Article Per Year (5 Year)
p-Index From 2021 - 2026
4.116
P-Index
This Author published in this journals
All Journal Jurnal Pendidikan Indonesia Jurnal Informatika dan Teknik Elektro Terapan Jurnal Teknologi Elektro Creative Information Technology Journal INTEGER: Journal of Information Technology Pendas : Jurnah Ilmiah Pendidikan Dasar Best Journal (Biology Education, Sains and Technology) Jurnal Computer Science and Information Technology (CoSciTech) Journal of Soft Computing Exploration Jurnal Informatika Terpadu International Journal of Community Service Journal of Social Research Journal of Innovation Research and Knowledge Jurnal Riset Rumpun Ilmu Teknik (JURRITEK) Jurnal Riset Rumpun Ilmu Kesehatan (JURRIKES) Jurnal Ilmiah Teknik Informatika dan Komunikasi Innovative: Journal Of Social Science Research Indonesian Vocational Research Journal IRA Jurnal Pengabdian Kepada Masyarakat Jurnal Penelitian Teknologi Informasi dan Sains Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK) Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Dedikasi Nusantara IJENSET Jurnal Teknik Informatika dan Teknologi Informasi
Mufti Ari Bianto
Universitas Muhammadiyah Lamongan
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 30 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 30 Documents
Search

 1   2   3 
Sistem Stok Barang Berbasis Rfm Dengan Mempertimbangkan Kebiasaan Konsumen Dan Barang Slow-Moving Di Usaha Konter Wijayanti, Lusi Salsabilla; Bianto, Mufti Ari; Zamani, Sevian Nadi; A, Dwi Putra
Innovative: Journal Of Social Science Research Vol. 5 No. 4 (2025): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v5i4.20978

Abstract

Mobile phone accessory stores, particularly those selling accessories and spare parts, face challenges in managing stock accumulation, especially with slow-moving items that are rarely purchased. This study aims to implement the RFM (Recency, Frequency, Monetary) method to segment customers based on their transaction behavior and relate it to product movement. Through this analysis, store owners can identify which products are fast-moving or slow-moving, and which customers actively contribute to inventory turnover. The segmentation results support better decision-making in promotional strategies, restocking the right products, and managing discounts for rarely sold items. This research shows that the RFM approach is not only useful for customer management, but also effective in enabling a more adaptive and efficient inventory management system.
Recommendation Implementation of a Digital Book Recommendation System Using Item-Based Collaborative Filtering in a University Library Application.: Item-Based Collaborative Filtering, recommendation system, digital library, Pearson correlation, MAE. Mutsna, Mutsna; Mufti Ari Bianto; M. Cahyo Kriswantoro
Computer Science and Information Technology Vol 6 No 2 (2025): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v6i2.10011

Abstract

This study implements the Item-Based Collaborative Filtering (IBCF) method for a digital book recommendation system within a web-based library application. The system accommodates two user types (administrator and student) with features for managing physical/digital books, barcode-based borrowing, and ebook rating functionality. The similarity matrix was calculated using Pearson Correlation based on student ratings, with predictions evaluated via Mean Absolute Error (MAE) to measure accuracy. Evaluation results show an MAE of [your MAE value], indicating a low level of prediction error. Book recommendations are displayed on the student dashboard based on highest ratings, enhancing user experience in reading material selection. This implementation demonstrates IBCF's effectiveness for limited datasets within a university library context.
A Car Booking Method Using K-Means : Case Study: Car Rental Tsalits Wildan Hamid; Mufti Ari Bianto
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 4 (2025): November: Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i3.1055

Abstract

This study discusses the application of the K-Means Clustering algorithm in the car rental ordering system. The objective is to help group booking data based on certain patterns such as car type, booking frequency, and rental duration. The clustering results are expected to improve service efficiency and help companies better understand customer preferences. The research was conducted using historical car rental booking data from a rental company. The results show that the K-Means method can successfully cluster booking data into several useful clusters for business decision-making. This extended paper also explores theoretical concepts of clustering, related studies, limitations of the method, and potential future enhancements such as integrating predictive analytics. It highlights the importance of transforming large volumes of raw booking data into actionable business intelligence to support marketing strategies, fleet management, and customer segmentation.  
Implementasi Sistem Pemesanan Hotel Menggunakan Algoritma Haversine untuk Optimalisasi Rekomendasi Lokasi Adhani, Hamka Lukmanul Hakim; Bianto, Mufti Ari; Pratama, Alif Nanda; Hidayah, Septina Alfiani
Jurnal Informatika Terpadu Vol 11 No 2 (2025): September, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jit.v11i2.2030

Abstract

A location-based lodging recommendation system helps users find nearby hotels efficiently through a web-based platform. The system utilizes the Haversine algorithm to calculate the distance between the user's location and the hotel by automatically retrieving coordinates via the Geolocation API. Calculated distances are compared with hotel data stored in a MySQL database, and the results are displayed on a web interface integrated with the Google Maps API. Testing was conducted on six hotels with distances ranging from 6.73 km to 23.97 km, and results were compared with Google Maps estimates. The system achieved an average distance difference of 0.0183 km, with an accuracy rate of 99.83%. These findings indicate that the Haversine algorithm provides highly accurate distance estimations and is reliable for location-based hotel recommendation systems.
Integrasi Metode Hybrid Recommendation dan Random Forest Regression untuk Optimasi Prediksi Durasi Menginap pada Sistem Pemesanan Kos Berbasis Web Mufti Ari Bianto; Hanif Azhar Ramadhan; Ardian Hudi Ramadhani; Tsalits Wildan Hamid
JURAL RISET RUMPUN ILMU TEKNIK Vol. 4 No. 3 (2025): Desember : Jurnal Riset Rumpun Ilmu Teknik
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurritek.v4i3.6591

Abstract

This study proposes the integration of a Hybrid Recommendation method (combining Content-Based and Collaborative Filtering) with Random Forest Regression (RFR) to improve the accuracy of stay duration prediction in web-based boarding house booking systems. The main issue in online boarding booking systems is the inaccuracy of predicting user stay duration, affecting room allocation efficiency and customer satisfaction. The dataset was sourced from the hotel sector due to its attribute similarities and data validity. The research process includes data preprocessing (missing value imputation, normalization, and one-hot encoding), temporal and contextual feature engineering, hybrid recommendation system construction with CBF and CF score weighting, and RFR model training optimized through Grid Search and 10-fold cross-validation. Evaluation was conducted using MAE, RMSE, R² metrics, as well as recommendation metrics such as Precision@5, Recall@5, and Mean Reciprocal Rank (MRR). Results show that this integrated model achieved an R² of 0.7239 and an MAE of 1.0537 days, as well as a Precision@5 of 0.9636. This integration proves effective in improving prediction accuracy and recommendation relevance and contributes to the development of AI-based intelligent systems in the accommodation domain.
Sistem Diagnostik Mata Digital berbasis Optoscope untuk Deteksi Dini Gangguan Penglihatan secara Akurat dan Efisien Mufti Ari Bianto; Mohammad Huda Adi Sanjaya; Yuni Furoida Maknuna; Adam Rizky Al’insani
JURNAL RISET RUMPUN ILMU KESEHATAN Vol. 4 No. 3 (2025): Desember : Jurnal Riset Rumpun Ilmu Kesehatan
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurrikes.v4i3.6586

Abstract

The development of digital technology has had a significant impact on the health sector, including eye examination services. This study discusses the development and implementation of a Digital Optoscope-based Eye Diagnostic application designed using a web platform (HTML). This application provides two main features: visual acuity testing and astigmatism testing, which can be accessed independently by users through digital devices such as laptops, tablets, or mobile phones. Users only need to follow the visual instructions presented interactively on the screen, then perform the test according to the procedure. The testing method is carried out by displaying font size settings according to the Snellen chart standard and radial astigmatism patterns. The results of each test session are automatically recorded and can be saved for further analysis. In addition, users can perform repeated tests to improve the accuracy of self-diagnosis, and the system will provide lens type recommendations based on the measurement results obtained. The trial results show that this application is able to provide convenience, efficiency, and initial accuracy in the process of examining vision disorders. This is very useful, especially for people in remote areas or with limited access to professional eye health services. Thus, the Digital Optoscope-based Eye Diagnostic application has the potential to be an innovative solution for the early digital detection of vision disorders. This study recommends further development, particularly in clinical validation, testing on a wider sample size, and integration with electronic medical record systems to enhance its benefits in comprehensive public health services. Furthermore, collaboration with medical professionals is crucial to ensure diagnostic accuracy. With this approach, the app is expected to become a reliable tool for continuous eye health monitoring.
Application Of The Simple Moving Average Method for Farming Fish Price Forecasting Systems Mubaarok, Ahmad Husni; Bianto, Mufti Ari; Saputra, Bagus Dwi
Indonesian Journal of Engineering, Science and Technology Vol. 1 No. 1 (2024): VOL. 01 NO. 01 (JUNE 2024)
Publisher : Universitas Muhammadiyah Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38040/ijenset.v1i1.713

Abstract

Price is one of the important things that needs to be considered as a determining factor for profit or loss on product sales as a result of price fluctuations which are very difficult to control. Price fluctuations are caused by many factors including weather, stock availability, demand and others. One of the steps to overcome the problem of price fluctuations is to forecast the entry price of fish. Forecasting is the art or science of predicting future events using past data. The purpose of this study is to apply the simple moving average method to estimate the price of farmed fish. The simple moving average method uses a number of actual demand data to generate forecast values for future requests. This method has two special properties, namely to make forecasts that require historical data over a certain period of time, the longer the moving average, the smoother the moving average will be. This study uses data on fish prices (milkfish and tilapia) daily for January 2023. The results show that the Simple moving average produces a very accurate forecast with a MAPE percentage for milkfish of 2% and tilapia of 1.97%.   Keywords – Forecasting; Price; Simple Moving Average.
Clean Water Recommendation System Based on Water Quality with Turbidity and TDS (Total Dissolve Solid) Sensors Based on Internet of Things (IOT) Arbiansyah, Lutfi; Bianto, Mufti Ari; Ardiansyah, Heri
Indonesian Journal of Engineering, Science and Technology Vol. 1 No. 2 (2024): VOL. 01 NO. 02 (DECEMBER 2024)
Publisher : Universitas Muhammadiyah Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38040/ijenset.v1i2.1014

Abstract

Residents of Khayangan Residence Cepu typically use water from natural sources such as rivers, lakes, and wells, often unaware of the potential dangers posed by contaminated water. To address this, a detection system is proposed to monitor and provide real-time information on water quality using Turbidity and Total Dissolved Solids (TDS) sensors. The system is developed using the Waterfall methodology, which ensures a structured and systematic approach, with each stage of development completed before proceeding to the next. This minimizes errors and enhances the accuracy of the final system. The IoT-based system utilizes Turbidity and TDS sensors connected to an ESP32 microcontroller, which processes data every 3 seconds and displays it on a website. The system measures water quality, with recorded values of PPM at 276, TDS at 0.34, and Turbidity at 16.08. This real-time monitoring system provides a straightforward process for assessing water quality in the housing complex, ensuring that residents have access to safe and clean water. The aim is to empower residents to make informed decisions about water use, thereby enhancing efficiency and safety in daily water consumption. Keywords-  ESP32; Turbidity Sensor; TDS Sensor.
The Monitoring System for Water Quality Based on The Internet of Things (IoT) and Uses A TDS Sensor Zafi, Ali; Saputra, Bagus Dwi; Bianto, Mufti Ari
Indonesian Journal of Engineering, Science and Technology Vol. 1 No. 2 (2024): VOL. 01 NO. 02 (DECEMBER 2024)
Publisher : Universitas Muhammadiyah Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38040/ijenset.v1i2.1015

Abstract

This research focuses on designing an Internet of Things (IoT)-based water quality monitoring system for aquaculture ponds, utilizing Total Dissolved Solids (TDS) sensors and the ESP32 microcontroller. The system is developed to monitor water quality in real-time by measuring the concentration of dissolved solids in the pond water. Data from the TDS sensor is collected by the ESP32 microcontroller, which is connected to a WiFi network and subsequently transmitted to the cloud, where it is displayed on a website. The study shows that the system can categorize water quality into three statuses: safe, alert, and poor. These categories are based on predefined TDS threshold values. Daily collected data is processed to provide accurate information on water quality status. This system enables continuous monitoring, facilitating pond management. Users can easily access data through a web page that presents information in an easily understandable format. The research demonstrates the effectiveness of using the ESP32 microcontroller and TDS sensors in an IoT-based monitoring application, as well as the system's capability to provide clear and timely indications of water quality status. Keywords--  ESP32 Microcontroller; Total Dissolved Solids (TDS); Water Quality Sensor  
Decision Support System for Prioritizing Road Repairs with Simple Additive Weighting Method Ramadhan, Bayu Putra; Ardiansyah, Heri; Bianto, Mufti Ari; Saputra, Bagus Dwi; Widodo, Aris
Indonesian Journal of Engineering, Science and Technology Vol. 2 No. 1 (2025): VOL. 02 NO. 01 (JUNE 2025)
Publisher : Universitas Muhammadiyah Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38040/ijenset.v2i1.1040

Abstract

The Decision Support System (DSS) is a technology utilized to address the issue of determining road improvement priorities. In this context, DSS will be used to integrate various road assessment criteria and provide recommendations for repair priorities based on proven methods. The aim of this study is to design a decision support system for prioritizing road repairs in Lamongan Regency and to implement this system effectively. The Simple Additive Weighting (SAW) method was chosen for its ability to handle multiple criteria and provide measurable evaluations of alternative solutions. The criteria used in this research include road condition, traffic volume, and socio-economic impact. The results of this system demonstrate a prioritization order for road repairs that can assist in more efficient decision-making, focusing on the most urgent needs. This research is expected to contribute to improving the efficiency of road infrastructure management and to aid authorities in the planning and execution of road repairs. Keywords-- Decision Support System; Road Repair Priority; Simple Additive Weighting.
Co-Authors A, Dwi Putra Adam Azzamul Husni Huda Adam Rizky Al’insani Adhani, Hamka Lukmanul Hakim AF Suryaning Ati MZ Afifah Agustin Ahmad Abdullah Fahmi Akbar Ramadhani Alfina Wijayanti Wibowo Angela Tiara Marsningrum Arbiansyah, Lutfi Ardian Hudi Ramadhani Aris Widodo Badriyatul Musyarofah Bagus Dwi Jauhari Bagus Dwi Saputra Bufa Al badi Ecki Salma Hapsari Eko Handoyo Eva Laili Wijayanti Fiqrul Labib Abdullah Hanif Azhar Ramadhan Hanif Azhar Ramadhan Heri Ardiansyah Hery Ardiansyah Hidayah, Septina Alfiani Ihsan, M. Nurul Khairul Umam Kusrini M. Cahyo Kriswantoro M. Rosyibad Rizein Mala Rosa Aprillya Moch. Ryan Nurfebrianto Mohammad Hisyam Romadhon Mohammad Huda Adi Sanjaya Mubaarok, Ahmad Husni Muhammad Syaifuddin Alamsyah Mutsna, Mutsna Pratama, Alif Nanda Ramadhan, Bayu Putra Rifki Noor Rohman Rofiatun Solekha Ryky Ardiansyah Salasun Nisah SAPUTRA, BAGUS DWI Setiyowati, Putri Ayu Ika Sholikha, Hidayatin Sudarmawan Sudarmawan Tsalits Wildan Hamid Uswatun Chasanah Vico Tegar Rawo Wijoyo Widuri Octavianunisa Wijayanti, Lusi Salsabilla Yuni Furoida Maknuna Zafi, Ali Zahrotun Nisa Zamani, Sevian Nadi Zufar Faiil Haq Zuhrotun Nisa