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All Journal Jurnal Sains dan Seni ITS BAREKENG: Jurnal Ilmu Matematika dan Terapan Journal of Computer Networks, Architecture and High Performance Computing Jurnal Statistika dan Aplikasinya Journal of Mathematics Education and Science Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Journal Of Sharia Banking Brilliance: Research of Artificial Intelligence Mafaza : Jurnal Pengabdian Masyarakat Digital Transformation Technology (Digitech) Jurnal Statistika dan Komputasi (STATKOM) AL-UMRON: Jurnal Pengabdian kepada Masyarakat Jurnal Matematika Integratif Jurnal Pengabdian Masyarakat dan Riset Pendidikan Almantiq
Nita Cahyani
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Innovation of an Expert System for Diagnosing Allergic Diseases in Children using the Web-based Certainty Factor Method Irsyada, Rahmat; Cahyani, Nita; Badriyah, Lailatul
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.5204

Abstract

In this modern era, the development of computer technology has increased so rapidly. Currently the computer is a tool in helping to overcome all the problems encountered by humans, including in the field of health. With the existence of technology, of course, it will greatly facilitate the community to get health services and consultations. One of the technological developments is an expert system. An expert system is a branch of artificial intelligence (Artificial Intelligence), which is an application designed to use a computer that tries to imitate the reasoning process of an expert or expert in solving specific problems and making decisions or conclusions because to solve a problem and save it. in the knowledge base for processing. This expert system was created to assist experts in deciding diseases based on existing symptoms. The Certainty Factor method is a theory that can be used to solve uncertainty problems. Certainty Factor (CF) is a value to measure expert confidence. Certainty Factor was introduced by Shortliffe Buchanan in making the MYCIN expert system to show the amount of trust. This method can work well when there are problems that start from gathering and then gathering information and then being able to find conclusions that can be drawn from that information. The Certainty Factor method will be applied to accurately determine allergic health in children. If this method is applied, it can minimize the presence of allergic diseases suffered by dangerous children. And when you have an allergy, it can be treated immediately.
Family Hope Program Recipient Determination System Using The Naive Bayes Method Irsyada, Rahmat; Cahyani, Nita; Mu’afa , M Rif’an Fawajul; Perdana , Chepy; Febriyanto, Erick
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.6362

Abstract

Poverty is still a problem that Indonesian people continue to face. To achieve prosperity and social justice for all Indonesian citizens, poverty can be considered a situation where a person does not have the ability to fulfill their basic needs, such as food, shelter, clothing, has a low income, has limited access to education, and has work skills. which is inadequate. The government, as a policy maker, has made various efforts to reduce poverty, one of which is through the Family Hope Program (PKH). However, in its implementation, the distribution of PKH assistance still faces problems in terms of targeting accuracy. To overcome this problem, a system is needed that can provide recommendations about who is worthy of receiving PKH assistance. One approach that can be used is a decision support system (DSS) using the Naïve Bayes method. Naïve Bayes is an algorithm used for text classification and is a Machine Learning method that focuses on calculating probability and statistics to predict future probabilities based on past experience. With the help of SPK, this system is able to provide recommendations about who should receive assistance. PKH is based on criteria such as school children, toddlers, pregnant women, the elderly and people with disabilities. Test results using the Naïve Bayes method with Confusion Matrix calculations show an accuracy level of 75%. Next, a comparison was carried out with testing using Cross Validation, which showed an increase in accuracy compared to previous testing without using 10-fold Cross Validation.
Performance Comparison of SelectKBest and Permutation Importance in Feature Selection for Diabetes Prediction Cahyani, Nita; Irsyada, Rahmat
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.6507

Abstract

This study evaluates the effectiveness of two feature selection methods, namely the statistics-based SelectKBest and the model-based Permutation Importance, in improving the performance of classification algorithms for diabetes prediction. A dataset consisting of 17 clinical and demographic features was used to train 11 machine learning algorithms with two subsets of selected features. Performance evaluation used accuracy, precision, recall, F1-Score, ROC AUC, and training time. Based on the results, the SelectKBest method was able to improve the performance of Random Forest with an accuracy of 82.7%, a precision of 0.8, a recall of 0.5, and an F1-Score of 0.615. Meanwhile, the Permutation Importance method showed more consistent performance, with six models including Random Forest, K-Nearest Neighbors, and Quadratic Discriminant Analysis (QDA) achieving an accuracy of up to 86.2%. QDA stood out with the highest ROC AUC of 0.887, indicating better class detection capabilities. These findings underscore the superiority of Permutation Importance in selecting relevant and varied features, including demographic factors, thereby improving overall prediction accuracy. In practice, Random Forest with SelectKBest is recommended for applications requiring fast and interpretable models, while QDA and Gradient Boosting with Permutation Importance are recommended for those requiring high accuracy and sensitivity. This study strengthens the foundation for developing more accurate and applicable diabetes prediction models across various contexts.
Profit Prediction for Skincare Resellers Using the Exponential Smoothing Method Cahyani, Nita; Irsyada, Rahmat; Firman, Azharil; Inayaturohmat, Fatuh; Pramesti, Retta Farah
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.6585

Abstract

This research elucidates the application of the exponential smoothing method in forecasting profit figures for Lutfia MS Glow Skincare. This method was chosen due to its capability to adapt data using the alpha value, along with continual refinement based on exponentially smoothed historical averages. With an explanatory purpose, the study collected profit data from 2020 to 2022 at Lutfia MS Glow Skincare. The single exponential smoothing technique was employed to develop a profit prediction system, enabling the identification of sales trends and evaluation through metrics like Mean Absolute Error (MAE) and Mean Squared Error (MSE). The approach offers simplicity in implementation while providing relatively accurate results, especially for short-term forecasting. This makes it particularly useful in retail and skincare business contexts, where sales figures can be volatile due to seasonal demands or market fluctuations. By utilizing exponential smoothing, the research helps reduce forecasting errors and provides actionable insights for business planning. The result of the analysis showed a reasonably low error margin with a Mean Absolute Percentage Error (MAPE) of 3.65%, indicating high prediction accuracy. The research outcomes furnish skincare resellers and decision-makers with practical guidance in planning inventory, managing supply chains, and executing marketing strategies, ultimately supporting better data-driven decisions in a competitive industry.
HYBRID K MEANS-MULTIVARIATE ADAPTIVE REGRESSION SPLINES FOR DISTRIBUTION OF DENGUE FEVER RISK MAPPING IN BOJONEGORO DISTRICT Kartini, Alif Yuanita; Cahyani, Nita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (396.953 KB) | DOI: 10.30598/barekengvol17iss1pp0313-0322

Abstract

Dengue Hemorrhagic Fever (DHF) is a dangerous disease transmitted by Aedes aegypti and Aedes albopictus mosquitoes’ bites. WHO data shows that almost half of the world's humans are exposed to Dengue Hemorrhagic Fever. The number of mortality caused by dengue disease is around 20,000 every year. In East Java, Bojonegoro District has the highest number of dengue hemorrhagic fever cases (416). To reduce this number, the causative factors need to be known. Additionally, it's important to pinpoint the region or cluster where the variables driving the spread are located so that prevention and treatment efforts are effective. Based on the elements contributing to the transmission of Dengue Hemorrhagic Fever, this study seeks to identify and categorize locations at risk for the spread of the illness. This study uses Hybrid K Means-Multivariate Adaptive Regression Splines (MARS) which is a combination of K-Means and MARS methods in the hope of providing better analytical results. This is because the data was divided into simpler parts by considering the Oakley distance. The results obtained from the K Means-MARS hybrid shows the relationship between response variables and predictor variables for each cluster. There are three clusters of risk for the spread of dengue hemorrhagic fever in Bojonegoro district with categories: high risk cluster, medium risk cluster and low risk cluster. The high risk cluster consists of 7 sub-districts (Baureno, Kepohbaru, Balen, Sumberrejo, Kedungadem, Bojonegoro and Dander). The variables affecting the DHF Sufferer in the high risk cluster were population density (X2), Altitude (X3) and Health Worker (X6). Meanwhile, the medium risk cluster consists of 10 sub-districts (Kalitidu, Kanor, Kapas, Ngasem, Ngraho, Padangan, Sugihwaras, Sukosewu, Tambakrejo, and Trucuk). The variables that affect the DHF Sufferer in the medium cluster are Number of Dead (X1), Population Density (X2) and Health Facility (X5). The low risk cluster consisted of 11 sub-districts (Bubulan, Gayam, Gondang, Kasiman, Kedewan, Malo, Margomulyo, Ngambon, Purwosari, Sekar, and Temayang). The variables affecting the DHF Sufferer rate in the low risk cluster were number of dead (X1) and population density (X2).
DATA MINING STUDY FOR GROUPING ELEMENTARY SCHOOLS IN BOJONEGORO REGENCY BASED ON CAPACITY AND EDUCATIONAL FACILITIES Nurdiansyah, Denny; Saidah, Saniyatus; Cahyani, Nita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp1081-1092

Abstract

The implementation of national education must ensure equitable distribution of educational facilities. However, based on data from the Regional Education Balance Sheet (NPD) in 2021, elementary schools in Bojonegoro District still need to meet the criteria for overall equality. It is mainly related to educational capacity and facilities. It is necessary to group elementary schools based on capacity and educational facilities to solve this problem by applying the clustering method. The research aims to conduct a comparative study of three clustering methods to get the best way to be used for clustering elementary schools in Bojonegoro Regency. This study applies three clustering methods, namely K-Means, K-Medoids, and Random Clustering, which are compared to get the best clustering method. The data used is secondary data representing educational capacity and facilities, namely the number of students, teachers, classrooms, and study groups (Rombel) from the Bojonegoro District Education Office. Obtained the resulting comparison of clustering methods with the best way falls on the K-Means method, which forms 5 clusters. It explained that elementary schools with educational capacity and facilities get highly complete 14 schools (cluster_3), complete 236 schools (cluster_2), fairly complete 176 schools (cluster_4), less complete 310 schools (cluster_1), and incomplete 177 schools (cluster_0). The conclusion that comparing Clustering methods obtained grouping of Elementary School data with the best way falls on the K-Means method by getting 5 clusters.
THE IMPACT OF DISTRIBUTION OF FUNDING AND THE AMOUNT OF THIRD PARTY FUNDS ON THE PERFORMANCE OF BANK BCA SYARIAH PERIOD 2014 – 2021 Husna, Ovilia; Hariyanto, Sidiq; Nurhana, Inka Ayu; Cahyani, Nita; Prastiwi, Iin Emy
Journal Of Sharia Banking Vol 4, No 2 (2023): Journal Of Sharia Banking
Publisher : Universitas Islam Negeri Syekh Ali Hasan Ahmad Addary Padangsidimpuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24952/jsb.v4i2.9381

Abstract

The main problem in this thesis is the relationship of third party funds  and financing to profits at Bank BCA Syariah. The purpose of this study is to determine how big the relationship between third party funds  and financing to the profits of Bank BCA Syariah.This study uses the profitability variable using the Return On Asset (ROA) measurement, and the independent variable is TPF (Third Party Funds).This study aims to determine whether the amount of financing and Third Party Funds has an effect on the Profit of Bank BCA Syariah. This research was conducted in 2014-2021. This research is a quantitative research with secondary data. Data analysis using multiple linear regression analysis,Simultan test (Test F), Partial Test (Test t), And Test Koefisiens determinasi. Which I got from the quarterly financial statements of Bank BCA Syariah in 2014-2021.. But first, use the classical assumption test to test the quality of the data, before it is processed by regression. From the results of this study, it was found that third party funds and financing had no significant effect on the Profit Bank of BCA Syariah. 
Application Of The Association Rule Method Based On Book Borrowing Patterns In Bojonegoro Regional Libraries Lestari, Putrye Aufia Indah; Cahyani, Nita
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i2.2893

Abstract

The library is an institution that processes collections of written and printed works, to meet the educational, research, information, and recreation needs of its users. The Bojonegoro Library Service provides reading materials with a collection of around 24,130 book titles and around 24,130 book copies. The number of registered visitors was 1,424 people. From 2021-2022, there are 303 book lending transaction data. Knowing the results of the Association Rule with the Frequent Pattem-Growth algorithm in determining recommendations for book placement based on borrowing patterns in libraries in the Bojonegoro area. The method used is Association Rule Mining, to produce an efficient algorithm, the algorithm used is the Frequent Pattern Growth (FP-Growth) Algorithm. The characteristic of the FP-Growth algorithm is the data structure used in a tree called FP-Tree. By using FP-Tree the FP-Growth algorithm can directly extract frequent itemsets from FP-Tree. The results of the research carried out by applying the FP growth algorithm with a support value limit of 20% and a confidence value of 80% from a dataset of 144 book lending transactions which became frequent itemsets were a combination of itemsets, resulting in a strong rule of 5 association rules which met the requirements. Can help the Bojongoro Library and archives service to improve the quality of service and can provide recommendations for librarians and as a reference for placing classes of books that are more often borrowed together closer together.
Analisis Faktor Makroekonomi yang Mempengaruhi Indeks Harga Saham Gabungan Menggunakan Algoritma Analisis Jalur Cahyani, Nita; Irsyada, Rahmat; Alfiyatul, Siti Nur
Digital Transformation Technology Vol. 4 No. 2 (2024): Periode September 2024
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v4i2.5207

Abstract

Perkembangan ekonomi yang baik pada suatu negara merupakan suatu indikator yang digunakan oleh para pelaku usaha untuk berinvestasi. Sebelum berinvestasi dalam sebuah saham, investor harus memperhatikan pergerakan harga saham. Indeks Harga Saham dipengaruhi oleh beberapa faktor makroekonomi, antara lain inflasi dan suku bunga BI. Upaya yang dilakukan pemerintah dalam mengatasi tingginya inflasi salah satunya adalah dengan mengurangi jumlah uang yang beredar. Selain inflasi dan suku bunga, nilai tukar uang juga dapat mempengaruhi indeks harga saham.Penelitian ini bertujuan untuk mengetahui faktor apa saja yang mempengaruhi indeks harga saham gabungan. Metode analisis yang digunakan dalam penelitian ini adalah metode analisis jalur. Hasil penelitian menyatakan bahwa jumlah uang beredar, nilai tukar uang dan suku bunga BI secara langsung secara sigifikan mempengaruhi indeks harga saham gabungan, sedangkan inflasi secara langsung secara signifikan tidak mempengaruhi indaks harga saham gabungan. Jumlah uang beredar, inflasi dan nilai tukar uang berpengaruh signifikan terhadap indeks harga saham gabungan melalui suku bunga BI.
Penerapan Algoritma Neural Network untuk Klasifikasi Diabetes Mellitus: Perbandingan Backpropagation dan Resillient Backpropagation Cahyani, Nita; Irsyada, Rahmat; Mahmuda, Rahmawati
Digital Transformation Technology Vol. 4 No. 2 (2024): Periode September 2024
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v4i2.5208

Abstract

Diabetes Mellitus (DM) adalah gangguan metabolisme yang ditandai dengan hiperglikemia kronis dan kelainan metabolisme karbohidrat, lipid, dan protein yang disebabkan oleh kelainan sekresi insulin, kerja insulin, atau keduanya. Penelitian ini bertujuan untuk membandingkan hasil klasifikasi menggunakan analisis Backpropagation Neural Network (BPNN) dengan Resilient Backpropagation Neural Network (RBPNN) pada kasus Diabetes Mellitus. Metode yang digunakan pada penelitian ini adalah metode analisis BPNN dan RBPNN dengan sumber data yang diperoleh dari RSUD Sosodoro Djatikusumo Bojonegoro. Dari penelitian ini diperoleh hasil penyebab utama faktor-faktor yang mengakibatkan DM adalah faktor keturunan, tekanan darah dan umur. Dari penelitian ini dapat disimpulkan bahwa faktor dominan yang ada pada penderita DM adalah faktor keturunan yang telah dijelaskan oleh model terbaik yaitu RBPNN
Co-Authors Agus Sulistiawan Alfiyatul, Siti Nur Ana Alfina Anggi, Diva Budiman S, M. Arif Denny Nurdiansyah Destri Susilaningrum Erick Febriyanto Firman, Azharil Hanifah, Aisyah Hariyanto, Sidiq Husna, Ovilia Iin Emy Prastiwi, Iin Emy Inayaturohmat, Fatuh Irsyada, Rahmat Kartini, Alif Yuanita Khoiriyah, Nuraini Lailatul Badriyah Lestari, Putrye Aufia Indah Mahmuda, Rahmawati Muhammad Arif Budiman Muhammad Sjahid Akbar Mu’afa , M Rif’an Fawajul Nilna Himawati Nur Inda Nafa Natalia Nuraini Khoiriyah Nurhana, Inka Ayu Perdana , Chepy Pramesti, Retta Farah Pratama, Gilar Budi Putri, Wardiana Adinda Putrye Aufia Indah Lestari Qibtiyah, Mariyatu Saidah, Saniyatus Sanjaya, Ucta Pradema Suttrisno Umi Kholifah