MINING FOOD TRANSACTIONAL DATA TO PRODUCE ASSOCIATION RULES AS A BASIS OF BUSINESS ACTIONS

ABSTRAKSI: The food industry sells a range of product variations. The company wants to take advantage of their data by building business action from high volumes of transactional data. In this case, data mining technology needs to be implemented to explore valuable information on transactional data to assess customer\u27s preferences to products as a business strategy.Information about the customers’ behaviors of buying food products is important and this can be done by mapping the transaction data which is described as the pattern of customers’ tastes. The association method using apriori algorithm is used to map customers’ choice.The challenge is in the data itself, high volumes of data have to be prepared before the data is fetched to the mining process. Data reduction will be held to handle huge instances and attributes of the data. This research focused on the way the data were handled until the association rules were developed. To achieve this objective, three validation levels were implemented to verify the reliability of the association rules shows by percentage confidence.Furthermore, some data mining technique such as: clustering and time series pattern will be implemented to examine the truth of association rules which were built.It can be concluded that the association rules were established after three validation levels on reduced high volumes of transactional data, will generate strong association rules with confidence equal or higher than 70% and the rules established truth can be seen from the time series pattern on each group of goods which are then used as the basis of business actions.Kata Kunci : Data Reduction, Association Rules, Apriori, Confidence, Clustering, Time Series PatternsABSTRACT: -Keyword:

IMPLEMENTATION OF FUZZY TSUKAMOTO LOGIC TO DETERMINE THE NUMBER OF SEEDS KOI FISH IN THE SUKAMANAH CIANJUR FARMER`S GROUP

One of the innovation programs of the Sukamanah Village Karangtengah Cianjur farmer group is in the field of fisheries. One of the programs carried out is the nursery for ornamental Koi fish. Nursery of Koi fish is done because the market demand for Koi fish is high, but there are still very few Koi fish providers. However, farmer groups are currently unable to determine the number of seeds that must be provided to meet market needs to obtain maximum profit. To overcome this, a system is required that can calculate the number of seeds needed based on fish supply and market demand. Fuzzy logic can help humans make decisions; besides, fuzzy logic is an appropriate way to map an input space into an output space. This research aims to build an application using fuzzy logic to determine the number of seeds needed based on the amount of supply and market demand for Koi fish. The data used is sourced from the Sukamanah Farmer’s group, Cianjur. The results showed that using fuzzy logic succeeded in predicting the number of koi fish seeds that must be provided with an accuracy rate of 94,78% using the MAPE method

SMART MONITORING AND WATERING OF CHILI PLANTS USING A FUZZY MAMDANI SYSTEM

In this research, the design and manufacture of a prototype for a monitoring and watering system that integrates the concept of fuzzy logic in chili plants are carried out. The relationship between air humidity, air temperature and soil moisture can be identified to determine the right volume of water. The fuzzy system is built based on the chili farming environment and the specifications of the installed water pump. This system uses NodeMCU ESP8266 as the main controller for fuzzy inference calculations. The fuzzy inference calculation process uses the Mamdani method. Information such as air humidity, air temperature, soil moisture and water level will be displayed in real-time on the Blynk application connected to the internet network. The process of watering chili plants in this system is carried out according to a predetermined schedule. Results for seven days showed that the average duration of watering plants was 3.96 seconds with a flow rate ± 43.12 ml/s. By considering the maximum volume of the fuzzy system, the water consumption can be reduced with 30.96% efficiency

Efek Komunikasi Bermediakan Komputer pada Periklanan Online

Promosi paling efektif dan efisien era informasi adalah kolaborasi elemen dunia maya, layanan online seperti blog, forum diskusi, chat room, email, website , dan juga kekuatan komunitas yang dibangun pada jejaring sosial, sehingga komunikasi yang terjalin mampu memberikan efek dengan daya pikat berantai. Kuantitas penggunaan media-media promosi sebelum era informasi terus mengalamai degradasi dari tahun ke tahun yang diiringi dengan meningkatnya promosi atau iklan online, hal ini tercermin dari hasil riset terhadap perilaku pengiklanan brand papan atas.Penelitian ini menggunakan studi deskriptif dengan paradigm kontstruktivisme. Jika ingin berpromosi di abad 21, Perusahaan harus berpromosi mengikuti cara-cara orang-orang abad ini berkomunikasi, itulah cara promosi yang efektif, populer dan juga efisien

EFEK KOMUNIKASI BERMEDIAKAN KOMPUTER PADA PERIKLANAN ONLINE

Promosi paling efektif dan efisien era informasi adalah kolaborasi elemen dunia maya, layanan online seperti blog, forum diskusi, chat room, email, website , dan juga kekuatan komunitas yang dibangun pada jejaring sosial, sehingga komunikasi yang terjalin mampu memberikan efek dengan daya pikat berantai. Kuantitas penggunaan media-media promosi sebelum era informasi terus mengalamai degradasi dari tahun ke tahun yang diiringi dengan meningkatnya promosi atau iklan online, hal ini tercermin dari hasil riset terhadap perilaku pengiklanan brand papan atas.Penelitian ini menggunakan studi deskriptif dengan paradigm kontstruktivisme. Jika ingin berpromosi di abad 21, perusahaan harus berpromosi mengikuti cara-cara orang-orang abad ini berkomunikasi, itulah cara promosi yang efektif, populer dan juga efisien

DECISION SUPPORT SYSTEM FOR DETERMINING STUDENT ELIGIBILITY TO PARTICIPATE OF MBKM IN THE INFORMATICS STUDY PROGRAM USING AHP AND TOPSIS

To be able to have mastery of various sciences that are useful for experience in the world of work, students are encouraged through the MBKM program. Most students of the Informatics Study Program will choose an internship scheme and independent study in applying for the MBKM. However, the increasing number of students' interest in this program requires the Informatics Study Program to be more selective in analyzing the eligibility of students to take part in the MBKM program it has chosen. For this reason, a decision support system is needed that can assist the study program in determining and assessing the eligibility of these students. This study created a DSS modeling using the Analytical Hierarchy Process (AHP) method and the Technique For Order Preference by Similarity to Ideal Solution (TOPSIS) using 8 criteria

Konsumen Sebagai Co-Creation untuk Menentukan Strategi Bisnis Menggunakan Algoritma Apriori pada Industri Retail Skala Internasional

Industri retail skala internasional menjual banyak variasi produk yang didapat dari berbagai vendor,  transaksi penjualan yang terjadi membentuk gudang data yang tersimpan pada basis data Sistem Enterprise Resource Planning.  Ketersediaan data historis hasil transaksi yang terdokumentasi dapat manfaaatkan lebih lanjut untuk ditambang dengan menganalisa keranjang belanja konsumen dengan mencari korelasi antara produk-produk dalam kumpulan transaksi penjualan yang sudah terjadi dalam kurun waktu tertentu. Algoritma apriori digunakan untuk membangun aturan asosiasi yang berfokus pada memetakan perilaku konsumen retail  sebagai co-creation manajemen startegi perusahaan dan dapat menghasilkan hubungan dan aturan yang akan mengungkapkan pola preferensi pelanggan terhadap berbagai jenis produk, yang sebelumnya tersembunyi dan sulit diukur. Aturan asosiasi yang dihasilkan melalui serangkaian proses teknik data mining diujikan lebih lanjut untuk mengukur keberhasilkan aturan asosiasi menggunakan data transaksional pada periode berikutnya.  Hasil pengujian aturan asosiasi dengan nilai minimum confidence 70% digunakan sebagai dasar membangun strategi bisnis diantaranya: memperkuat penjualan paket, strategi penempatan produk,  segmentasi pasar berdasarkan preferensi warna, mengelola stok dan ketersediaan produk

MEMBERDAYAKAN KONTEN WEBSITE DENGAN ONLINE TELEPORT/SM-18

viii+149hlm;14x21c

Software Cracking

viii, 136 hlm.;23 cm.l ilus

CUSTOMER PROFILING PADA SUPERMARKET MENGGUNAKAN ALGORITMA K-MEANS DALAM MEMILIH PRODUK BERDASARKAN SELERA KONSUMEN DENGAN DAYA BELI MAKSIMUM

Sebuah  supermarket  dengan  sistem  informasi  berbasiskan komputer  memiliki  data  transaksi  dan  data  master  yang  dikelola dengan baik. Manajemen ingin membuat strategi bisnis berdasarkan  penambangan  historis  data  transaksi  yang dimilikinya.  Salah  satunya  dengan  mencari  tahu  segmentasi pola  perilaku  pelanggan  atau  customer  profiling yang memiliki daya beli tinggi terhadap barang-barang tertentu. Untuk  itu  akan  dilakukan  pencarian  informasi  berharga terhadap  analisa  data  mining  dengan  aturan  klasterisasi menggunakan  algoritma  K-Means  dalam  mengelompokan pola belanja konsumen terhadap barang