method. The algorithm used is k-means clustering with the help of the elbow method to get the optimal number of clusters, which is 2 clusters. Cluster 0 with low category consists of 22 regions, and cluster 2 with high category consists of 5 regions. The result of silhouette coefficient evaluation is 0.689 with standard structure criteria
Penerapan K-Means Clustering dalam Pengelompokan Kasus Tuberkulosis di Provinsi Jawa Barat Fadhlan Sulistiyo Hidayat; Rizma Berliana Putri Affandi; Virgaria Zuliana; Tesa Nur Padilah
Jurnal Ilmiah Wahana Pendidikan Vol 8 No 15 (2022): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (183.523 KB) | DOI: 10.5281/zenodo.7049113

Abstract

Tuberculosis is a very common infectious disease and is lethal in most of the cases. This is the background of this research, namely because there are many cases of Tuberculosis in Jawa Barat. According to data obtained from the Open Data Jabar, namely Tuberculosis Data in Jawa Barat Province, showing data that in 2020 all districts and cities in Jawa Barat had a number of Tuberculosis cases starting from 320 cases in Banjar Regency which was the lowest case, and 10,248 cases in Bogor Regency which is the highest case in Jawa Barat. The purpose of this study was to cluster TB cases into high and low categories based on gender. The data we use is data on the number of TB cases in Jawa Barat province in 2020 which consists of 27 districts/cities. In this study using the Clustering method with the K-Means algorithm. The results obtained based on the test, the clusters obtained were 2 with cluster 0 with 23 low TB cases and 4 clusters for high TB cases. Researchers hope that the results of this study can become knowledge for the government to reduce the number of TB in Jawa Barat
Perancangan Sistem Informasi Penjualan Produk Parfum Berbasis Web Pada Toko Rinas Mashel Bekasi Raynaldy Mahdi Putra; Tesa Nur Padilah; Carudin Carudin
Jurnal Ilmiah Wahana Pendidikan Vol 8 No 18 (2022): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (204.139 KB) | DOI: 10.5281/zenodo.7134500

Abstract

Advances in Information Technology have experienced very significant developments in various aspects of human life, including in the electronic sales industry (E-Commerce). To take advantage of this potential, an E-Commerce Website-based Sales Information System is useful for selling goods or services through electronic media so that the process becomes computerized and able to function in processing data and changing data to obtain accurate information. Rinas Mashel is a store that sells a variety of inspired perfume products in Bekasi. In the process of making transactions, collecting data on goods and making reports at the Rinas Mashel store, they still use the manual method by recording them in a book, so this is considered very ineffective because it is feared that errors will occur due to human error factors. Therefore, the perfume product sales information system is needed by Rinas Mashel store to make it easier to run business processes and provide the information needed accurately. The results of this study are in the form of designing and implementing a sales system using the PHP, JavaScript, CSS, HTML programming languages with MySQL database. While taking advantage of this research is to be able to help Rinas Mashel to improve service by making it easier for customers in the sales transaction process and being able to help relieve admin performance in data collection and minimize errors in making sales reports.
PERBANDINGAN METODE SIMPLE QUEUE DAN QUEUE TREE DALAM OPTIMALISASI MANAJEMEN BANDWIDTH Nafis Naufal Anwari; Puwantoro .; Tesa Nur Padilah
Jurnal informasi dan komputer Vol 10 No 2 (2022): Jurnal Sistem Informasi dan Komputer yang terbit pada tahun 2022 pada bulan 10 (
Publisher : STMIK Dian Cipta Cendikia Kotabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35959/jik.v10i2.365

Abstract

The internet is currently very much needed because of the increasing number of users, many people are dependent on the internet because this information technology is very fast. In this case, it has a huge impact on the need for the provision of very efficient internet services. One technology that is becoming a trend in computer networks, namely wireless computer networks (wireless local area networka / WLAN). This technology is the development of local area network technology that allows efficiency in the implementation and development of computer networks that can increase user mobility and computer network technology using cable media. Bandwidth management is a way to manage the internet network for even distribution of bandwidth usage even though many network users use the simple queue and queue tree method, one method for doing a bandwidth management, in this simple queue and queue tree there are bandwidth management settings and can add bandwidth size every larger client, this research methodology uses qualitative research results. The results showed that the results of the comparison of two simple queue and queue tree methods were optimal enough to be used in cybercomnet bandwidth management.
Pencarian Pola Pemakaian Obat Menggunakan Algoritma FP-Growth Nikita Salsabila; Nina Sulistiyowati; Tesa Nur Padilah
Journal of Applied Informatics and Computing Vol 6 No 2 (2022): December 2022
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v6i2.4187

Abstract

Obat‘merupakan sebuah bahan yang digunakan‘untuk mendiagnosis sebuah penyakit yang dapat digunakan untuk pencegahan atau pengobatan penyakit pada manusia atau hewan. Dalam penggunaannya, proses perencanaan stok obat di klinik atau rumah sakit merupakan hal penting yang harus diperhatikan karena apabila stok obat tidak sesuai maka akan menimbulkan masalah dalam ketersediaan stok obat. Pada penelitian ini terjadi permasalahan pada stok obat pada sebuah klinik yang berlokasi di Kabupaten Brebes yang mana terjadi kelebihan stok obat yang mengakibatkan jumlah data stok obat tidak sesuai dengan stok obat yang tersedia. Oleh sebab itu proses data mining dengan bantuan metodologi Knowledge Discovery in Databases (KDD) digunakan untuk membantu dalam pengelolaan stok obat pada klinik tersebut. Adapun tahapan KDD diantaranya, data selection, data pre-processing, data transformation, data mining, dan interpretation/evaluation. Pengujian dilakukan dengan menggunakan aplikasi Rapid Miner. Penerapan metode asosiasi pada data mining mampu menghasilkan suatu aturan asosiasi baru dari masing–masing item. Berdasarkan analisis yang dilakukan dengan algoritme FP-Growth, ditetapkan nilai support sebesar 75 frekuensi atau 23% dan nilai confidence sebesar 75%. Hasil penelitian menghasilkan 6 aturan asosiasi dengan kombinasi item terbesar hingga 3 item. Evaluasi pengujian yang didapat dari nilai Lift Ratio mendapat nilai rata-rata sebesar 1.267.
Analisis Sentimen Opini Publik Tentang Vaksin Booster Menggunakan Metode Support Vector Machine dan firefly Algorithm RIfky Pujianto; Dadang Yusup; Tesa Nur Padilah
Jurnal Ilmiah Wahana Pendidikan Vol 8 No 23 (2022): Jurnal Ilmiah Wahana Pendidikan
Publisher : Peneliti.net

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (353.475 KB) | DOI: 10.5281/zenodo.7397891

Abstract

Coronavirus is a viral epidemic that has swept across the world. Indonesia is one of the countries affected by the virus, so the government is trying to prevent the spread of the coronavirus so that not many people are exposed to the coronavirus. One of the government's efforts to prevent the spread of this virus is to create a free vaccination program. In January 2022, the government issued the latest vaccine, namely the booster vaccine. The emergence of the booster vaccine is slightly doubted by the public because of the many hoax news about this booster vaccine. This study aims to analyze the sentiment of public opinion on the emergence of the booster vaccine. The data used for this analysis comes from public opinion on Twitter. The data is taken using the crawling method. This research uses the support vector machine (SVM) method as a process for classifying public opinion and the firefly algorithm as an optimization of SVM parameters. There are 3 class labels used for classifiers, namely positive, negative, and neutral. A lot of data used after the pre-processing process is 2223 data which is then split into as much as 80% training data and 20% testing before entering the classification stage using the SVM method. The results of the classification using SVM produce an accuracy of 85% on the default parameters and after being optimized using the firefly algorithm it produces an accuracy of 86% with parameters C = 1.0–3.0, = 0.1-1.0.
PENERAPAN ALGORITMA K-MEANS CLUSTERING UNTUK PENGELOMPOKAN KECELAKAAN BERKENDARA DI RUAS TOL JAKARTA-CIKAMPEK Mochamad Riszky Sulaeman; Purwantoro .; Tesa Nur Padilah
Jurnal informasi dan komputer Vol 11 No 01 (2023): Jurnal Informasi dan Komputer yang terbit pada tahun 2023 pada bulan 04 (April)
Publisher : STMIK Dian Cipta Cendikia Kotabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35959/jik.v11i01.369

Abstract

The high number of driving accidents on toll roads is an evaluation material. So that it becomes a special concern for toll road service providers, both state-owned and private, which have proven this concern by improving, adding infrastructure and educating road users to minimize accidents on toll roads. The initial stage of preventing driving accidents is to find out the factors that cause driving accidents obtained through accident data analysis. The analysis can be done with Data Mining, namely K-Means Clustering. K-Means Clustering groups the data into several clusters according to the characteristics of the data. The clustering stage is carried out by determining the number of cluster trials, namely by setting k = 3, k = 5 and k = 7, and the performance is using the Davis Bouldin Index (DBI). The results of the cluster application of K-Means Clustering are tested to determine the best cluster model that tested and refers to the evaluation of DBI performance which approaches the value of Zero (Best value) sequentially so that the value of k=7 is the best DBI value of 0.179 while for k=5 the DBI is 0.180 and k=3 the DBI value is 0.233.
PENERAPAN ALGORITME FP-GROWTH UNTUK MENENTUKAN PELETAKAN BARANG PEDAGANG SAYUR Wahyu Alfafisabil; Budi Arif Dermawan; Tesa Nur Padilah
Jurnal Informatika Polinema Vol. 7 No. 4 (2021): Vol 7 No 4 (2021)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v7i4.507

Abstract

Sayuran merupakan sumber vitamin dan protein. Setiap ibu rumah tangga membutuhkan sayuran untuk memasak dalam kehidupan sehari-hari. Sayuran didapatkan di pasar sehingga akan mempersulit ibu rumah tangga yang rumahnya jauh dari pasar. Pedagang sayur keliling merupakan pedagang yang menjual berbagai macam sayuran yang dibawa ke rumah-rumah untuk memenuhi kebutuhan ibu rumah tangga. Pedagang sayur keliling bertujuan untuk mencari keuntungan, sehingga untuk memaksimalkan tingkat penjualan diperlukan strategi penjualan. Association rules adalah metode untuk mencari hubungan antar item pada suatu dataset. Data mining dapat disebut salah satu langkah dari proses KDD. FP-Growth merupakan algoritme untuk mencari himpunan data yang paling sering muncul. Penelitian ini menganalisis data transaksi untuk memprediksi peletakan barang dipedagang sayur dengan tujuan memaksimalkan tingkat penjualan menggunakan algoritme FP-Growth dan bahasa pemrograman python. Pada proses data mining dengan menggunakan algoritme FP-Growth peneliti menjelaskan langkah-langkah FP-Growth dengan perhitungan manual. Evaluasi peneliti melakukan pencocokan hasil perhitungan manual dengan program. Setelah perhitungan sesuai, peneliti menggunakan data tota transaksi untuk mengetahui rules-nya dengan syarat minimum support 0.01 atau 1% dan minimum confidence 0.9 atau 90%. Pada hasil terdapat 44 rules yang memenuhi syarat.
Co-Authors Asep Jamaludin Budi Arif Dermawan Carudin Carudin Dadang Yusup Dea Amelia Fadhlan Sulistiyo Hidayat Mochamad Riszky Sulaeman Nafis Naufal Anwari Nikita Salsabila Nina Sulistiyowati Novi Widiawati Purwantoro . Puwantoro . Raynaldy Mahdi Putra RIfky Pujianto Rizma Berliana Putri Affandi Virgaria Zuliana Wahyu Alfafisabil