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All Journal Journal of Informatics and Computer Science (JINACS) Modem : Jurnal Informatika dan Sains Teknologi Journal of Emerging Information Systems and Business Intelligence (JEISBI) Inovate : Jurnal Ilmiah Inovasi Teknologi Informasi
ARIES DWI INDRIYANTI, ARIES
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Computer Science & IT Decision Sciences, Operations Research & Management Languange, Linguistic, Communication & Media Library & Information Science

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Analisis Sentimen Opini Publik Terhadap Kebijakan Baru Skripsi Pada Media Sosial Twitter Menggunakan Metode Naive Bayes: Public Opinion Sentiment Analysis of New Thesis Policies on Twitter Social Media Using the Naive Bayes Method Puspitasari, Refandah; Dwi Indriyanti, Aries
Journal of Emerging Information Systems and Business Intelligence Vol. 5 No. 3 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jeisbi.v5i3.61273

Abstract

Evaluation of Enterprise University Website Service Quality using E-Servqual and IPA Methods Valen Zidana Erlita; Dwi Indriyanti, Aries
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 3 No. 3 (2025): Juli : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v3i3.555

Abstract

The Enterprise University Website is an academic platform for internship students and employees at PT Petrokimia Gresik. This study aims to measure user satisfaction with the Enterprise University website and identify priority improvements using the e-Servqual and IPA methods. The e-Servqual method is applied through seven dimensions: Efficiency, System Availability, Fulfillment, Privacy, Responsiveness, Compensation, and Contact. Based on these, service indicators that should be the main focus for improvement are determined using the Importance-Performance Analysis (IPA) method. This research is a quantitative study. The sample consists of 49 Merdeka internship students at PT Petrokimia Gresik who are also users of the Enterprise University website. The results show that based on e-Servqual calculations, the overall average gap between user perceptions and expectations is (-0.61). This indicates that the service quality of the Enterprise University website is still lacking and does not provide user satisfaction. Furthermore, data analysis using the IPA method, as shown in the Cartesian diagram, reveals that the top improvement priorities lie in three indicators located in Quadrant I. The findings of this study can serve as a basis for strategic decision-making by platform managers to optimize services and enhance user satisfaction in the academic processes at PT Petrokimia Gresik.
Pengembangan Layanan Informasi FAQ Berbasis Chatbot di Badan Pendapatan Daerah Kota Surabaya Menggunakan Framework RASA Rendy Harenza, Aderio; Dwi Indriyanti, Aries
Journal of Informatics and Computer Science (JINACS) Vol. 6 No. 04 (2025)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jinacs.v6n04.p1168-1179

Abstract

Abstrak - Badan Pendapatan Daerah (Bapenda) Kota Surabaya sebagai lembaga publik yang berperan penting dalam pengelolaan pajak dan pendapatan daerah harus terus meningkatkan kualitas pelayanannya kepada masyarakat khususnya bagi para wajib pajak. Salah satu bentuk layanan informasi yang tersedia di Bapenda Kota Surabaya adalah fitur Frequently Asked Question (FAQ) yang dapat diakses pada website resminya. Namun layanan tersebut terbatas dan kurang efektif dalam menjawab berbagai pertanyaan dari masyarakat. Untuk mengatasi permasalahan tersebut, penelitian ini mengembangkan sistem chatbot berbasis framework RASA yang terintegrasi dengan sistem monitoring berbasis web. Penelitian ini menerapkan dua metode, yaitu metode CRISP-DM untuk pengembangan model chatbot dan metode Rapid Application Development (RAD) untuk pengembangan sistem monitoring. Hasil pengujian menunjukkan bahwa chatbot memiliki akurasi dengan nilai F1-score sebesar 0.946, nilai precision 0.954, dan tingkat keberhasilan story sebesar 84,6%. Sistem monitoring juga berjalan baik berdasarkan pengujian black box testing yang telah dilakukan. Dengan demikian, solusi ini cukup efektif dalam meningkatkan efisiensi layanan informasi dan meringankan beban petugas dalam memberikan informasi kepada masyarakat khususnya para wajib pajak. Kata Kunci— Frequently Ask Question, Chatbot, Framework RASA, Natural Language Understanding, Badan Pendapatan Daerah.
PENERAPAN ALGORITMA K-MEANS CLUSTERING SEBAGAI STRATEGI PROMOSI PENERIMAAN MAHASISWA BARU PADA UNIVERSITAS HASYIM ASY’ARI JOMBANG Mahmudi, Imam; Dwi Indriyanti, Aries; Lazulfa, Indana
Inovate Vol 4 No 2 (2020): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v4i2.692

Abstract

Admission of new students at the Hasyim Asy'ari University in Jombang is held every year. To more of the newstudents, admissions Committee conducted several promotions as very important early activities such as: online,banners, brochures, school events, and orally with student roles and Alumni. The number of competition infinding new student applicants, requiring the University of Hasyim Asy'ari to conduct analysis of several waysof promotion that have been done so that the promotion strategy can be seen which is more precise and effective.This research will conduct grouping/clustering of districts or cities based on certain attributes in a Web-basedapplication. The method used in this study is a K-means clustering algorithm that can group student data intomultiple clusters based on similar attribute agreements. The attributes used are hometown, online, oral,banners/billboards, brochures and events. At this Peletitian generate a total of 5 clusters (k = 5) with the firstcluster 20 hometown with the most effective promotional media online and oral, the second cluster of 31 Origincities with the most effective promotional media oral and online, the third cluster of 4 cities originating withmedia The most effective promotion of events and banners, the fourth cluster of 15 hometown with the mosteffective promotional media brochures and oral, the fifth cluster 2 hometown with the most effective promotionalmedia oral and event. The results of this study were used as a recommendation to determine a promotionalstrategy based on the promotional media of each cluster formed.Keywords: Promotion strategy, Admission of New Students, K-means Algorithm, Clustering
SISTEM PERAMALAN PENJUALAN TAS PADA TOKO FIRDAUS BAG BERBASIS WEB MENGGUNAKAN METODE MOVING AVERAGE Uswatun Khasanah, Siti; Dwi Indriyanti, Aries; Andriani, Anita
Inovate Vol 4 No 2 (2020): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v4i2.693

Abstract

Sales of bags every year experience a rapid growth, especially for types of school bags, therefore many ofthe bag shops that not only sell one type of school bag, but a variety of school bags, such as those that areoffered in Paradise Stores. Firdaus bag shop sells 17 types of school bags such as, ripper bags, alto bags,character bags etc. The number of bag sales reaches more than 100 pcs per month from all types of bags,but in making sales reports and reporting data the shop owner still uses a manual system. Asking the storeowner to have difficulty adding or subtracting bag data preparation data. The purpose of this research isto study the bag selling system in the web-based paradise Bag Store. The data in this study use 17 types ofbags with the method used in this study is the method of moving average or moving average. Movingaverage is one of the forecasting methods that uses time series data. The period used is period 6.Forecasting errors can be calculated using the MAD and MAPE formulas. The results of this study are abag sales system in the following month. The bag sales data used are January to December 2018 withmoving averages. The result of applying the moving average method is forecasting in January 2019.Forecasting the most bag sales in January 2019 is the sale of large ripper bags with a total of 127 pcs.Forecasting The level of accuracy is generated using MAD and MAPE. MAD for alto palo bags is 5.83while MAPE for alto palo bags is 58.02%.Keywords: Sales, Moving Average, Forecasting Error
Diagnosis Penyakit Tanaman Jagung Dengan Metode Case Based Reasoning Berbasis Android Lailiyah, Ami; Dwi Indriyanti, Aries; Wiratsongko, Radityo
Inovate Vol 5 No 1 (2020): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v5i1.3071

Abstract

Corn plant still ranks second as a staple food in Indonesia today. Limited knowledge and lack of understanding regarding the identification and handling of maize disease often result in less than optimal growth of the maize plant. If corn disease attacks when the maize is still young but the farmers are too late to control it, it is likely that it will have a bad impact on unsatisfactory yields and even result in crop failure. Given these problems, a system that has the expertise to diagnose diseases in corn is needed, which can process problems, accelerate and facilitate early detection of the risk of several diseases in corn plants. The method used to calculate the probability in the process of detecting the chance of emergence of the risk level of several diseases in corn is Case Base Reasoning using the java programming language, xml and using the Android-based MySQL database. The results of the system experiment carried out resulted in a rapid diagnosis with a percentage of certainty and a solution for treatment. Testing the respondent's assessment has resulted and it is concluded that the accuracy of the system based on the 30 data that has been tested can be seen that the diagnostic accuracy rate of this system reaches 83.33%. Keywords : Case Based Reasonig, Android, responden
Sistem Prediksi Persediaan Barang Menggunakan Metode Regresi Linier Berbasis Website Bastian Nursyahputra, Andhika; Dwi Indriyanti, Aries; Faizah, Arbiati
Inovate Vol 5 No 1 (2020): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v5i1.3072

Abstract

The prediction process is important for the company in the formulation of the company's strategy in the future. Therefore, a precise prediction method is needed by the company to be able to maximize the estimation of future sales. The Double Exponential Smoothing method is a popular method used in privacy because it has good performance. This method has parameter values and has a large influence on the results of predictions. This method uses data compilation that shows trends. Exponential smoothing in the presence of a trend such as a simple transmitter such as two components must be updated every period - its level and trend. Level is an estimate that is smoothed from the data value at the end of each period. A trend is a smoothed estimate of average growth. The purpose of this design produces a prediction method that is appropriate and applicable in the company to facilitate sales activities in the company. With the right prediction method, it is expected that the company can make efficient all the resources needed by the company. Keywords: Exponential Smoothing, Multiple Exponential Smoothing, level.
Rancang Bangun Web E-Commerce Menggunakan Metode Collaborative Filtering (Study Kasus: Toko aksesories tata) Aisha, Dita; Dwi Indriyanti, Aries; Heru Mujianto, Ahmad
Inovate Vol 5 No 1 (2020): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v5i1.3078

Abstract

E-Commerce is one of the alternative choices for a store that is used as a medium of information in order to facilitate interaction between sellers and consumers. The number of products, the variety of products in an e-commerce, often makes consumers feel confused about choosing the product they need. This resulted in a repetitive and time-consuming transaction process. Consumers are often confused about finding information on the rating of the product the user wants to buy. In this study, a Web e Commerce was created which was able to provide recommendations automatically to the user. The method used is the Collaborative Filtering method using Addjusted Cossine Similarity as a tool or method of calculating the similarity between users, then the weigted sum algorithm as the prediction calculation. Collaborative Filtering is used to assist users in selecting the appropriate item based on ratings given by other users. Keywords: Collaborative Filtering (CF), Recommendations, E-commerce Website.
Klasifikasi Dokumen Skripsi Dengan Menggunakan Text Mining (Studi Kasus: Fakultas Teknologi Informasi) Irfanto, Feri; Dwi Indriyanti, Aries; Bagus Pratama Putra, Dharma
Inovate Vol 5 No 2 (2021): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v5i2.3118

Abstract

Thesis document classification is a data mining method with the aim of categorizing thesis abstracts whose categories are unknown. The purpose of thesis document classification aims to assist students in finding a thesis document that is in accordance with their research by reading the abstract to find out specific category. The research discussed about the application of text mining in the classification of thesis documents with case studies at the Faculty of Information Technology. Text mining is functioned to extract data in the form of text to get information from a collection of documents. In this study using the Naïve Bayes Classifier method, a classification method by calculating probability by adding frequencies with a combination of values in the data set. This method has the aim of classifying the datatesting according to the datatraining attributes. Abstract files processed in this classification are abstract files from IT Faculty students who have graduated. There are 5 categories used, namely SPK, RPL, Data Mining, Image Processing, and System and Network Security. The process of calculating the classification of the thesis document using the Naïve Bayes Classifier method begins with inputting training data, preprocessing, calculating the term frequency (word occurrences), calculating the word probability value from the training data, and the final process is calculating the maximum probability value for each category. The data used in this study were 49 data, 34 of which were used for training data and the remaining 15 were used for testing data. Of the total 15 testing data, 14 data were classified correctly and 1 sample was not classified correctly. The accuracy obtained from the thesis document classification system is 93%. Keywords: Thesis Document Classification, Text Mining, Naïve Bayes Classifier
Sistem Penentuan Status Gizi Balita Menggunakan Metode Naïve Bayes Classifier (Studi Kasus Posyandu Anggrek Putih Seblak Desa Kwaron Chasanah, Nidhaul; Dwi Indriyanti, Aries; Faizah, Arbiati
Inovate Vol 6 No 2 (2022): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v6i2.3174

Abstract

Determination of toddler growth and development is very important to do to see if there is a growth disorder of toddlers from an early age by measuring body weight as the best way to assess the nutritional status of toddlers each month so that children's growth and development will be monitored by measuring toddlers and toddlers regularly, body weight and height. Posyandu is useful for providing services to the community about the importance of toddler development and nutritional status quickly and accurately. Therefore, in this research, make a system design as information about the nutritional status of toddlers us.ing th.e Naïve Bayes Classifier metod. This method is fairly sample classification metod by assuming the attribute classification. The calculation process using the Naive Bayes Classifier metod to determine the nutritional status of toddlers will go through 6 stages. So each new data will perform a probability with each existing class, the final result is seen from the highest value of this calculation which is used to see the results of determiining the nut.risio.nal th.e te.sted child.ren. Deter.mi.ning th.e nutritional status o. .f. toddlers by inputting age, sex, weight, height with three data on the nutrition categories of children under five, namely thin, normal, fat. System testing was carried out with 83 data on toddlers at Posyandu Anggrek Putih Dsn Seblak, Kwaron Village, each of which 53 toddler data as training data and 30 other toddler data were used for data testing with an accuracy value of 86.66%. Keywords: Determination of Toddler Nutritional Status, Classification, Naive Bayes Classifier
Co-Authors Aisha, Dita ANITA ANDRIANI, ANITA Bagus Pratama Putra, Dharma Bastian Nursyahputra, Andhika Chasanah, Nidhaul Faizah, Arbiati Hartono, Sherly Indana Lazulfa, Indana Irfanto, Feri Kistofer , Terdy Lailiyah, Ami mahmudi, imam Mujianto, Ahmad Heru Puspitasari, Refandah Rendy Harenza, Aderio Umi Rahmawati, Evis Uswatun Khasanah, Siti Valen Zidana Erlita Wiratsongko, Radityo