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All Journal Prosiding Semnastek Paradigma Techno Nusa Mandiri : Journal of Computing and Information Technology Pendas : Jurnah Ilmiah Pendidikan Dasar JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Teknologi Informatika dan Komputer Journal of Students‘ Research in Computer Science (JSRCS) IMTechno: Journal of Industrial Management and Technology Jurnal Administrasi Kantor Jurnal Teknik Informatika dan Elektro (JURTIE) Jurnal Riset Rumpun Ilmu Teknik (JURRITEK) Inisiatif: Jurnal Ekonomi, Akuntansi Dan Manajemen Neraca Manajemen, Akuntansi, dan Ekonomi Intechno Journal : Information Technology Journal
Novita Indriyani
Universitas Bina Sarana Informatika
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Social Sciences Other

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Attendance Mobile Application With Face Recognition and Detect Location Andika Bayu Hasta Yanto; Ahmad Fauzi; Novita Indriyani
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 5 No. 1 (2022): Jurnal Teknologi dan Open Source, June 2022
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v5i1.2187

Abstract

Every company must have an attendance policy for each of its employees for the purpose of employee attendance and performance reports in the performance of their work, but currently there are still many companies that still have an absence system that is not computerized, so the calculation and accounting process is still done manually, because everything is calculated manually, it is possible that there are errors in the calculations and take time to process data absence of all employees. Therefore, an application that can automatically process and record data is needed to avoid errors and speed up the data processing process. In addition, the application can facilitate employees' attendance as it can be accessed directly from cell phones by using facial recognition and location detection to prove the attendance of employees.
Application Of Simple Additive Weighting (SAW) For The Selection Of Breast Milk Pumps For Working Mothers Novita Indriyani; Ahmad Fauzi; Andika Bayu Hasta Yanto
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 5 No. 2 (2022): Jurnal Teknologi dan Open Source, December 2022
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v5i2.2626

Abstract

Optimal breastfeeding is very important because it can save more than 800,000 lives of children under five every year. Among the many reasons why mothers do not exclusively breastfeed is that they go back to work (22.5%). Homemakers have a greater chance of exclusively breastfeeding because they spend more time with the baby, allowing them to breastfeed optimally. Based on the results of previous studies, working mothers give breast milk directly (when they are at home or resting) and give milk from milk. Using a breast pump is considered more practical, easier and saves time. The breastpump method (MPA) for exclusive breastfeeding for working mothers also does not interfere with the work process and offers flexibility in working hours. What worries women who work while breastfeeding is maintaining breast milk production during working hours. However, according to research, there is no significant difference between the effectiveness and satisfaction of breast milk production when using an electric breast pump. The use of a breast pump does not affect the amount of breast milk produced, even though an electric breast pump provides more effectiveness and satisfaction in expressing breast milk. This study aims to select the type of breast pump for working mothers to facilitate exclusive breastfeeding of the baby. The result of the calculation of SAW method resulted in a recommendation for a breast pump Moom Uung with a value of 15.67 The result of the calculation of SAW method resulting in a recommendation for a breast pump Moom Uung with a value of 15.67.
Implementation of Data Mining of Organic Vegetable Sales With Apriori Algorithm Ahmad Fauzi; Andika Bayu Hasta Yanto; Novita Indriyani
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 6 No. 1 (2023): Jurnal Teknologi dan Open Source, June 2023
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v6i1.3049

Abstract

In the modern organic vegetable sector, the author observes that there is very tight business competition. Therefore, an effective approach is essential to attract buyers, although restricted sources of new information are one of the hurdles in establishing this business.Association rules are expressed with numerous features that are commonly referred to as (affinity analysis) or (market basket analysis. It was discovered that if consumers buy curly red chilies, they are also inclined to buy cayenne pepper with a 100% confidence level. Likewise, if people buy kale and red curly chiles, they are more likely to buy cayenne pepper with a 100% confidence level. This also applies if consumers buy tomatoes and curly red chilies with a 100% confidence level. In addition, other associations were also observed, such as if consumers buy curly red chilies, they prefer to buy tomatoes with a confidence level of 86%, or if they buy tomatoes and bird's eye chilies, they tend to buy curly red chiles with an 86% confidence level.Likewise, if people buy both cayenne pepper and red curly chili, they are more likely to buy tomatoes with an 86% confidence level. Finally, if customers buy kale and cayenne pepper, they are also likely to buy red curly chilies at an 83% confidence level. Based on the data acquired from this study, it is intended to obtain information about combinations of organic veggies that consumers typically buy together in each transaction, with the intention of improving organic vegetable yields and devising appropriate sales tactics.
A Decision-Making Model for Kindergarten School Selection Using the AHP Method: A Case Study of West Bekasi Novita Indriyani; Ahmad Fauzi; Andika Bayu Hasta Yanto
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.5096

Abstract

Choosing a Kindergarten (TK) is an important decision for parents because it involves many aspects such as the quality of educators, curriculum, facilities, costs, and environmental safety. However, the complexity of these criteria often creates uncertainty in making objective decisions. This study applies the Analytical Hierarchy Process (AHP) method to help provide recommendations for selecting the best kindergarten in the West Bekasi area. The hierarchical structure is built with six main criteria assessed by respondents through pairwise comparisons using Expert Choice. The synthesis results show that Kindergarten C received the highest weight of 0.433, followed by other alternatives, thus being determined as the best choice based on the criteria used. A Consistency Ratio (CR) value of 0.1 indicates that respondents' assessments are within the consistent limit (CR ≤ 0.1). Thus, the AHP model is proven to be able to measure priorities in a structured manner and help parents in making decisions about choosing a kindergarten more objectively and rationally.
Application of Backward Elimination Method for Optimization of Decision Tree C4.5 Algorithm in Employee Performance Prediction Ahmad Fauzi; Novita Indriyani; Andika Bayu Hasta Yanto
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 9 No. 1 (2026): Jurnal Teknologi dan Open Source, June 2026
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v9i1.5639

Abstract

This study aims to analyze the application of the Backward Elimination method in optimizing the Decision Tree C4.5 algorithm in predicting employee performance. The main problem in this study is the employee performance evaluation process which is still done manually so that it has the potential to cause inconsistency in the assessment results. The study used a dataset of 500 employee data with several performance assessment attributes such as age, education level, work discipline, productivity, and superior assessment. The research method includes data preprocessing, feature selection using Backward Elimination, application of the Decision Tree C4.5 algorithm, and model evaluation using 10-Fold Cross Validation in the RapidMiner application. The test results show that the Decision Tree C4.5 algorithm without optimization obtained an accuracy value of 89.60% and an AUC of 0.944. After applying the Backward Elimination method, model performance increased with an accuracy value of 92.80% and an AUC of 0.972. This increase indicates that the Backward Elimination method is able to reduce less relevant attributes so that the classification process becomes more optimal. Thus, the application of the Backward Elimination method has proven effective in improving the performance of the Decision Tree C4.5 algorithm in predicting employee performance.
Co-Authors Abimanyu, Ridwan Ahmad Fauzi Ahmad Fauzi Andika Bayu Hasta Yanto Andika Bayu Hasta Yanto Apriliantoni, Apriliantoni Apriliantoni, Rasyad Fiqry Caturitama Bernadhed, Bernadhed Chamariyah Chamariyah Darusyifa F, Muhamad Dea Ayu Prananda Fani Fitra Fauzi Ahmad Muda Haikal Restu Dirgantara Henny Destiana Heru Satria Tambunan Indarti Kharisma fajarwati Kurniawati Mulyanti Marlina Marlina Muhamad Ripqi Nanda Iramatul Izza, RA Nani Agustina Noor Shodiq Askandar Rachmat Suryadithia Rian Septian Anwar Ridwan Abimanyu Rizki Wahyu Yunian Putra Sandra Jamu Kuryanti Shabrina Nailussaadah Siska Andriani Slamet Heri Winarno Suryadithia, Rachmat Wahyudi, Wiwid Wina Yusnaeni Yunianto, Irdha Zulia Almaida Siregar