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All Journal MUST: Journal of Mathematics Education, Science and Technology Martabe : Jurnal Pengabdian Kepada Masyarakat Progresif: Jurnal Ilmiah Komputer Jurnal Teknologi Dan Sistem Informasi Bisnis Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Jurnal ELTEK Jurnal Ilmiah Research Student JURNAL ILMIAH PENELITIAN MAHASISWA Jurnal ELTEK Dinamis: Jurnal Pengabdian Kepada Masyarakat Taawun: Jurnal Pengabdian kepada Masyarakat Inovate : Jurnal Ilmiah Inovasi Teknologi Informasi JUTECHSY: Journal of Technology and Information System
ANITA ANDRIANI, ANITA
Universitas Hasyim Asyari
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Social Sciences Other

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Implementasi Algoritma FP Growth Untuk Menganalisa Pola Pembelian Barang (studi kasus : Koperasi) Sabila K.S., Nella; Sujatmiko, Bambang; Andriani, Anita
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.v6i2.3173

Abstract

Analyzing piles of sales transaction data turns out to be able to produce information, one of which can take a recommendation and layout decisions of goods such as arranging goods according to association patterns, doing discount or cheap redemption prices on products that are less desirable based on the results of the association pattern, and information on goods that are not in demand. less desirable according to association rules. The association pattern has several solutions, one of which is using the fp growth algorithm. The purpose of using the fp growth algorithm is to find out frequent itemset data sets, in this study the authors apply the fp growth algorithm and association rules to cooperative data for the 1 day period of 2019. The results of this study are to produce applications that can make it easier for cooperatives to take A decision uses 20 sample data to look for association rules and FP growth, which can analyze consumer habits in making purchases, with an average percentage of support values of 9.09% and a confidence value of 100% Keywords: Data Mining, Fp Growth, Association rules, recommendations
Implementasi Algoritma Apriori Untuk Menentukan Strategi Pemasaran Bilqis Ismail Putri, Tiara; Sujatmiko, Bambang; Andriani, Anita
Inovate Vol 7 No 1 (2022): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v7i1.3680

Abstract

Store X is retail that provide a variety of toys for girls and boys. Every day the sales transaction data Store X will definitely increase and accumulate. So that data does not accumulate it is good can be used to know the habits of the buyer or of buyer behavior of goods purchased. How to search the goods sold simultaneously can use the data mining methods, which is a technique to analyze large-sized data by finding relationships among the data or the search combination and rule. The search for a combination is done with the process of merging (join) and pruning (prune) items called apriori algorithm. This research resulted in a website-based system by testing data sales transactions as many as 30 data a memorandum of the transaction with a minimum support of 35% and minimum confidence of 75%. So as to form one rule, namely, if buy a Meja Belajar K then will buy a Kreatif Block Tas with the value of the support 36.67% and the value of the confidence 78.57%. Keywords : Association, Apriori Algorithm, The Transaction Data, Sales
Klasifikasi Komentar Publik Dalam Pemilihan Umum Presiden 2024 Dengan Menggunakan Metode Naive Bayes: Studi Kasus Indentifikasi Haters Dan Non-Haters Imania, Dina; Andriani, Anita; Ali, Mahrus
Inovate Vol 8 No 1 (2023): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v8i1.5096

Abstract

Indonesia is one of the countries that adheres to a democratic system. The democratic system of governmentprioritizes the people. So that when the election of the people's representatives is carried out, the people havethe highest right to go through elections that take place freely. In 2024, the Indonesian presidential electionwill be held. Every moment of the presidential election or presidential general election, there are manyopinions from the public about the rumored presidential candidate. However, in practice, there are manynegative comments that are "hate speech," which can trigger social conflict and damage the politicalenvironment. This research aims to build a classification model of public comments into "haters" and "non-haters" categories in Indonesian using the Naïve Bayes algorithm. This research uses data totaling 1000, withdetails of training data of 800 and test data of 200. With the stages of data collection, data pre-processing,classification with Naïve Bayes, Evaluation, and Deployment. The results obtained an accuracy value of83.5%, a precision value of 82%, and a recall value of 90%.Keywords: Presidential Election; Classification; Naive Bayes.
PENERAPAN METODE VIKOR DALAM SELEKSI PEMBERIAN REWARD PADA RESELLER CAN BEAUTY JOMBANG BERBASIS WEBSITE Fajriyatus Sa’adah , Thulu’ul; Lazulfa , Indana; Andriani , Anita
Inovate Vol 8 No 2 (2024): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v8i2.6166

Abstract

Can Beauty is one of the businesses engaged in beauty in skin care. The provision of rewards to resellers is still seen from the success of sales achievement targets and there has been no assessment based on other supporting criteria. In addition, the selection process has not used a computerized system or by being directly selected by the Owner. From these problems, a decision support system is needed to solve the problem. The VIKOR method was chosen for its ability to classify and compromise existing alternatives. Therefore, this method is considered very effective when choosing in the selection of rewards to resellers. The VIKOR method is a simple rating method and can be used to choose from several criteria to get accurate results. By applying the VIKOR method, it is expected to be able to produce more accurate and objective output in the selection process of giving rewards to Can Beauty Jombang resellers. The calculation procedure for the VIKOR method in this system is based on predetermined standards, among others, the number of packages every 6 months, the type of transaction payment, the attitude of the reseller and the length of subscription. As well as weights for each criterion and obtained ranking results and taken the top 25 ranks. By using the VIKOR method, Can Beauty Jombang Distributors can determine which resellers are entitled to receive rewards. Keywords: Decision Support System, VIKOR, Reseller Reward
SISTEM PENDUKUNG KEPUTUSAN PELANGGARAN TATA TERTIB SANTRI MENGGUNAKAN METODE SMART Darmawan, Ricky; Andriani, Anita; Fatkhur Rizal, Muhammad; Widoyoningrum, Sri
Inovate Vol 9 No 1 (2024): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v9i1.7230

Abstract

Santri Pondok Pesantren Tebuireng 4 who violate the rules will get punishment to improve behavior and provide a deterrent effect, but the data collection of sanctions is still manual so that often repeated violations are not recorded. This research aims to design a system of decision assistance based on the SMART method to record the history of violations and determine the appropriate type of sanction automatically. This descriptive research with a quantitative approach was conducted at Pondok Pesantren Tebuireng 4, Riau, for four months. Data were collected through interviews and documentation, then used to design a system with the SMART method, which was implemented using UML for visualization and documentation of system design through diagrams such as flowcharts, use case diagrams, and activity diagrams. System testing at Pondok Pesantren Tebuireng 4 using Black Box Testing showed satisfactory results on various scenarios, such as the appearance of the login page, dynamic website functionality, report print page, and final score results. Testing was conducted with the pesantren Security Team, and the results confirmed that the SMART-based system can generate automated reports that facilitate efficient monitoring and enforcement of santri discipline. With this system, the process of selecting actions for violations becomes faster and more accurate, and allows users to easily add, edit, and delete data. Keywords: sanctions, students, SMART, decision support system.
IMPLEMENTASI NAIVE BAYES DALAM MEMPREDIKSI PENYAKIT DIABETES MELLITUS Qois Al’Ariq; Setyo Permadi, Ginanjar; Mashuri, Chamdan; Andriani, Anita
Inovate Vol 9 No 1 (2024): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v9i1.7267

Abstract

Diabetes mellitus is a illness that significantly affects the global population. This study explores theimplementation of Naive Bayes to predict diabetes mellitus. The problems faced include the complexity ofclinical datasets, feature diversity, and the need for accurate predictions. The proposed solution is to usethe Naive Bayes classification algorithm that utilizes a simple but strong assumption about featureindependence. The system is described with steps involving data pre-processing, dataset partitioning,Naive Bayes model training, and performance evaluation. The datasets used include age, gender, weight,HbA1C, fasting blood sugar. The results and testing show that the Naive Bayes model can provide fairlyaccurate predictions for diabetes mellitus, with performance assessed through evaluation metrics such as ,recall, accuracy, F1-score, and precision. In conclusion, the implementation of Naive Bayes is a fairlyeffective approach to predicting diabetes mellitus. In this study, The performance of the Naïve Bayesmethod is considered quite accurate, this is evidenced in the highest accuracy score of 85.71%. Despite itssimplicity, this algorithm can handle the complexity of the dataset and provide reliable predictions.Keywords: Diabetes Mellitus, Data Mining, Machine Learning, Classification, and Naïve Bayes.
IMPLEMENTASI METODE K-NEAREST NEIGHBOR (KNN) UNTUK MENENTUKAN PENERIMA BANTUAN SOSIAL (STUDI KASUS DESA PURISEMANDING JOMBANG) Agung Rizky Wijaya; Lazulfa, Indana; Muhammad Fatkhur Rizal; Andriani, Anita
Inovate Vol 9 No 1 (2024): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v9i1.7269

Abstract

The distribution of social assistance is one of the government's efforts to improve the welfare of the community,especially for low-income families. In the village of Purisemanding, the process of distributing Direct CashAssistance (BLT) often faces challenges in identifying the right recipients due to the manual data collectionmethods that are prone to errors and manipulation. This study aims to implement the K-Nearest Neighbor (KNN)method in the classification system for social assistance recipients to enhance the accuracy and efficiency ofBLT distribution. The study concludes that the use of the KNN method in the classification system for socialassistance recipients can improve objectivity in the process of determining recipients. This, in turn, affects theefficiency of the data collection and distribution process. This system is expected to be a practical solution forvillage governments in addressing the issues related to social assistance distribution that have been encounteredso far.Keywords: K-Nearest Neighbor, KNN, classification, social assistance, Purisemanding Village.
PENERAPAN SISTEM PENDUKUNG KEPUTUSAN SELEKSI PEGAWAI TERBAIK DENGAN METODE MFEP DI DINAS PENDIDIKAN KABUPATEN JOMBANG Rizky Permadi Syah; Setyo Permadi, Ginanjar; Andriani, Anita; Kistofer, Terdy
Inovate Vol 9 No 1 (2024): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v9i1.7278

Abstract

The Education and Culture Office of Jombang District implements a system of selecting the best employeesevery year to improve employee morale and reward their performance. Currently, the selection is donemanually, with subjective selection by the head of the office. This process takes a long time, and the resultsare subjective without standardized calculations. To improve accuracy and efficiency, a decision-makingsystem is needed that can assist in determining the best employees. One of the methods used is MFEP(Multi Factor Evaluation Process), with criteria such as work quality, responsibility, teamwork, discipline,and attendance. This method allows determining the weight of each attribute, ranking the suitability ofcriteria and alternatives, and ranking the best weighted data from several alternatives. Using the MFEPmethod and a sample of 36 employee data points, the highest value obtained is 8.8 and the lowest value is6.3. After calculation and ranking, a selection will be made to determine the best employee based on theranking value results.Keywords: best employee, selection method, decision-making system, ranking.
SISTEM PENJADWALAN BIMBINGAN BELAJAR BERBASIS WEB MENGGUNAKAN ALGORITMA GENETIKA Adinda Yuli Setiani; Ahmad Heru Mujianto; Andriani, Anita; Sri Widoyoningrum
Inovate Vol 9 No 1 (2024): September
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v9i1.7282

Abstract

Scheduling is the act, process, and method of scheduling or entering schedule data involves preparingactivities for a specific period while considering a number of variables, including classes, teachers, and time.The scheduling procedure at Omah Sinau Tutoring is still done manually. This causes inefficient use of timeand will affect the standard of education received by students. Omah Sinau Tutoring uses genetic algorithmsas an optimization technique to create schedules in order to overcome this problem. Many optimizationproblems can be solved with genetic algorithms. The benefits of analogies between the mechanisms ofnatural selection and the mechanisms of interbreeding, mutation, and other features inherent in the geneticalgorithm process serve as the basis for genetic algorithm solutions, rather than mathematical calculations.Genetic algorithms are capable of handling complex problems that are challenging to tackle by traditionalapproaches. The number of populations, generations, crosses, and mutations that can be handled by thegenetic algorithm to solve the problem by generating optimal scheduling and reducing the time needed tocreate the schedule so that the process of creating it becomes effective and efficient are the parameters used,based on the results of the tests conducted.Keywords: scheduling, genetic algorithm, tutoring.
IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR UNTUK KLASIFIKASI PENGAJUAN PINJAMAN UANG DI BMT MU’AMALAH SYARI’AH TEBUIRENG Listanto, Firgiawan; Lazulfa, Indana; Andriani, Anita; Sucipto , Hadi
Inovate Vol 9 No 2 (2025): Maret
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33752/inovate.v9i2.8872

Abstract

Technological developments have had a significant impact on the banking industry, especially in facilitating access to information and financial services. This research implements the K-Nearest Neighbor algorithm for classification of loan applications at BMT Mu'amalah Syari'ah Tebuireng. This research focuses on efficiency and accuracy in the loan application evaluation process which was previously carried out manually. The data used includes customer information collected through interviews and observations. After going through the data preprocessing and normalization stages, the K-NN algorithm is applied to classify loan applications based on parameters such as age, employment, monthly income, dependents, collateral, residence, and credit status. The implementation of this algorithm has been proven to be able to speed up the evaluation process and reduce the risk of errors in decision making, thereby providing significant benefits in improving service quality and operational efficiency at BMT Mu'amalah Syari'ah Tebuireng. Keywords: K-Nearest Neighbor, Classification, Loan Application, BMT Mu’amalah Syari’ah Tebuireng
Co-Authors Abda Abda Adi Susanto, Adi Susanto Adinda Yuli Setiani Agung Rizky Wijaya Arbiati Faizah ARIES DWI INDRIYANTI, ARIES Aries Dwi Indriyanti, Aries Dwi Arif Hidayatullah, Arif Arwin Dermawan, Dodik Augusta Jannatul Firdaus, Reza BAMBANG SUJATMIKO Bilqis Ismail Putri, Tiara Choirun Nizar, Reza Claudia Afaf Azzahrah Dedy Rahman Prehanto Delia Febrianti Dharma Bagus Pratama Putra F, Reza Augusta Jannatul Fajriyatus Sa’adah , Thulu’ul Farenda, Cika Fatkhur Rizal, Muhammad Firdaus, Reza Augusta Jannatul Firdaus, Reza Augusta Jannatul Ginanjar Setyo Permadi Heru Mujianto , Ahmad Husein Hanafiyah, Muhammad I Kadek Dwi Nuryana, I Iftitaahul Mufarrihah Iftitaahul Mufarrihah Imania, Dina Indriawan, Fani Islamiyah, Nadiatul istiqomah istiqomah Istiqomah Istiqomah Kadek Dwi Nuryana , I Karimatun Nisa', Lilis Kistofer, Terdy Laili, Elisa Nurul Lazulfa, Indana Libasut Taqwa , Nungqi Listanto, Firgiawan M. Aufa Alfis Syihab Mahrus Ali Mahrus Ali Mashuri, Chamdan Mufarrihah, Iftitaahul Muhammad Fatkhur Rizal Muhammad Hafidz Alfito Hakim Muhimmatul Mahmuda Mujianto, Ahmad Heru Nur Rohmah, Fitri Ovi Fitri Satriyati Qois Al’Ariq Reza Augusta J.F. Reza Augusta Jannatul Firdaus Ricky Darmawan Risca Setiawan Rizky Permadi Syah Sabila K.S., Nella Sri Widoyoningrum Sucipto , Hadi Tanhella Zein Vitadiar Uswatun Khasanah, Siti Wahyu Saputro, Angga Widoyoningrum, Sri Widoyoningrum, Sri Widoyoningrum