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All Journal Media Statistika CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Infinity Kubik Desimal: Jurnal Matematika IndoMath: Indonesia Mathematics Education BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Otomasi Kontrol dan Instrumentasi JURNAL TIARSIE Teorema: Teori dan Riset Matematika Jambura Journal of Mathematics Eksakta : Berkala Ilmiah Bidang MIPA Kumawula: Jurnal Pengabdian Kepada Masyarakat JPMI (Jurnal Pembelajaran Matematika Inovatif) SEPREN: Journal of Mathematics Education and Applied KUBIK: Jurnal Publikasi Ilmiah Matematika Euclid Jurnal Matematika Integratif JNPM (Jurnal Nasional Pendidikan Matematika) Matematika IndoMath: Indonesia Mathematics Education Kreano, Jurnal Matematika Kreatif Inovatif Jurnal Infinity Jurnal Pendidikan MIPA
Kusuma, Dianne Amor
Departemen Matematika FMIPA Unpad
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture 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 Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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The students' mathematics self-regulated learning and mathematics anxiety based on the use of chat GPT, music, study program, and academic achievement Delima, Nita; Kusuma, Dianne Amor; Paulus, Erick
Jurnal Infinity Vol 13 No 2 (2024): VOLUME 13, NUMBER 2, INFINITY
Publisher : IKIP Siliwangi and I-MES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22460/infinity.v13i2.p349-362

Abstract

In the era of society 5.0, the reach of student learning resources is increasingly wider, with the internet and free AI-based search engines. The use of music during learning is a way for students to increase learning motivation. This research aims to find out: (1) Whether ChatGPT technology and music used during independent study have an impact on students' Mathematics Self-Regulated Learning (MSRL) and Mathematics Anxiety (MA); (2) Whether MSRL and MA have an association with the study program students choose; and (3) Whether MSRL and MA have an association with students' academic achievement. This research uses a correlational descriptive research method. The data collection technique uses a survey, implementing Google Forms. The respondents of this research were students at several universities in Indonesia. The research results show a significant difference in MSRL between students who use ChatGPT and students who do not use ChatGPT during independent learning. However, there was no significant difference in MSRL between students who listened to music and those who did not listen to music during independent learning. There was no significant difference in MA between students who used ChatGPT and those who did not use ChatGPT during independent study. There was no significant difference in MA between students who listened to music and those who did not listen to music during independent study. There is a significant association between MSRL and the origin of the student's Study Program, but there is no significant association between MA and the origin of the Study Program. There is no significant association between MSRL and Academic Achievement. There is no association between MA and students' Academic Achievement.
Implementasi Convolutional Neural Network Berbasis Model untuk Klasifikasi Kelayakan Citra Permen Jahe pada Perangkat Android Dwipriyoko, Estiyan; Pamungkas, Fabio Syechan; Kusmaya , Kusmaya; Kusuma, Dianne Amor
Jurnal Otomasi Kontrol dan Instrumentasi Vol 17 No 1 (2025): Jurnal Otomasi Kontrol dan Instrumentasi
Publisher : Pusat Teknologi Instrumentasi dan Otomasi (PTIO) - Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/joki.2025.17.1.5

Abstract

Ginger is one of the primary ingredients for ginger candy. The manual process of evaluating the feasibility of ginger candy at the Tasacika Company is still prone to errors and is less efficient. This research aims to develop a Convolutional Neural Network model for classifying the feasibility of ginger candy and create an Android-based application that facilitates this process. The research method uses an Experimental approach. Model development is carried out with a Convolutional Neural Network with the MobileNetV2 architecture, using the Cross Industry Standard Process for Data Mining methods. Software development is done using the Prototyping method. This research used a dataset of images taken directly from the Tasacika Company's ginger candy factory. The model is trained and tested using Google Colab with the Python programming language and the TensorFlow and Keras libraries. Implementation is carried out using Kotlin and XML. It can be concluded that the research has succeeded in developing a ginger candy feasibility classification model. The test results show that the developed model is effective in minimizing human error in the process of checking the feasibility of ginger candy. This research also succeeded in developing an Android-based ginger candy feasibility classification application
Rainfall Model Using Principal Component Regression Analysis with R Software in Sulawesi Yunia, Annisa Alma; Kusuma, Dianne Amor; Suhandi, Bambang; Ruchjana, Budi Nurani
Desimal: Jurnal Matematika Vol. 3 No. 3 (2020): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v3i3.6108

Abstract

Indonesia is a tropical country that has two seasons, rainy and dry. Nowadays, the earth is experiencing the climate change phenomenon which causes erratic rainfall. The rainfall is influenced by several factors, one of which is the local scale factor. This research was aimed to build a rainfall model in Sulawesi to find out how the rainfall relationship with local scale factor in Sulawesi. In this research, the data used were secondary data which consisted of 15 samples with 6 variables from Badan Pusat Statistik (BPS). The limitation of the sample size in this study was due to the limited secondary data available in the field. The data was processed using Principal Component Regression Analysis. The first step was reducing local scale factor variables so that the principal component variable could be obtained that can explain variability from the original data which then that variable was analyzed using principal regression analysis. The data were analyzed by utilizing R Studio software. The results show that two principal component variables can explain 75.2% of the variability of original data and only one principal component variable that was significant to the rainfall variable. The regression model explained that the relationship between rainfall, humidity, air temperature, air pressure, and solar radiation was in the same direction while the relationship between rainfall and wind velocity was not in the same direction. Overall, the results of the study provided an overview of the application of the Principal Component Regression analysis to model the rainfall phenomenon in the Sulawesi region using the R program.
MODEL SPACE TIME AUTOREGRESSIVE INTEGRATED (STARI) UNTUK DATA DEBIT AIR SUNGAI CITARUM DI PROVINSI JAWA BARAT Alawiyah, Mutik; Kusuma, Dianne Amor; Ruchjana, Budi Nurani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 14 No 1 (2020): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (911.908 KB) | DOI: 10.30598/barekengvol14iss1pp147-158

Abstract

Rainfall in West Java during the rainy season is quite high. This causes the area around the watershed to experience flooding. However, in the dry season the Citarum watershed experiences drought. Changes in the Citarum river water discharge from time to time is not only influenced by time but also influenced by the location around it. To forecast the Citarum river water discharge data, the Space Time Autoregressive Integrated (STARI) model can be used. In this study, the STARI model was applied to the Citarum river water discharge data at all four observation sites. Based on the stationary data, it showed that the data is not stationary, so the differencing process must first be done 1 time. The identification of the order of the AR model was one because the PACF plot was truncated in lag 1. The spatial lag used in this study was the spatial lag of order 2, so the Citarum river water discharge could be predicted with the STARI model. Estimation of STARI) model parameters with a uniform weight matrix was ​estimated by the MLE method with the help of R and S-Plus 8.0 softwares. STARI model with MAPE less than 10% was used for predicting Citarum river water discharge data for the four observation locations, thus the STARI model can be recommended to predict Citarum river water discharge data.
COMPARISON OF AUTOREGRESSIVE MODEL WITH MISSING DATA TREATED USING ORDINARY LEAST SQUARES AND INTERPOLATION WITH WEIGHTING METHOD Akmaliah, Syifani; Kusuma, Dianne Amor; Ruchjana, Budi Nurani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (526.3 KB) | DOI: 10.30598/barekengvol16iss2pp751-760

Abstract

Bandung is committed to contributing to the achievement of the Sustainable Development Goals (SDGs) in Indonesia. One of the efforts that can be made to support the 13th pillar of SDGS regarding climate change is to forecast the air temperature of Bandung City in the future. One of the models that can be used for forecasting air temperature data in Bandung is the Autoregressive (AR) model. Based on BMKG data, often the time series data obtained has missing data. Therefore, in order to do a good time series analysis, it is necessary to make an effort to correct the missing data. The purpose of this research was to examine the procedure for overcoming missing data in the AR model using the Ordinary Least Squares (OLS) method and Interpolation with Weighting, which was applied to forecasting the average air temperature data in the city of Bandung. The research methodology followed the Box-Jenkins 3-step procedure. The first-order AR estimation parameter model was estimated using the OLS method and then used to overcome missing data using both methods with weighting using R software. Both methods resulted in an estimated value of 0.9991 and the same Mean Average Percentage Error (MAPE) value of 2,459% with very accurate criteria. Therefore, to overcome the missing data on the average air temperature data in the city of Bandung with a parameter estimator close to one, we got the same result for both methods.
COMBINATION OF ETHNOMATHEMATICS AND THE MOZART EFFECT TO IMPROVE PROBLEM-SOLVING SKILLS AND MATHEMATICAL DISPOSITION Kusuma, Dianne Amor; Ruchjana, Budi Nurani; Widodo, Sri Adi; Dwipriyoko, Estiyan
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp1155-1166

Abstract

The background of this research is that student learning outcomes in analytical geometry lecture during the transition from pandemic to Covid-19 endemic are still low, which is due to a lack of student interest in learning, and they are still accustomed to online learning, thus having an impact on their low problem-solving skills and mathematical disposition. This research aims to determine to what extent the implementation of ethnomathematics and the Mozart effect can improve students' problem-solving skills and mathematical disposition in analytical geometry lecture during the transition from pandemic to endemic COVID-19, so the research is important to do. The implementation of ethnomathematics and the Mozart effect in mathematics learning is unique because it is a combination of learning approaches that have never been used before in Indonesia and other countries. The research method used was a quasi-experimental non-equivalent control group design because this research was experimental and sample determination was not carried out randomly, but using purposive sampling technique on the second-semester students of the mathematics undergraduate program, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran. The instruments used in this study were problem-solving skills test, mathematical disposition scale, and students’ attitude questionnaire toward learning with the implementation of ethnomathematics and the Mozart effect. The results showed that: (1) problem-solving skills of students who received learning by implementing ethnomathematics and the Mozart effect are better than students who achieved direct instruction; (2) mathematical disposition of students who received learning by implementing ethnomathematics and the Mozart effect is better than students who achieved direct instruction; and (3) students are interested and motivated to learn mathematics by implementing ethnomathematics and the Mozart effect. This research concludes that the implementation of ethnomathematics and the Mozart effect can improve students' problem-solving skills and mathematical disposition in analytical geometry lecture during the transition period from the pandemic to endemic COVID-19. It can be seen from good average post test scores achieved by students.
Aplikasi Pemantauan Stok Berbasis Internet of Things dan Cloud Computing Mutmainah, Anisa Qolbiah; Haryana, KM. Syarif; Dwipriyoko, Estiyan; Kusuma, Dianne Amor
Jurnal Tiarsie Vol 22 No 1 (2025): Jurnal TIARSIE 22.1
Publisher : Fakultas Teknik Universitas Langlangbuana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32816/tiarsie.v22i1.260

Abstract

Pengelolaan stok bahan baku di Kafe Jus Gedong Bandung masih dilakukan secara manual sehingga menimbulkan ketidaktepatan data, keterlambatan pemantauan, dan potensi pemborosan. Penelitian ini bertujuan mengembangkan aplikasi pemantauan stok berbasis Internet of Things (IoT) dan cloud computing. Sistem memanfaatkan sensor ultrasonik dan mikrokontroler ESP8266 untuk mendeteksi ketersediaan stok, dengan informasi real-time ditampilkan melalui LCD, LED, buzzer, serta tersimpan pada platform ThingSpeak. Notifikasi otomatis dikirimkan melalui Telegram, dan data stok dapat diekspor dalam format Excel. Metode penelitian menggunakan pendekatan eksperimen dengan model prototyping berbasis umpan balik pengguna. Hasil pengujian menunjukkan sistem mampu membaca stok secara akurat, memberikan peringatan saat stok menipis, menampilkan data real-time secara stabil, serta mendukung dokumentasi stok. Aplikasi ini meningkatkan efisiensi pemantauan dan pengambilan keputusan berbasis data, serta berpotensi untuk diimplementasikan pada usaha sejenis.
Penerapan Perangkat Lunak RStudio untuk Penaksiran Parameter Model Spatial Autoregressive Salsabil, Tsuroyya; Kusuma, Dianne Amor; Ruchjana, Budi Nurani
KUBIK Vol 8 No 1 (2023): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v8i1.30037

Abstract

Research and analysis that are not only based on time (temporal) but also on space (spatial) require tools in the form of software to ensure that the data analysis and processing yield good, fast, and accurate results. One of the software tools that can be used for this purpose is RStudio software. The advantages of RStudio include being open-source software (OSS), which can be used freely without cost, and it has many packages and functions that can facilitate data processing. One of the spatial-based analyses is spatial data analysis. The structure within RStudio allows users to call functions related to spatial data analysis, perform computations with sparse matrices (matrices with many zero values), such as spatial weight matrices, estimation of spatial model parameters, and so on. This research examines the application of RStudio software in estimating the parameters of a first-order Spatial Autoregressive (SAR) model using the Maximum Likelihood Estimation (MLE) method on the data of the designation of Intangible Cultural Heritage (ICH) in Indonesia. Based on the results of applying RStudio software, a first-order SAR model with a Queen contiguity weight matrix for the categories of Traditional Customs, Rituals, and Celebrations (TCRC) and Performing Arts (PA) with the minimum Akaike Information Criterion (AIC) value and maximum pseudo- value was obtained for predicting the designation data of ICH in Indonesia. The application of RStudio software to the first-order SAR model for the designation data of ICH in Indonesia speeds up and simplifies calculations, making it suitable as a recommendation for relevant agencies such as the Department of Culture, Tourism, Youth, and Sports (Disbudparpora). 
Penerapan Model Geographically Weighted Regression pada Data Penetapan Warisan Budaya Takbenda di Indonesia Pratomo, Firdaus Ryan; Kusuma, Dianne Amor; Ruchjana, Budi Nurani
KUBIK Vol 9 No 1 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v9i1.33492

Abstract

Intangible Cultural Heritage (WBTb) determination data in Indonesia is a cultural investment that needs to be preserved. One of the efforts to preserve WBTb is to determine the cultural preservation factors that influence the WBTb determination data in Indonesia. These factors include Percentage of Population Watching Performances/Art Exhibitions (PPWP), Percentage of Population Using Regional Languages (PPURL), and Percentage of Households Using Traditional Products (PHUTP). However, the different cultural wealth in each province results in spatial heterogeneity, resulting in differences in the determination of cultural preservation factors in each province. This determination can be done with the Geographically Weighted Regression (GWR) model. This study aims to apply the GWR model with Fix Gaussian Kernel, Fix Bisquare Kernel, and Fix Tricube Kernel weighting to determine cultural preservation factors in WBTb determination data in Indonesia so that it can be known what cultural preservation factors are most influential in each region. The research findings show the existence of spatial heterogeneity only in the category of WBTb designation data for Performing Arts (PA) and Oral Expression Tradition (OET), as well as different GWR models in each province that reflect differences in cultural preservation factors. Evaluation with the coefficient of determination shows that the GWR model with the Fix Gaussian Kernel weighting function is the best model for the PA category. 
Implementasi Cooperative Learning Tipe Group Investigation untuk Meningkatkan Kemampuan Representasi Matematis dan Kemandirian Belajar Kusuma, Dianne Amor; Angraini, Lilis Marina; Dwipriyoko, Estiyan
Sepren Vol 7 No 01 (2025): Edisi November 2025
Publisher : Prodi Pendidikan Matematika FKIP Universitas HKBP Nommensen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36655/sepren.v7i01.1987

Abstract

Hasil belajar yang dicapai mahasiswa dalam matematika dipengaruhi oleh beberapa kemampuan matematis yang mereka kuasai, salah satunya adalah kemampuan representasi matematis. Tujuan dari penelitian ini adalah menganalisis sejauhmana implementasi cooperative learning tipe group investigation (GI) dapat meningkatkan kemampuan representasi matematis dan kemandirian belajar mahasiswa. Penelitian ini menggunakan metode quasi experimental non-equivalent control group design, serta instrumen yang digunakan adalah tes kemampuan representasi matematis yang berbentuk uraian dan skala kemandirian belajar. Hasil dari penelitian ini memperlihatkan bahwa implementasi cooperative learning tipe GI dapat meningkatkan kemampuan representasi matematis mahasiswa dan berdampak positif terhadap kemandirian belajar mahasiswa.
Co-Authors Akmaliah, Syifani Alawiyah, Mutik Amelia Annis Deshinta Ayuningtyas, Annis Deshinta Annisa Alma Yunia Annisafiya, Nadira Arif Rahman Azril Bambang Suhandi Budi Nurani Ruchjana Dwipriyoko, Estiyan Edi Kurniadi Endang Rusyaman Erick Paulus Erick Paulus Estiyan Dwipriyoko Estiyan Dwipriyoko Firdaniza Firdaniza Hutauruk, Agusmanto J. B. Ika Wulandari Jaja Jaja JAJA, JAJA KM. Syarif Haryana Kusmaya , Kusmaya Lilis Marina Angraini Mohammad Ihsan Muchamad Subali Noto Mutmainah, Anisa Qolbiah Nita Delima Nurcaweda Riztria Adinda Nurul Gusriani, Nurul Nurul Ikhsan Karimah Oktaviansyah, Eka Pamungkas, Fabio Syechan Pratiwi, Dian Meilin Pratomo, Firdaus Ryan Putri, Salsabila Eka Salsabil, Tsuroyya Salsabila Salsabila Sri Adi Widodo Suhandi, Bambang Syarif, K.M. Tsanawafa, Almeira Tsuroyya Salsabil Wahyu Gunawan Widjajani Widjajani Widowati Pusporini, Widowati Yunia, Annisa Alma