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Implementation of Multi Objective Optimization on the Basic of Ratio Analysis Method in Decision Support System for Hope Family Program Assistance Recipients in Kelinjau Ulu Village Arsita; Salmon; Heny Pratiwi
TEPIAN Vol 2 No 4 (2021): December 2021
Publisher : Politeknik Pertanian Negeri Samarinda

The research was conducted to be able to create a decision support system for beneficiaries of the Family Hope Program or “Program Keluarga Harapan (PKH)” with the Multi Objective Optimization Method On The Basic Of Ratio Analysis (Moora), which later if this research is successful it can assist aid managers in making decision making for program aid recipients Family Hope “PKH”. This research was conducted at the office of the Family Hope Program “PKH” assistance manager in Kelinjau Ulu Village, Muara Analog District, the data collection method used was interviews which asked questions related to “PKH” beneficiaries. By means of observation, namely making direct observations at the “PKH” Assistance Manager office. In this study, the system development method used is the decision support system development method. The model with the decision support software used is the Visual Basic.NET programming language, the database used by Microsoft Access. The final result of this research is in the form of a Decision Support System for beneficiaries of the Family Hope Program “PKH” Using the Multi Objective Optimization Method on the Basic of Ratio Analysis (Moora) which can facilitate more precise selection of “PKH” aid recipients.

Application of the SMARTER Method in Determining the Whitening of Study Permits and Teacher Study Tasks Rahmat Daffa Affandi; Heny Pratiwi; Azahari; Muhammad Ibnu Sa'ad
Aptisi Transactions On Technopreneurship (ATT) Vol 5 No 2 (2023): July
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v5i2.311

Â Study assignment programs and study permits aim to meet the need for staff with certain skills or competencies. in the context of carrying out tasks and functions as well as organizational development, reducing the gap between competency standards and or position requirements with the competencies of Teachers who will fill positions, as well as increasing the knowledge, abilities, skills, attitudes, and professional personality of Teachers, as an integral part of the development plan teacher career. This of course requires a decision support system to be able to assist the Education Office in selecting teachers to provide teacher study permits and study assignments. Decision Support Systems (DSS) or Decision Support Systems (DSS) are computer-based systems that are interactive in assisting decision-makers by utilizing data and models to solve unstructured problems. In this study, the SMARTER method was used as a multi-criteria decision making. The purpose of this research is to assist the Education Office in making decisions when providing a determination of the redemption of study permits, and teacher study assignments as well as providing uniformity and legal certainty in the implementation of study assignments and study permits, and supporting teachers within the local government so that they can improve competence and be more professional in carrying out its duties and functions. Based on research that has been done using the SMARTER method, the sum of each criterion is 0.7840. This implementation produces information that is relatively fast, precise, and feasible to use for updating study permits and teacher learning assignments, and can be carried out without being constrained by time by implementing a web-based application.

Penerapan Data Mining Dalam Menganalisis Pola Belanja Konsumen Menggunakan Market Basket Analysis Sarifmata Purnomo; Heny Pratiwi; Sa'ad, Muhammad Ibnu
METIK JURNAL Vol 7 No 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.678

Currently, almost every activity is related to data. in the business sector, daily sales transaction data stored in the database system will always increase and accumulate. The existing data is only used as an archive by the shop owner so that it has an impact on sales strategies that are not implemented well, even though the existing data can be processed into information to determine the layout of goods so that it has an impact on increasing the occurrence of impulse buying, increasing or maintaining turnover, and minimizing product waste. accumulate until it expires which can be detrimental to the shop.The aim of this research is to find consumer shopping patterns using Marker Basket Analysis. This research method is called market basket analysis or also called association rules, which is a data mining technique for finding patterns that often appear simultaneously in transaction data, so that it can be used as a method for finding information about what kinds of goods are frequently used. purchased by consumers simultaneously. The results of this research, based on data analysis using the Rapidminer application, found 25 associative relationships or rules with a lift ratio value of more than 1, these rules become a reference in determining the layout of goods. Providing recommendations for layout changes aims to make it easier for consumers to shop, increase the possibility of impulse buying by consumers, and maximize product display, thereby reducing the accumulation of goods in the Purnama Store Warehouse.

MEDIA PEMBELAJARAN INTERAKTIF BERBASIS EDUTAINMENT Muhammad Ibnu Sa'ad; Heny Pratiwi; Ahmad Abul Khair
BEduManagers Journal : Borneo Educational Management and Research Journal Vol. 4 No. 2 (2023): BEduManagers Journal : Borneo Educational Management and Research Journal
Publisher : Manajemen Pendidikan Program Doktor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/bedu.v4i2.3011

This educational entertainment-based interactive learning media aims to maximize the teaching and learning process to make it easier and more enjoyable so that it can increase students' interest in learning, especially financial literacy, 3D animation material. Apart from that, teachers can also create questions for students to work on without having to correct them manually because of this system. equipped with an automatic error correction feature based on answers made by the teacher and an educational entertainment system on this website. It is also equipped with mini flash games so that the site content becomes more diverse, and the material is equipped with animation. Content updates can be done dynamically via the admin panel. This educational entertainment-based interactive learning media was developed using the Prototype system development methodology and system development tools using UML (Unifield Modeling Language). In developing this educational entertainment website, the programming languages PHP, HTML, JavaScript, JQuery MySQL Database, and Sublime Text were used as editors. text and Adobe Flash Professional CS6 as image editor. From the results of this research, an edutainment website was created which contains learning material features in the form of animated images, video tutorials about 3D animation, photos of teaching and learning activities for students majoring in multimedia engineering, educational games, discussion forums and multiple choice questions.

Penerapan Data Mining Dalam Menganalisis Pola Belanja Konsumen Menggunakan Market Basket Analysis Sarifmata Purnomo; Heny Pratiwi; Sa'ad, Muhammad Ibnu
METIK JURNAL (AKREDITASI SINTA 3) Vol. 7 No. 2 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i2.678

Currently, almost every activity is related to data. in the business sector, daily sales transaction data stored in the database system will always increase and accumulate. The existing data is only used as an archive by the shop owner so that it has an impact on sales strategies that are not implemented well, even though the existing data can be processed into information to determine the layout of goods so that it has an impact on increasing the occurrence of impulse buying, increasing or maintaining turnover, and minimizing product waste. accumulate until it expires which can be detrimental to the shop.The aim of this research is to find consumer shopping patterns using Marker Basket Analysis. This research method is called market basket analysis or also called association rules, which is a data mining technique for finding patterns that often appear simultaneously in transaction data, so that it can be used as a method for finding information about what kinds of goods are frequently used. purchased by consumers simultaneously. The results of this research, based on data analysis using the Rapidminer application, found 25 associative relationships or rules with a lift ratio value of more than 1, these rules become a reference in determining the layout of goods. Providing recommendations for layout changes aims to make it easier for consumers to shop, increase the possibility of impulse buying by consumers, and maximize product display, thereby reducing the accumulation of goods in the Purnama Store Warehouse.

Analisis Sentimen Orang Tua Murid Baru Terhadap SMPN 40 Samarinda pada SPMB 2025 Menggunakan Algoritma Naïve Bayes Putra, Resifa Ananta; Heny Pratiwi; Ahmad Abul Khair
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 2 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No2.pp292-299

The New Student Admission Selection (SPMB) plays an essential role in ensuring equal educational access in Indonesia. However, during SPMB 2025 at SMPN 40 Samarinda, many candidates living nearby did not choose the school as their first preference, suggesting that perceptions and school image significantly influenced their choices. This study aims to analyze new student parents sentiments toward SMPN 40 Samarinda using the Naïve Bayes algorithm combined with the Term Frequency–Inverse Document Frequency (TF-IDF) technique. Data were collected from 42 respondents and categorized into positive, neutral, and negative sentiments. The model achieved an accuracy of 86%, precision of 56%, and recall of 63%, showing that Naïve Bayes performs effectively on limited data, though less sensitive to minority classes. The analysis revealed that most parents expressed positive perceptions, indicating growing trust that SMPN 40 Samarinda can support students’ character development. These findings emphasize the importance of strengthening school image and service quality while highlighting the potential of machine learning–based sentiment analysis as a data-driven approach to understanding educational perceptions.

Analisis Sentimen Orang Tua Murid Baru Terhadap SMPN 40 Samarinda pada SPMB 2025 Menggunakan Algoritma Naïve Bayes Ananta Putra, Resifa; Heny Pratiwi; Ahmad Abul Khair
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 2 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

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

The New Student Admission Selection (SPMB) plays an essential role in ensuring equal educational access in Indonesia. However, during SPMB 2025 at SMPN 40 Samarinda, many candidates living nearby did not choose the school as their first preference, suggesting that perceptions and school image significantly influenced their choices. This study aims to analyze new student parents' sentiments toward SMPN 40 Samarinda using the Naïve Bayes algorithm combined with the Term Frequency–Inverse Document Frequency (TF-IDF) technique. Data were collected from 42 respondents and categorized into positive, neutral, and negative sentiments. The model achieved an accuracy of 86%, a precision of 56%, and a recall of 63%, showing that Naïve Bayes performs effectively on limited data, though it is less sensitive to minority classes. The analysis revealed that most parents expressed positive perceptions, indicating growing trust that SMPN 40 Samarinda can support students’ character development. These findings emphasize the importance of strengthening school image and service quality while highlighting the potential of machine learning–based sentiment analysis as a data-driven approach to understanding educational perceptions.

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

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

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

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.

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