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All Journal POSITIF Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) Ilmu Pendidikan: Jurnal Kajian Teori dan Praktik Kependidikan Jurnal Pilar Nusa Mandiri Indonesian Journal of Applied Statistics Desimal: Jurnal Matematika MUST: Journal of Mathematics Education, Science and Technology Adi Widya : Jurnal Pengabdian Masyarakat International Journal of Computing Science and Applied Mathematics Buana Matematika : Jurnal Ilmiah Matematika dan Pendidikan Matematika Jurnal Ilmiah Sinus Jurnal Karinov Jurnal PAUD: Kajian Teori dan Praktik Pendidikan Anak Usia Dini Square : Journal of Mathematics and Mathematics Education Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Journal of Mathematics Education and Science Indonesian Journal of Mathematics and Natural Science Education International Journal of English Linguistics, Literature, and Education (IJELLE) Postulat : Jurnal Inovasi Pendidikan Matematika Journal of Practical Computer Science (JPCS) prosiding seminar nasional Abdi Makarti Euclid International Journal of Trends in Mathematics Education Research (IJTMER) Journal of Technology, Mathematics and Social Science (J'THOMS) Jurnal Pengabdian Masyarakat Ilmu Komputer Indonesian Journal of Mathematics and Natural Science Education Jurnal Pengabdian Masyarakat Teknologi dan Pendidikan (MANTAP) Journal of Information Technology, Computer Engineering and Artificial Intelligence (ITCEA)

Retno Tri Vulandari

STMIK Sinar Nusantara

Author-ID : 639527

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Physics Social Sciences Other

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Penerapan Algoritma Fuzzy Time Series Average-Based untuk Memprediksi Penjualan Kelapa Retno Tri Vulandari; Sri Siswanti; Dwi Tri Laksono
Indonesian Journal of Mathematics and Natural Science Education Vol 1 No 2 (2020): Indonesian Journal of Mathematics and Natural Science Education
Publisher : Fakultas Tarbiyah dan Ilmu Keguruan, IAIN Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35719/mass.v1i2.31

UD Bambang Kelapa adalah salah satu bisnis di Solo yang bergerak dalam penyediaan kelapa parutuntuk rumah makan dan beberapa industri kuliner yang ada di wilayah Solo. Pada operasinya UD Bambangmembawa kelapa dari luar setiap bulan untuk memenuhi kebutuhan semua pelanggannya. UD Bambangsering mengalami kesulitan dalam menentukan jumlah kelapa yang dibutuhkan setiap bulan, oleh karenaitu UDBambang membutuhkan sistem yang dapat digunakan untuk memprediksi permintaan kelapa dalambeberapa bulan terakhir. Berbasis fuzzy time series average adalah metode prediksi yang menggunakanprinsip fuzzy dan memiliki akurasi yang cukup baik untuk peramalan jangka pendek, sehingga metode inisesuai untuk meramalkan kebutuhan penjualan kelapa. Data yang digunakan dalam penelitian ini adalahdata kebutuhan penjualan kelapa dalam setahun terakhir, 2015 - 2016 dalam hal ini diperoleh dari UDBambang Kelapa. Hasil yang diperoleh dalam penelitian ini adalah akurasi algotima berbasis fuzzy timeseries rata-rata untuk prediksi kebutuhan penjualan kelapa dengan pengujian data pada tahun 2016 sebanyak12 data yang diuji dengan mean absolute error (MAPE) adalah 7,82% dan termasuk dalam kategori baikkriteria. Sedangkan hasil pengujian fungsional menggunakan metode Black Box Testing, diperoleh bahwasemua komponen sistem telah diuji dan sesuai dengan yang diharapkan

PERBANDINGAN HASIL PANEN PADI DIPENGARUHI RATA-RATA CURAH HUJAN ATAU IRIGASI DENGAN MODEL REGRESI NONLINIER KUBIK DIKABUPATEN SUKOHARJO Dhian Dwi Hermawan; Bebas Widada; Retno Tri Vulandari
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 6, No 1 (2018): Jurnal TiKomSiN
Publisher : STMIK Sinar Nusantara

The rice yields in Sukoharjo Regency each year experience unstable ups and downs. The absence of predicted rice yield prediction resulted in lack of information needed to increase rice production in Sukoharjo Regency. The purpose of this research is to apply Cubic Nonlinear Method to predict rice yield in Sukoharjo Regency by comparing irrigation model with rainfall average model to see the accuracy in predicting the rice harvest in Sukoharjo regency. The design method uses UML (Unified Model Language), a program created using vb net programming language and using SQL server database, functionality testing using Black Box Test and validity testing using MSE and MAPE. The computed data is data of 2016. The results show prediction in 2017 with irrigation model has more accurate calculation result. The calculation of MSE and MAPE values manually and applying is the same ie75401808,23 and 3.01862E-14. The Cubic Nonlinear Method with irrigation model can be the initial solution to predict the rice harvest in Sukoharjo District and the output of the program is the prediction of rice harvest from the Cubic Nonlinietic Method method.Keywords: Prediction, Nonlinear Regression, Cubic, Rice Harvest

Penerapan Metode Naive Bayes Untuk Klasifikasi Pelanggan Hakam Febtadianrano Putro; Retno Tri Vulandari; Wawan Laksito Yuly Saptomo
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 8, No 2 (2020): Jurnal TIKomSiN, Vol.8, No. 2, 2020
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v8i2.500

Business location plays an important role in sales. The business location in cities makes the seller easier to distribute activities for people. Distribution activities are closely related to sales activities. If there is a sales transaction, a classification of potential and non-potential customers will be required. One method that can be used for classification is mining data. One of the most frequently used data mining for classification is the Naive Bayes method. The attributes used in the customer classification process are purchase amount, time interval, and location. The result of the classification system is 23 true reactions and 2 false reactions. Based on the results are using the confusion matrix method, it shows that the accuracy value reaches 92%, the precision value reaches 100%, the recall value reaches 91%.Keywords: Trading Business, Customer Classification, Naive Bayes, Confusion Matrix

Implementasi Metode Double Exponential Smoothing pada Prediksi Jumlah Penjualan Kain Pantai Nacita Agnes Dorestin; Wawan Laksito YS; Retno Tri Vulandari
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 10, No 1 (2022): Jurnal TiKomSiN, Vol. 10, No. 1, April 2022
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v10i1.596

Y2K Batik is an SME (Small and Medium Enterprise) engaged in batik. Y2K Batik produces and sells beach wear with various motifs. One of the important things in business is inventory of merchandise, inventory of merchandise is a factor in determining the success of a trading company to achieve its goals, because the goods sold affect the level of income to increase company profits. With these considerations, it is necessary to analyze the production of beach wear for the availability of merchandise in fulfilling customer orders. Based on the above background, the scope of the problem in this study is master data collection obtained from records of selling beach batik cloth periodically from time to time. By utilizing the existing data and applying certain methods, a sales forecasting prediction can be made using the Double exponential Smoothing method. From the results of calculations and testing of forecasting data on the Mandala Motif Beach Fabric variable with the most optimal value using = 0.9 of 2127 with an error value of 19.46% and an accuracy rate of 80.54% (Good). The Canting Motif Beach Wear variable with the most optimal value using = 0.9 of 3174 with an error value of 3.61% and an accuracy rate of 96.39% (Very Good). Double Exponential Smoothing is the most widely used method to determine the trend equation of the second smoothing data through a smoothing process. The programming language uses Microsoft Visual Studio 2013 and the DBMS uses Microsoft SQL Server 2012. The purpose of this research is to create a system that can simplify the process of analyzing the production of beach wear in order to meet the availability of goods ordered by customers.

Implementasi Metode Penghalusan Ekponensial Tunggal Dalam Prediksi Penjualan Buku Heri Setyawan; Sri Hariyati Fitriasih; Retno Tri Vulandari
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 9, No 2 (2021): Jurnal TiKomSiN, Vol. 9, No. 2, 2021
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v9i2.539

The prediction of the quantity of product sales in the future is intended to control the amount of existing product stock, so that product shortages or excess stock can be minimized. When the quantity of sales can be predicted accurately, the fulfillment of consumer demand can be sought on time and the cooperation of the store with the relationship is maintained well so that the store can avoid losing both sales and consumers. The purpose of this study is to compare the effectiveness of the use of the Single Exponential Smoothing method and methods Double Exponential Smoothing with a smoothing parameter value a = 0.5 for forecasting sales by comparing the error values in the two methods using the Mean Squared Error (MSE) method, the MSE results of the Single Exponential Smoothing method is 4967.75 while the MSE Double Exponential Smoothing is 5113.03. Thus, the Single Exponential Smoothing method is more accurate than Double Exponential Smoothing in calculating book sales forecasting because it has a low MSE value.

PENERAPAN ALGORITMA APRIORI PADA SISTEM REKOMENDASI BARANG DI MINIMARKET BATOX Nur Fitrina; Kustanto Kustanto; Retno Tri Vulandari
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 6, No 2 (2018): Jurnal TIKomSiN
Publisher : STMIK Sinar Nusantara

Recommendations are application models from previous measurement of data and information. To process data that is quite a lot is used the right method. Association rules are one technique that can be used in associating indirect data from a data. The purpose of this study is to create a system that can be used to provide information on goods in accordance with consumer combinations. The method used is direct interviews with staff to get information in the form of sales data and system requirements. The design model uses the System Development Life Cycle (SDLC), namely Analysis, Design, Construction, Implementation, and Testing. The system design method used is UML (Unified Modeling Language). The system used is an algorithm that is made web-based using the language PHP and MySQL as databases. The results used in this study are to stop at the specified 2-item iteration and two rules that meet minimum 30% support rules and a minimum confidence of 70%, namely Cofemix → Sugar and Sugar → Sugar.

Prediksi Penjualan Kertas Menggunakan Metode Double Exponential Smoothing Erinsyah Aditya Nugroho Putro; Elistya Rimawati; Retno Tri Vulandari
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 9, No 1 (2021): Jurnal TIKomSiN, Vol.9, No. 1, 2021
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v9i1.548

One of the important thing in business is the inventory of goods and services. Business goal can be reached when business owner know how the number of their inventory. Printing business is using forecasting model in their purchasing raw materials to estimate and calculate their selling prediction. That model is used to minimize economic losses when the costumer canceled order because paper was ran out and to prevent paper damage does not occur date to storage that to long. Double Exponential Smoothing method is used in this research to predict the sales of Paper A and HVS A3+ paper and calculates the prediction error with MAPE (Mean Absolute Percentage Error). This study aims to make an accurate forecasting application. The prediction results from application are in the form of prediction calculations for sales in the following month which will be used to optimize the purchase of paper to be sold. In applying the research results of Paper A and HVS A3 +, the best alpha was obtained in the 12th period, namely 0.3 and 0.6 with a MAPE error of 12% and 18% and an accuracy rate of 88% and 82% where the alpha was used to predict period 13 and produces a forecast value of 446 for Paper A and 474 for HVS A3 +

IMPLEMENTASI K-MEANS CLUSTERING PADA PENGELOMPOKAN POTENSI KERJASAMA PELANGGAN Ragil Prasojo; Yustina Retno Wahyu Utami; Retno Tri Vulandari
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 7, No 2 (2019): Jurnal TiKomSiN, Vol.7, No. 2, 2019
Publisher : STMIK Sinar Nusantara

Tight competition in the business world today, the number of MSMEs engaged in the same field, this requires MSMEs to develop strategies to achieve goals. Apart from having to develop products and services, an MSME must also retain customers. Therefore grouping of potential customers is needed. By utilizing data that is an indicator of the customer. This utilization is called data mining. Data mining is run based on data that has been determined that is customer data, number of accessories, cooperation time, and item returns. Therefore in this study, a potential customer collaboration system was designed using the K-Means method, so that potential customers are obtained. The results of this study are a web-based system application that can classify customers with the K-Means method. Grouping into 3 clusters, the first cluster with enough criteria consists of 7 customer data. This criterion consists of customers who have a small number of goods purchased and a large number of goods returned. The second cluster consists of 17 customer data with good criteria. This criterion consists of customers who have a large number of goods purchases and a few goods returns. The third cluster consists of 7 customer data with very good criteria. This criterion consists of customers who have the most number of purchases and the least return of goods.Keywords: customer, Data Mining, K-Means Clustering

Implementasi Algoritma Apriori pada Tata Letak Kategori Buku di Perpustakaan Al Fiyan Nizaela F; Teguh Susyanto; Retno Tri Vulandari
Jurnal Ilmiah SINUS Vol 20, No 1 (2022): Vol. 20 No. 1, Januari 2022
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v20i1.566

The library is a collection place of various kinds of books. Arrangement of books by category called book shelving makes easier for customers to choose and find books. However, the location and arrangement of book categories becomes a problem in a library. Based on the book borrowing data, data mining was carried out to find out a book borrowed simultaneously by library visitor in one transaction. This can be solved by using the association rule technique and a priori algorithm. Possible combinations of borrowed books were based on certain rules and then tested whether the combination of items meets the minimum support requirements to create eligible rules. The results of this study were in the form of information about a combination of borrowed books for libraries to arrange the location of books according to categories that are often borrowed together.

Penerapan Metode Penghalusan Eksponensial Tunggal pada Prediksi Penjualan Air Minum dalam Kemasan Dwi Handoko; Andriani Kusumaningrum KW; Retno Tri Vulandari
Jurnal Ilmiah SINUS Vol 19, No 2 (2021): Vol. 19 No. 2, Juli 2021
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v19i2.530

The Bottled Drinking Water Industry has grown rapidly to various provinces and cities throughout Indonesia now. The development of this industry is caused by high demand from consumers and the lower quality of raw water in springs and wells. PT. Cahaya Bumi Intanpari (CBI) is a company that produces gallons, bottles, and glasses bottled drinking water under the brand “AirMu”. Sales of bottled water every month always fluctuate, the management of PT. Cahaya Bumi Intanpari requires an estimate of the amount of production of each type of bottled water to market demand in the future. Based on the description of the background, in this study, a desktop-based application was designed and built. The research method used includes data collection and data analysis. Data collection includes observation, interviews, and literature study. While data analysis includes making data flow diagrams. The forecasting model is used in forecasting the sales of bottled drinking water at PT. Cahaya Bumi Intanpari is a time series or it can be called a time series, and the forecasting method used is single exponential smoothing. From the results of calculation testing, it is proven that the Single Exponential Smoothing method can be implemented in the AMDK sales forecasting system. Based on the validity test, it is found that the prediction test results of bottled drinking water sales below 20% are included in the good criteria.

Co-Authors Afan Lathofy Ahmad Samawi Al Fiyan Nizaela F Andriani Kusumaningrum Bayu Tristanto Bebas Widada Bebas Widada Bebas Widada Bebas Widada Bentar Putra Pamungkas Danar Wijaya Aditama Dhian Dwi Hermawan Dhian Dwi Hermawan Didik Nugroho Dwi Handoko Dwi Handoko Dwi Rema wati Dwi Remawati Dwi Tri Laksono Eny Nur Aisyah Erinsyah Aditya Nugroho Putro Ervina Yuliana Ningrum Fadel Thoriq Nur Muhammad Faris Abyan Zakly Febrianto, R Arie Febriyanti, Renita Hakam Febtadianrano Putro Hendro Wijayanto Hendro Wijayanto Heri Setyawan Hermawan, Dhian Dwi I Made Seken Kumaratih Sandradewi Kustanto Kustanto Kusumaningrum, Andriani Kusumawijaya, Andriani Kusumaningrum Lathofy, Afan Lestari, Zannuba Anugrah Indah Mita Purwati MUHAMMAD HASBI Muhammad Hasbi Muhammad Isnan Nurrohman Muhammad Yusuf Mujirahayu Meyliana, Nirma Nacita Agnes Dorestin Nacita Agnes Dorestin Nugraheni, Ria Pertiwi Nugroho, Zulkifly Setyo Nur Fitrina Parwitasari, Tika Andarasni paulus harsadi Putri Pertiwi, Ina Ragil Prasojo Raharja, Bayu Dwi Remawati, Dwi Restu Utami, Widya Ria Pertiwi Nugraheni Rimawati, Elistya Sakti, Dicky Cahyono Sandradewi, Kumaratih Sapto Nugroho Saptomo, Wawan Laksito Yuly Setiyowati Setiyowati Setiyowati Setiyowati Setiyowati Setiyowati Setiyowati Sri Hariyati Fitriasih Sri Harjanto Sri Harjanto Sri Harjanto Sri Siswanti Sumanto Suryadi Suryadi Suryanti Galuh Pravitasari Suryanti Galuh Pravitasari Sutrima Sutrima Teguh Susyanto Teguh Susyanto Tika Andarasni Parwitasari Tri Irawati, Tri Tristanto, Bayu Usep Kustiawan W, Yustina Retno Waskitho, Anggit Widhi wati, Dwi Rema Wawan Laksito YS Wawan Laksito Yuly Saptomo Widada, Bebas Wijayanto, Hendro Wuri Astuti Yehoshua Yehoshua Yustina Retno W Yustina Retno Wahyu Utami

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