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All Journal PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Teknik Komputer AMIK BSI JITK (Jurnal Ilmu Pengetahuan dan Komputer) JUTIM (Jurnal Teknik Informatika Musirawas) Jurnal Informatika dan Rekayasa Elektronik Specta Journal of Technology Infotek : Jurnal Informatika dan Teknologi International Journal of Social and Management Studies (IJOSMAS) SPEED - Sentra Penelitian Engineering dan Edukasi Paradigma International Journal of Accounting, Management, Economics and Social Sciences (IJAMESC) INTERACTION: Jurnal Pendidikan Bahasa
Rohimah, Luthfia
Universitas Bina Sarana Informatika
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Model Hibrida K-Nearest Neighbors Berbasis Genethic Algorithm untuk Prediksi Penyakit Ginjal Kronis Rukiastiandari, Sinta; Rohimah, Luthfia; Aprillia, Aprillia; Chodidjah, Chodidjah; Mutia, Fara
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 1 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i1.27918

Abstract

Chronic Kidney Disease, which is often abbreviated as PGK, is a serious disease that is of major concern to society and the medical world. This disease can cause various serious complications if not treated properly and early. Therefore, accurate prediction of CKD is very important to support early intervention that can slow disease progression, prevent further complications, and increase the patient's chances of recovery. This research aims to increase the accuracy of PGK predictions by developing a hybrid model that combines the K-Nearest Neighbors (KNN) algorithm with optimization using the Genetic Algorithm (GA). In this approach, the KNN algorithm is used to build a prediction model, while GA acts as an optimization tool that improves model performance. The effectiveness of the optimized model is evaluated using key metrics such as accuracy, precision, recall, and area under the curve (AUC). The results show a significant increase in performance, with accuracy increasing by 17.75%, precision increasing by 23.84%, and recall increasing by 5.34%. This research makes an important contribution to the development of data mining technology for clinical applications and opens up opportunities for further improvements in the future in increasing the prediction accuracy of chronic diseases such as CKD
HOW PLATFORM FEATURES DRIVE CONSUMER BEHAVIOR ON OMNICHANNEL IN INDONESIA Sinta Rukiastiandari; Dede Suleman; Lilik Yuliawati; Fara Mutia; Luthfia Rohimah; Aprillia
International Journal of Accounting, Management, Economics and Social Sciences (IJAMESC) Vol. 1 No. 5 (2023): October
Publisher : ZILLZELL MEDIA PRIMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61990/ijamesc.v1i5.87

Abstract

This study investigates the relationship between platform features, customer engagement, satisfaction, purchase and repurchase intentions, and customer types in omnichannel retail. A survey of 250 participants utilized an online questionnaire, analyzed with statistical methods. Results show that platform convenience and advanced features drive satisfaction, purchase, and repurchase intentions. Impact on customer engagement varies by customer type. Ease of use indirectly affects satisfaction, purchase, and repurchase via engagement and customer type. The research underscores considering customer type when assessing ease of use and design impact on outcomes. It reveals intricate relationships, surpassing prior research by illustrating how platform features affect diverse customer engagement. Ease of use indirectly influences loyalty via engagement and customer type. This underscores a multifaceted loyalty formation. Businesses must factor engagement and customer type in platform refinement for target audience needs. Study underscores understanding platform features, engagement, and loyalty interplay for enhanced customer experiences and business success. It establishes a foundation for future research and practical omnichannel retail improvements.
Predicting Graduation Outcomes: Decision Tree Model Enhanced with Genetic Algorithm Rukiastiandari, Sinta; Rohimah, Luthfia; Aprillia, Aprillia; Mutia, Fara
Paradigma - Jurnal Komputer dan Informatika Vol. 26 No. 1 (2024): March 2024 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v26i1.3165

Abstract

This research aims to improve the accuracy of predicting student permit results in the digital era by utilizing machine learning techniques. The main focus is the use of a Decision Tree (DT) model optimized with a Genetic Algorithm (GA) to overcome the limitations of accuracy and testing of conventional methods. This research began with collecting student academic data, followed by preprocessing to eliminate incompleteness and organize the data format. The DT model is then built and optimized with GA, which is inspired by biological evolutionary processes to improve feature selection and parameter tuning. The results show a significant increase in prediction accuracy, from 86.19% to 87.68%, and an increase in the Area Under Curve (AUC) value from 0.755% to 0.788%. This research not only proves the effectiveness of GA integration in improving DT models, but also paves the way for the application of evolutionary techniques in educational data analysis and other fields. The main contributions of this research include the development of more accurate prediction models and practical applications in educational contexts, with the hope of assisting educational institutions in making more informed decisions for their students.
PREDIKSI STATUS AKADEMIK MAHASISWA BERDASARKAN DATA PEMBAYARAN DENGAN NAIVE BAYES DAN PARTICLE SWARM OPTIMIZATION Rukiastiandari, Sinta; Rohimah, Luthfia; Mutia, Fara; Aprillia; Chodidjah, Chodidjah
Jurnal Informatika dan Rekayasa Elektronik Vol. 8 No. 2 (2025): JIRE November 2025
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v8i2.1756

Abstract

Pendidikan tinggi di Indonesia menghadapi tantangan dalam pengelolaan pembayaran mahasiswa, di mana keterlambatan dapat berdampak pada status akademik, termasuk risiko cuti atau pengunduran diri. Penelitian ini bertujuan mengembangkan model prediksi status akademik berbasis data pembayaran kuliah dengan metode Naive Bayes (NB) yang dioptimasi menggunakan Particle Swarm Optimization (PSO). Dataset berjumlah 15.697 record mahasiswa yang telah melalui pra-pemrosesan, termasuk penanganan nilai hilang dan pengkodean atribut kategorikal. Hasil menunjukkan bahwa model NB menghasilkan akurasi 98,83%, precision 98,21%, recall 65,09%, dan AUC 0,905. Optimasi dengan PSO meningkatkan recall menjadi 65,13% dan AUC menjadi 0,907, sementara akurasi dan precision tetap stabil. Analisis fitur mengindikasikan bahwa Jenis Kelamin, Jurusan SLTA, dan Kuliah Sambil Bekerja merupakan atribut paling berpengaruh, sedangkan Pekerjaan Ayah relatif kurang signifikan. Temuan ini menegaskan potensi NB-PSO sebagai pendekatan prediktif untuk mendukung pengelolaan administrasi akademik yang lebih efektif.
The Influence of Service Quality and Price on Alfamart Consumer Loyalty with Customer Satisfaction As Mediation Variables Herawaty, Mety Titin; Aprillia, Aprillia; Rahman, Aan; Rohimah, Luthfia; Taruna, Helmy Ivan; Styaningrum, Etik Dwi; Suleman, Dede
International Journal of Social and Management Studies Vol. 3 No. 2 (2022): International Journal of Social and Management Studies (IJOSMAS)
Publisher : IJOSMAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (544.63 KB) | DOI: 10.5555/ijosmas.v3i2.179

Abstract

This study aims to analyze the quality of service and price on consumer loyalty, with the variable customer satisfaction as a mediating variable. Data collected from 100 respondents of Alfamart minimarkets in Jakarta, Bogor, Depok, Tangerang and Bekasi. The distribution was carried out during December 2021, using the google form due to the pandemic conditions. The research method used is purposive sampling, namely people who shop at the Alfamart Minimarket in the last month and are willing to fill out the questionnaire that the researcher gave. The collected data were analyzed using Structural Equation Modeling with SmartPLS version 3.0 software. Hasil penelitian menunjukkan Service Quality has a positive and significant effect on Customer Satisfaction, Price has a positive and significant effect on Customer Satisfaction, Service Quality has a positive and significant effect on Customer Loyalty, Price has a no significant effect on Customer Loyalty, Customer Satisfaction has a no significant effect on Customer Loyalty, Customer satisfaction did not significantly mediate the service quality and price variables on consumer loyalty.
The Effect Of Product Quality And Promotion On Customer Purchase Decisions Of Pizza Hut Restaurant In The City Of Tangerang Selatan With Price As Intervening Variable Suleman, Dede; Saputra, Fendi; Sugiyah, Sugiyah; Aprillia, Aprillia; Martias, Andi; Rohimah, Luthfia; Herawaty, Mety Titin; Rulando, Refindo Pradikta
International Journal of Social and Management Studies Vol. 3 No. 6 (2022): International Journal of Social and Management Studies (IJOSMAS)
Publisher : IJOSMAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5555/ijosmas.v3i6.256

Abstract

This study aims to examine and examine the effect of product quality, promotion and price on purchasing decisions by Pizza Hut customers in South Tangerang City. This research is quantitative where data is obtained by giving Likert scale questionnaires to respondents who bought Pizza Hut products in the last three months in South Tangerang City. The data collection method used purposive sampling. From the questionnaires distributed online using the google form link, of the 96 respondents who filled out, only 94 data were eligible for further processing using the SmartPLS version 3.0 software. The results showed that product quality, promotion and price had a significant effect on purchasing decisions. price is not significant as a mediating variable on the effect of product quality on purchasing decisions, while on the effect of promotion on purchasing decisions, price becomes a significant mediating variable
Analysis of CSR Models in Improving English Recount Text Reading Skills in Karya Vocational High Schools Aprillia; Sinta Rukiastiandari; Fara Mutia; Luthfia Rohimah; Endang Sri Andayani
INTERACTION: Jurnal Pendidikan Bahasa Vol. 13 No. 1 (2026): INTERACTION: Jurnal Pendidikan Bahasa
Publisher : Program Studi Pendidikan Bahasa Inggris, Universitas Pendidikan Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36232/interactionjournal.v13i1.4892

Abstract

Reading comprehension is one of the essential skills in English language learning at the high school level at Pendidikan Karya Tangerang. Based on initial observations, it was found that reading comprehension skills, especially in recount texts, are still relatively low. This is characterized by difficulties in understanding the main ideas, detailed information, vocabulary, and the sequence of events in the text. This study aims to analyze the application of the Collaborative Strategic Reading (CSR) model in improving reading comprehension skills in English recount texts.This study used a pre-test and post-test control group design. The research sample consisted of 60 eleventh-grade students, divided into two groups: an experimental group (30 students) taught using the CSR model and a control group (30 students) taught using conventional learning methods. The results of the pre-test and post-test control showed a significant difference in reading comprehension ability between the experimental class (82,40) and the control class (72,10), indicating that the increase in scores in the experimental class was greater than in the control class. The N-Gain score for the experimental class was in the medium-high category (0,54), while the control class (0,28) was in the medium category.These findings indicate that the CSR model is effective in improving students' English recount text reading comprehension skills. This study is expected to serve as a reference for English teachers in implementing innovative and effective collaborative learning models
Optimization of Random Forest Prediction for Industrial Energy Consumption Using Genetic Algorithms Sartini Sartini; Luthfia Rohimah; Yana Iqbal Maulana; Supriatin Supriatin; Dewi Yuliandari
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 11 No. 1 (2023): March 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i1.5886

Abstract

Abstract Saving electrical energy consumption in industries is crucial; hence, the prediction of industrial energy consumption needs to be performed. The random forest method can be applied to steel industry data to predict energy consumption. The purpose of this prediction is to increase energy savings in industries and optimize the performance of the random forest method. The results of the random forest show that the algorithm can predict energy consumption in industries effectively; however, it needs further optimization to achieve better predictions. Therefore, the genetic algorithm method will be used to optimize the previous method. The optimization results indicate that it is successfully conducted in terms of accuracy and kappa level. This optimization is beneficial to society, especially industrial companies.
Classifying Half-Unemployment Levels in Indonesian Provinces: A K-Means Approach for Informed Policy Decisions Suhardjono Suhardjono; Hari Sugiarto; Dewi Yuliandari; Adjat Sudradjat; Luthfia Rohimah
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 11 No. 2 (2023): September 2023
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v11i2.7390

Abstract

Half-level unemployment refers to individuals who work part-time and are not fully employed. Increasing the half-poverty rate from year to year can lead to challenges in the lives of these individuals. The issue arising with the rise in the half-poverty rate is the government's difficulty in prioritizing areas that require intervention to address these problems. Consequently, an increase in the half-poverty rate can have adverse consequences. Therefore, it is necessary to categorize underemployment rate data obtained from public sources, specifically from data.go.id, using the widely recognized clustering method known as K-Means. The purpose of this categorization is to identify and classify provinces with a significant prevalence of half-poverty levels. This classification will assist the government in making informed decisions when addressing individuals who meet the half-poverty criteria. The results were obtained by grouping the data from the first to the eighteenth iteration into three categories: 'large' (C1), 'medium' (C2), and 'small' (C3) in terms of half-poverty levels. Group C1 comprises 17 provinces with a high half-poverty rate, while C2 includes only 2 provinces, and C3 covers 16 provinces with a significant half-poverty rate. Based on these findings, it is advisable for the Indonesian government to consider implementing policies aimed at reducing the poverty level by half. Priority should especially be given to the C1 group when creating employment opportunities for the province's residents
Co-Authors - UBSI, Aprillia Aan Rahman Adjat Sudradjat Amelia, Silvy Andi Martias Aprillia Aprillia Aprillia, Aprillia Chodidjah Chodidjah Dede Suleman Dewi Yuliandari Endang Sri Andayani Fara Mutia Fara Mutia Hari Sugiarto - UBSI Helmy Ivan Taruna Juarni Siregar Juarni Siregar Lilik Yuliawati Mety Titin Herawaty Muhammad Rizki Pradana Mutia, Fara Rikiwanto sinaga Rulando, Refindo Pradikta Saputra, Fendi Sartini Sartini Silvy amelia Sinta Rukiastiandari Styaningrum, Etik Dwi Sugiyah Sugiyah, Sugiyah Suhardjono S Supriatin Supriatin Yana Iqbal Maulana Yoraeni, Ani