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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 Journal of Innovative and Creativity Almantiq Jurnal Pengabdian Masyarakat Indonesia
Nita Cahyani
Universitas Padjadjaran
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 Law, Crime, Criminology & Criminal Justice 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.
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
Implementasi Machine Learning Model sebagai Sistem Prediksi Penyakit Breast Cancer Cahyani, Nita; Irsyada, Rahmat; Kartini, Alif Yuanita
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.v4i2.5209

Abstract

Breast Cancer atau Kanker payudara adalah penyakit yang paling umum ditemukan pada wanita di seluruh dunia. Setiap perkembangan untuk prediksi dan diagnosis penyakit kanker merupakan modal penting untuk hidup sehat. Sehingga, akurasi tinggi dalam prediksi kanker penting untuk memperbarui aspek pengobatan dan standar kelangsungan hidup pasien. Teknik Machine Learning (ML) merupakan aplikasi dari Artificial Intelligence (AI) yang dapat memberikan kontribusi besar pada proses prediksi dan diagnosis dini kanker payudara, dan telah terbukti sebagai teknik yang kuat. Dalam penelitian ini, diterapkan algoritma Machine Learning yaitu metode single: Support Vector Machine (SVM), Random Forest, Logistic Regression, dan K-Nearest Neighbors (KNN) dan metode ensemble yaitu SMOTE-Boosting dan SMOTE-Bagging pada dataset Breast Cancer di Bojonegoro. Tujuan dari penelitian ini Mendaptakan ketepatan klasifikasi atau prediksi breast cancer khususnya studi kasus di Bojonegoro dengan tingkat kinerja yang lebih baik. Nilai akurasi yang terbaik pada metode single yaitu model Random Forest (RF) sebesar 95,65% untuk data testing, 100% untuk data training sedangkan untuk metode ensembel SMOTE-Boosting Random Forest (RF) sebesar 100% untuk data testing, 100% untuk data training dan SMOTE-Bagging RF sebesar 97% untuk data training dan 100% untuk data testing. Sehingga SMOTE-Boosting RF dapat dijadikan analisis prediksi yang terbaik dalam penelitian ini. Hasil ini dapat digunakan di masa depan untuk memprediksi penyakit lainnya.
Transformasi Digital UMKM: Pengembangan Marketplace BANGKIT (Belanja UMKM Kreatif, Inovatif, dan Komplit) untuk Ekspansi Penjualan Produk Lokal UMKM Kabupaten Subang Rahmat Irsyada; Lani Nurlani; Abd Rachman Mildan; Arnov Abdillah Rahman; Rachmad Augy; Nita Cahyani
JURNAL PENGABDIAN MASYARAKAT INDONESIA Vol. 4 No. 3 (2025): Oktober : Jurnal Pengabdian Masyarakat Indonesia (JPMI)
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jpmi.v4i3.6021

Abstract

Limitations in the adoption of digital technology are a major challenge for Micro, Small, and Medium Enterprises (MSMEs) in Subang Regency, which is reflected in the still-manual production process, conventional business management, and limited marketing reach on a local scale. On the other hand, the general public also faces low digital literacy which hinders participation in the modern economy. This community service program aims to address these problems through the design and development of an integrated marketplace platform called BANGKIT (Creative, Innovative, and Complete MSME Shopping). The program implementation method uses a participatory approach that includes three main stages: (1) development of the marketplace platform as a digital showcase for local products; (2) intensive training and mentoring for MSME actors regarding online store management, product photography, and digital marketing strategies; and (3) facilitation of the onboarding process for MSME products into the platform. The results of this activity are the realization of a functional digital economic ecosystem, increased capacity and empowerment of MSME partners, and expanded market reach for local products. This program not only provides concrete solutions for MSMEs, but also supports the achievement of the Key Performance Indicators (KPI) of higher education through the active involvement of lecturers and students in providing direct benefits to the community. Program outputs are disseminated through publications in community service journals, mass media, activity videos, poster works and reports on increasing the level of partner empowerment: management aspects.
Implementation of the K-Nearest Neighbor Method in a Web-Based Creditworthiness Decision Support System in Employee Cooperatives Nita Cahyani; Rahmat Irsyada; Hidayah Maulida
Journal of Innovative and Creativity Vol. 5 No. 3 (2025)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

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

Abstract

The Republic of Indonesia Employees' Cooperative (KPRI) was established as a legal entity based on the principles of family and people's economy, with a primary mandate to improve the welfare of its members. In its operations, savings and loan units are a crucial service. However, the cooperative's financial sustainability often faces serious challenges in the form of the risk of losses due to bad debts from debtors. This problem indicates that conventional methods for assessing prospective borrowers are often inaccurate and risk subjective, necessitating the need for stronger and more systematic criteria as a basis for decision-making. This research aims to address these issues by developing a Decision Support System (DSS) for loan eligibility. Through literature review and the collection of historical member transaction data, this research implements the K-Nearest Neighbor (K-NN) algorithm. This method was chosen for its ability to classify new loan eligibility based on similarity patterns (shortest distance) to previous customer data. The research results show that integrating the K-NN algorithm into the decision support system has a significant positive impact. The system has proven capable of providing classification recommendations that assist cooperative staff in processing loan applications according to predetermined criteria. System testing yielded a feasibility rate of 88%, indicating excellent performance. Overall, it can be concluded that the implementation of the K-NN method in KPRI loan approval processes makes the selection process more objective, accurate, and time-efficient compared to manual methods. This system is suitable for implementation as a strategic solution to minimize the risk of bad debt and maintain the financial stability of cooperatives.
Co-Authors Abd Rachman Mildan Agus Sulistiawan Alfiyatul, Siti Nur Ana Alfina Arnov Abdillah Rahman Azharil Firman Budiman S, M. Arif Chepy Perdana Denny Nurdiansyah Destri Susilaningrum Diva Anggi Erick Febriyanto Fatuh Inayaturohmat Gilar Budi Pratama Hanifah, Aisyah Hariyanto, Sidiq Hidayah Maulida Husna, Ovilia Iin Emy Prastiwi, Iin Emy Irsyada, Rahmat Kartini, Alif Yuanita Khoiriyah, Nuraini Lailatul Badriyah Lani Nurlani Lestari, Putrye Aufia Indah M Rif’an Fawajul Mu’afa Mahmuda, Rahmawati Muhammad Arif Budiman Muhammad Sjahid Akbar Nilna Himawati Nur Inda Nafa Natalia Nuraini Khoiriyah Nurhana, Inka Ayu Pramesti, Retta Farah Putri, Wardiana Adinda Putrye Aufia Indah Lestari Qibtiyah, Mariyatu Rachmad Augy Rahmat Irsyada Rahmat Irsyada Retta Farah Pramesti Saidah, Saniyatus Sanjaya, Ucta Pradema Suttrisno Umi Kholifah