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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Sebatik JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) Aptisi Transactions on Technopreneurship (ATT) METIK JURNAL TEPIAN Buletin Poltanesa Informatika Wicida Journal of Pedagogy and Education Science TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi BEduManageRs Journal : Borneo Educational Management and Research Journal
Heny Pratiwi
Teknik Informatika, STMIK Widya Cipta Dharma
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Social Sciences Other

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Journal : Buletin Poltanesa

 1 
Design of a Web-Based Management Application for Jamu Bu Tri Shop with Sales Analysis Features Daru Caraka; Heny Pratiwi; Vilianty Rafida
Poltanesa Vol 26 No 2 (2025): December 2025
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v26i2.3555

Abstract

Digital transformation that comes from information technology has been the main game changer for businesses of all sectors. Even the least expected ones, like micro, small and medium enterprises that are MSMEs like herbal medicine shops in Indonesia, have been impacted. Jamu Bu Tri Shop is using a manual management system which leads to problems such as inaccurate data recording, lack of real-time product tracking, slow transaction processes, and difficult financial reporting. This study is about a web-based store management application with sales analysis features through the use of the Rapid Application Development methodology. Observation, interview of the owner and employees of the shop and documentation were the data collection methods. The system design was done through the Unified Modeling Language diagrams like Use Case Diagrams, Activity Diagrams, and Class Diagrams. This application can automate product management, sales transactions, category and supplier management, expense recording, and integrated report generation. The main novelty is an analytical dashboard that provides the interaction of data visualization through the line chart, bar graph, and donut chart. Black Box testing checked all system functions with 100% accuracy in eight main modules and the System Usability Scale evaluation gave a score of 91.67 with Grade A. The implementation results showed that there were considerable improvements in the operation: transaction recording time was reduced by 90%, monthly report preparation was enhanced by 98%, product stock checking was improved by 94%, and best-selling product identification was sped up by 99.7%.
Comparison Analysis of K-Nearest Neighbor and Naïve Bayes Methods in Classifying Academic Reference Books Chandra Panca Wibawa; Heny Pratiwi; Andi Yusika Rangan
Poltanesa Vol 26 No 2 (2025): December 2025
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v26i2.3556

Abstract

This study compares the performance of the K-Nearest Neighbor (KNN) and Multinomial Naïve Bayes (MNB) algorithms in classifying academic reference books based on their titles within the STMIK Widya Cipta Dharma library system. A dataset consisting of 2,153 cleaned book records was processed using the Knowledge Discovery in Databases (KDD) framework, including data selection, preprocessing, transformation, and classification. Book titles were normalized and transformed into numerical features using TF-IDF with unigram and bigram extraction. The dataset was split using a 75%–25% ratio, resulting in 1,614 training samples and 539 testing samples. Experimental results show that the KNN classifier achieves an accuracy of 72.72%, outperforming Multinomial Naïve Bayes with an accuracy of 62.70%. Confusion matrix analysis shows that KNN correctly classifies more book titles across categories. The superior performance of KNN is attributed to the sparse and short-text nature of book titles, which benefits distance-based similarity. These findings highlight the potential of machine-learning-based automated classification to improve cataloging and information retrieval in academic libraries.
Developing a Calorie Requirement Application Based on a BMI Calculator for Android Using User-Centered Design (UCD) Fadjri Astra Ryan Sinurat; Heny Pratiwi; Ahmad Fajri
Poltanesa Vol 26 No 2 (2025): December 2025
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v26i2.3557

Abstract

This study aims to develop an Android-based calorie requirement application using the User-Centered Design (UCD) approach and to evaluate its usability through the System Usability Scale (SUS). The application calculates individualized calorie needs using the Basal Metabolic Rate (BMR) and Total Daily Energy Expenditure (TDEE) formulas, while the Body Mass Index (BMI) feature functions only as a weight classification tool to support user awareness. Healthcare workers at Puskesmas Loa Ipuh were involved throughout the research, concept development, design, prototyping, and testing stages to ensure that the system aligns with real user needs. The UCD process used in this study consists of five stages: research, concept, design, development, and testing. The final application was built using the Kotlin in Android Studio and includes features such as calorie calculation, BMI calorie calculates, food recommendations, and daily nutritional tracking. Usability evaluation with the System Usability Scale involved 23 respondents and resulted in an average score of 82.60, which falls into the “excellent” category, indicating that the application is easy to use, efficient, and well accepted by target users. These findings demonstrate that integrating UCD with validated calorie estimation formulas can produce a functional and user-centered mobile application that supports users in understanding their daily calorie needs and improves accessibility to basic nutritional information.
Sentiment Analysis Using the Naïve Bayes Method to Improve E-Commerce Customer Satisfaction at the PedagangAksesoris Store Bai' Fathur Rayhan; Heny Pratiwi; Muhammad Fahmi
Poltanesa Vol 26 No 2 (2025): December 2025
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid development of the e-commerce sector in Indonesia has made customer feedback a very important source of information in assessing the quality of goods and services. However, with so many reviews available, the manual assessment process often becomes complicated. The purpose of this study is to analyze customer sentiment towards PedagangAksesoris store on the Shopee platform using the Naïve Bayes Classifier method to identify positive and negative opinions that can help improve customer satisfaction. The data for this study was collected through web scraping of Shopee user reviews, followed by a preprocessing stage that included cleaning, filtering, removing affixes, and separating words. The data was then divided into training data and testing data to train and test the model. The Naïve Bayes method was applied by calculating word probabilities using Laplace smoothing, while model performance was evaluated using a Confusion Matrix through the RapidMiner application. The results of this study show that the Naïve Bayes model can classify customer reviews with a high degree of accuracy, with precision reaching 100% for the negative category and 80% for the positive category, as well as recall of 87.5% and 100%. These findings confirm that the Naïve Bayes method is an effective and efficient way to perform text-based sentiment analysis on reviews in e-commerce. The results of this sentiment analysis can be used as a basis for strategic decision-making by businesses to improve product quality, services, and customer satisfaction.  
Co-Authors Ahmad Abul Khair Ahmad Fajri Ahmad Rofiq Hakim Amelia Yusnita Ananta Putra, Resifa Andi Yusika Rangan Anggra Prima Arsita Ashari Ramadani Azahari Azahari, Azahari Bai' Fathur Rayhan Chandra Panca Wibawa Dana Aulia Rahman Daru Caraka Dendy Kurniawan Dessy Purnamasari Ekawati, Hanifah Fadjri Astra Ryan Sinurat Ita Arfyanti Jundro Daud Hasiholan Loho, Atventitus Etwin M Yuditia Arfiyanto T Nassa M. Irwan Ukkas Irwan Ukkas Ukkas Muhammad Fachri Sanjaya Muhammad Fahmi Muhammad Ibnu Sa'ad Muhammad Ibnu Saad Saad Muhammad Rega Praduana Nursobah, Nursobah NURUL HIKMAH Pahrudin, Pajar Pitrasacha Adytia Putra, Muhammad Sadam Saktia Putra, Resifa Ananta Putri Wulandari SA'AD, MUHAMMAD IBNU Salmon Salmon Sarifmata Purnomo Shinta Palupi Susi Salviati Syamsuddin Mallala