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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Swabumi (Suara Wawasan Sukabumi) : Ilmu Komputer, Manajemen, dan Sosial INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Knowledge Engineering and Data Science Jurnal Matematika: MANTIK Jurnal Matematika Sains dan Teknologi BAREKENG: Jurnal Ilmu Matematika dan Terapan JCES (Journal of Character Education Society) JTP - Jurnal Teknologi Pendidikan Jurnal Varian JAMBURA JOURNAL OF PROBABILITY AND STATISTICS International Journal of Global Operations Research Parameter: Journal of Statistics VARIANSI: Journal of Statistics and Its Application on Teaching and Research Jurnal Statistika dan Sains Data Jurnal Sains dan Kesehatan
Hasanah, Siti Hadijah
Universitas Terbuka, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Immunology & microbiology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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Multivariate Adaptive Regression Splines (MARS) for Modeling Student Status at Universitas Terbuka Siti Hadijah Hasanah
Jurnal Matematika MANTIK Vol. 7 No. 1 (2021): Mathematics and Applied Mathematics
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15642/mantik.2021.7.1.51-58

Abstract

Multivariate Adaptive Regression Splines (MARS) used to model the active student’s status in the Department of Statistics at Universitas Terbuka and determine the factors that influence the response variable. This study consists of 9 variables, namely gender, age, education, marital status, job, initial registration year, number of registrations, credits, and GPA, but after modeling using the MARS method, the explanatory variable can affect the response variable is the initial registration year. Several registrations, GPA, and credits. Based on the results of the R output and using a 95% confidence interval, each base 1 to 10 function is partially significant with the p-value of the base 1-10 function being smaller than 0.05 and simultaneously with a smaller p-value. of 0.05, so that the above model has a significant effect partially or simultaneously on the response variable. From these results, it is concluded that the MARS model is suitable for determining the factors that affect the active status of students.
COUNSELING ON HEALTHY FOOD MANAGEMENT FOR UNDERNOURISHED TODDLERS AT TUNAS HARAPAN PAMULANG TANGERANG SELATAN Sri Enny Triwidiastuti; Siti Hadijah Hasanah
JCES (Journal of Character Education Society) Vol 5, No 1 (2022): Januari
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jces.v5i1.5648

Abstract

Abstrak: Penyuluhan Pengolahan Makanan Sehat yang dilakukan di Pos Gizi Tunas Harapan Pamulang Timur merupakan penyuluhan dalam peningkatan kemampuan para kader Pos Gizi dan ibu-ibu yang memiliki balita berstatus gizi kurang. Kegiatan ini memberikan penyuluhan tentang cara pengolahan makanan sehat, perilaku hidup sehat, dan pemberian makanan tambahan (PMT). PMT ini menggunakan bahan baku pangan lokal dengan menu khas daerah yang disesuaikan dengan kondisi setempat. Data bayi/balita BBR berasal dari Kader Pos Gizi yang berjumlah 14 anak. Kegiatan ini berlangsung bersamaan dengan terjadi pandemi, sehingga strategi pelaksanaan menjadi berubah, walaupun demikian protokol Covid 19 dilaksanakan dengan ketat. Penyuluhan disertai dengan pembagian flyer untuk kader Pos Gizi dan para ibu bayi/balita, serta diharapkan dapat membantu relawan/kader Pos Gizi melaksanakan tugas meningkatkan gizi balita. Hasil penyuluhan dan PMT secara statistik tidak ada perbedaan yang signifikan antara rata-rata BB sebelum dan sesudah PMT dengan taraf nyata 5%. Penyebabnya adalah jadwal PMT berubah, yang semula 5 kali dalam seminggu di awal bulan, menjadi 5 kali selama 2 bulan.Abstract: Counseling on Healthy Food Processing conducted at the Tunas Harapan Pamulang East Heart Center is an extension to increase the capacity of Hearth cadres and mothers who have under-fives with undernourished status. This activity provides counseling on how to process healthy food, healthy living behavior, and providing additional food/PMT. This PMT uses local food raw materials with regional specialties adapted to local conditions. Data for BBR infants/toddlers came from the Hearth Cadre, totaling 14 children. This activity took place simultaneously with the pandemic, so the implementation strategy changed, even though the Covid 19 protocol was implemented strictly. The counseling is accompanied by the distribution of flyers for Hearth cadres and mothers of babies/toddlers, and it is hoped that they can help Hearth volunteers/cadres carry out the task of improving toddler nutrition. The results of counseling and PMT statistically there was no significant difference between the average weight before and after PMT with a significance level of 5%. The reason is that the PMT schedule has changed, which was originally 5 times a week at the beginning of the month, to 5 times for 2 months.
Analysis of User Satisfication with Graduates in Statistical Study Program Universitas Terbuka Siti Hadijah Hasanah; Dewi Juliah Ratnaningsih
Jurnal Varian Vol 5 No 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v5i1.1331

Abstract

Revolution 4.0 requires the Universitas Terbuka Statistics study program to change the educational curriculum that aims to produce quality graduate competencies. Therefore, to collect informationand evaluate the competence of graduates, it is necessary to conduct tracer study research on each graduate. This study aims to measure user satisfaction with graduate competencies using Gap analysis, Importance-Performance Analysis (IPA), Customer Satisfaction Index (CSI), and a multi-attribute Fishbein model. Based on the value of Gap and Science, the main priority that must be improved by graduates to meet user expectations is the ability to solve problems, generate ideas, and be able to present the results of these ideas in the form of reports/journals. The value of the level of suitability between user satisfaction and the importance of the ability of graduates is very good at 92.87% and a CSI value of 78.25%, which means that overall user satisfaction with graduates is good, besides thatbased on the results of the multi-attribute Fishbein model, an Ao value of 158.20 which means that graduate users have a positive attitude towards the abilities of UT Statistics program graduates.
PENERAPAN METODE HUNGARIAN DAN APLIKASI QM UNTUK MEMINIMALISASI KOMPLAIN KEBERSIHAN DARI KLIEN Epin Nur Cahya; Nina valentika; Isnurani; Siti Hadijah Hasanah
Jurnal Matematika Sains dan Teknologi Vol. 23 No. 1 (2022)
Publisher : LPPM Universitas Terbuka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33830/jmst.v23i1.1425.2022

Abstract

An outsourcing company with a work contract period can run well if the work agreement made by the client is carried out properly. One of the things that affect the contract period is client complaints. By minimizing client complaints, the sustainability of work contracts between outsourcing companies and client companies is getting higher. For this reason, outsourcing companies assign workers based on the abilities of each worker so that the work results are optimal. One of the methods in solving assignment problems is the Hungarian method and the QM application. The purpose of this research is to minimize the value of hygiene complaints from clients. The results showed a reduction in the value of 15 client complaints from 43 complaints to 28 complaints related to the completion of the assignment of employees of outsourcing company using the Hungarian method and the QM application.
Application of Machine Learning for Heart Disease Classification Using Naive Bayes Siti Hadijah Hasanah
Jurnal Matematika MANTIK Vol. 8 No. 1 (2022): April - June
Publisher : Mathematics Department, Faculty of Science and Technology, UIN Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15642/mantik.2022.8.1.68-77

Abstract

The Naive Bayes classifier uses an approximation of a Bayes theorem by combining previous knowledge with new ones. The purpose of this research is to develop machine learning using Naive Bayes classification techniques and as a decision system in producing fast and accurate classification accuracy in diagnosing cardiovascular diseases such as heart disease. Cardiovascular disease is the leading cause of death, 32% of all global deaths, of which 85% are caused by stroke and heart disease. Based on the results of the analysis, it was found that the accuracy of classification accuracy in the training data on patient data was classified as having and not having heart disease, respectively 83,21% and 83,1%. In data testing, the percentage of patient data classified as having and not having heart disease was 83,78% and 87,50%, respectively. Based on the AUC values ​​in the training data and testing data, they are 83,15% and 85,24%, respectively. So, from these results, it can be concluded that the Naive Bayes method is good for classifying heart disease patient data.
Penerapan Analisis Faktor dalam Mengidentifikasi Efektivitas Aplikasi Mybb Forum Diskusi Dian Nurdiana; Siti Hadijah Hasanah
SWABUMI (Suara Wawasan Sukabumi): Ilmu Komputer, Manajemen, dan Sosial Vol 12, No 1 (2024): Volume 12 Nomor 1 Tahun 2024
Publisher : Universitas Bina Sarana Informatika Kota Sukabumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/swabumi.v12i1.16476

Abstract

Program Studi Sistem Informasi di Universitas Terbuka merupakan program studi dengan sistem pembelajaran terbuka dan jarak jauh, layanan bimbingan akademik dan diskusi dilakukan melalui media. Forum diskusi menggunakan aplikasi Mybb disediakan sebagai media layanan akademik dan diskusi, namun saat ini belum diukur terkait efektivitasnya. Tujuan dari penelitian ini yaitu untuk menerapkan analisis faktor dalam mengidentifikasi efektivitas penggunaan aplikasi forum Mybb di lingkungan Program Studi Sistem Informasi sebagai media layanan bimbingan dan diskusi mahasiswa. Metode penelitian menggunakan kuantitatif deskriptif, dilanjutkan dengan analisis faktor menggunakan  Barlett Test of Sphericity dan Keiser Meyers Oklin (KMO). Data penelitian berasal dari data primer hasil pengisian kuesioner mahasiswa dan berdasarkan hasil analisis faktor didapatkan bahwa terdapat dua faktor yang dapat mengidentifikasi efektivitas penggunaan aplikasi forum Mybb yaitu faktor easy to use dan easy to learn. Faktor easy to use yang terdiri dari indikator fungsionalitas, flexibilitas, aksesibilitas, dan useful. Sedangkan faktor easy to learn yang terdiri dari indikator efisien, fitur, informatif, dan performance.The Information Systems Study Program at the Open University is a study program with an open and distance learning system, academic guidance services and discussions are conducted through the media. Discussion forums using the Mybb application are provided as a medium for academic services and discussion, but currently their effectiveness has not been measured. The purpose of this study is to apply factor analysis in identifying the effectiveness of using the Mybb forum application in the Information Systems Study Program environment as a medium for student guidance and discussion services. The research method uses descriptive quantitative, followed by factor analysis using the Barlett Test of Sphericity and Keiser Meyers Oklin (KMO). The research data comes from primary data from filling out student questionnaires and based on the results of factor analysis it is found that there are two factors that can identify the effectiveness of using the Mybb forum application, namely the easy to use and easy to learn factors. The easy to use factor consists of indicators of functionality, flexibility, accessibility and usefulness. Meanwhile, the easy to learn factor consists of efficient, feature, informative, and performance indicators.
College Students' Perceptions Toward Usability of Simulator Application as a Form of Virtual Experiment at the Distance Learning Nurdiana, Dian; Hasanah, Siti Hadijah; Maulana, Muhamad Riyan
International Journal of Global Operations Research Vol. 5 No. 1 (2024): International Journal of Global Operations Research (IJGOR), February 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i1.269

Abstract

The use of simulator applications as one of the learning media is used in face-to-face classes. Its use is rarely used to support distance learning. In fact, the distance learning process must have the same quality as face-to-face learning. The role of technology and media is one of the keys to success in conveying material to students. This study examines the use of simulator applications in distance learning in terms of its reusability. The simulator application used is Cisco Package Tracer on learning computer networks with modules as the main teaching material used by students. The use of this media aims to understand and practice computer network simulations. By involving 60 participants, a case study regarding usability feasibility was measured by using the USE Questionnaire which consisted of 4 usability dimensions: Usefulness, Ease of Use, Ease of Learning, and Satisfaction. The findings show that the use of simulator applications in distance learning gets good or positive responses in the context of usability. This shows that the use of simulator applications is suitable for use in distance learning.
METODE KLASIFIKASI JARINGAN SYARAF TIRUAN BACKPROPAGATION PADA MAHASISWA STATISTIKA UNIVERSITAS TERBUKA Hasanah, Siti Hadijah; Permatasari, Sri Maulidia
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 2 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1137.936 KB) | DOI: 10.30598/barekengvol14iss2pp243-252

Abstract

Backpropagation Artificial Neural Network (ANN) is an ANN that uses a supervised learning algorithm. The purpose of this study is to determine the parameters and measure the accuracy of the classification accuracy of the student status of the Open University Statistics Study Program. Based on the results, the simulation obtained 15 parameters that can affect student status, including gender, age, education (Senior High School, Diploma, Bachelor, and Magister), marital status, employment status (not working, private employees, entrepreneurs, and civil servants), initial registration year, registration number, semester credit system, and GPA). Meanwhile, for the classification accuracy, the activation function and the learning rate are used minimum mean square of error (MST) on training data. The simulation results are also applied to the testing data with a cut-off point value of 0.3481, so the accuracy of the ROC curve is obtained in the training data for not active students is 99.43% and 99.14% active, while the testing data for not active students is 94.00%. and active 93.94%. So from this research, it can be concluded that ANN Backpropagation is a very good method in applying the classification method.
GOJEK DATA ANALYSIS THROUGH TEXT MINING USING SUPPORT VECTOR MACHINE (SVM) AND K-NEAREST NEIGHBOR (KNN) Hasanah, Siti Hadijah; Maulana, Muhamad Riyan; Nurdiana, Dian
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp889-902

Abstract

The main focus of this research is to apply and test the effectiveness of SVM and KNN methods in Gojek data text analysis. This research will examine how the two methods can classify user comments and feedback and identify data sentiment analysis at the same time practically help Gojek understand user needs and improve service quality. The data obtained through scrapping is categorized into positive and negative sentiment. Data is taken from Gojek application user reviews throughout the year 2022 with a total of 1148 sentiment data with a percentage of 80% training data and 20% testing data. Evaluation of model performance using Confusion Matrix and AUC-ROC Curve shows that SVM is more effective than KNN, with accuracy on training data of 92.55% for SVM and 81.71% for KNN, as well as accuracy on testing data of 82.40% for SVM and 77,09% for KNN.
Generative artificial intelligence as an evaluator and feedback tool in distance learning: a case study on law implementation Nurdiana, Dian; Maulana, Muhamad Riyan; Hasanah, Siti Hadijah; Chairunnisa, Madiha Dzakiyyah; Komuna, Avelyn Pingkan; Rif'an, Muhammad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i3.pp2490-2505

Abstract

The development of generative artificial intelligence (GAI) has impacted various fields, including higher education. This research examines the use of GAI as an evaluator and feedback provider in distance legal education. This study tested five GAI models: ChatGPT, Perplexity, Gemini, Bing, and You, using a sample of 20 students and evaluations from legal experts. Descriptive statistical analysis and non-parametric tests, including Wilcoxon, intraclass correlation coefficient (ICC), Kappa, and Kendall's W, were used to assess accuracy, feedback quality, and usability. The results showed that ChatGPT was the most effective GAI, with the highest mean scores of 4.22 from experts and 4.12 from students, followed by Gemini with scores of 4.15 and 4.07. In terms of binary judgement accuracy, Gemini scored 80%, ChatGPT 60%, while Perplexity, Bing, and You had lower scores. Statistical analysis showed moderate agreement (ICC=0.439) and low alignment (Kappa=-0.058) between the GAIs and expert evaluations, with a Kendall's W value of 0.576 indicating moderate consistency in judgements. These findings emphasize the importance of selecting effective GAIs such as ChatGPT and Gemini to improve academic evaluation and learning in legal education, and pave the way for further innovations in the use of AI.
Co-Authors Abdul Rahim Chairunnisa, Madiha Dzakiyyah Dela Juliarsih Rahman Dewi Juliah Ratnaningsih Eka Julianti Epin Nur Cahya Erlyne Nadhilah Widyaningrum Eva Lestari Ningsih Faulina, Ria Fitriana, Ika Nur Laily Hendrayani, Hendrayani Ika Purnamasari Isnurani Kertanah Komuna, Avelyn Pingkan M Fathurahman Maulana, Muhamad Riyan Mujahidin, Ilham Nina Valentika Nuramaliyah, Nuramaliyah Nurdiana, Dian Nurmayanti, Wiwit Pura Pangruruk , Thesya Atarezcha Pangruruk Putri, Desi Febriani Rif'an, Muhammad Siringoringo, Meiliyani Sri Enny Triwidiastuti Sri Maulidia Permatasari Wiwit Pura Nurmayanti Wiwit Pura Nurmayanti Yuniarti, Desi Zainul Arif