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PENGEMBANGAN MUTU PENGELOLAAN PROGRAM STUDI BERBASIS MONITORING ANALYTIC TOOLS Inna, Suma; Fauziah, Irma; Santoso, Ary
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 14 No 2 (2022): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2022.14.2.5740

ABSTRACT. This paper discusses Monitoring Analytics Tools (MAT) to analyze the management quality of the Mathematics Study Program Faculty of Science and Technology UIN Syarif Hidayatullah Jakarta. Study program management based on Monitoring Analytics Tools (MAT) is one of strategy for building a study program management system based on data-driven and automated analytics. This method is handy in improving the quality of study programs so that they are more measurable, targeted, effective, and efficient in providing excellent services and developments. Monitoring Analytics Tools (MAT) in this study focused on two management quality developments of the study program, namely Monitoring Analytics Tools (MAT) for Lecturer Quality Development in the Learning Process through a Lecturer Evaluation Survey by Students and Monitoring Analytics Tools (MAT) for the Graduate Development through Graduate User Surveys. The results show that the responsiveness dimension (punctuality in learning activities) has the lowest satisfaction index for Lecturer Quality Development. Meanwhile, for the quality of graduates, the dimensions of specific skills (presentation and writing report skills) are the lowest satisfaction index.Keywords: Monitoring Analytic Tools, Quality of Services, Service Satisfaction Survey ABSTRAK. Pengelolaan program studi berbasis Monitoring Analytics Tools (MAT) merupakan salah satu upaya membangun sistem pengelolaan program studi berbasis data driven dan otomation analytics guna menjalankan pelayanan dan pengembangan mutu program studi yang lebih terukur, tepat sasaran, efektif dan efesien. Atas kebutuhan yang sangat tinggi untuk meningkatkan mutu Program Studi dalam rangka mengejar akreditasi Program Studi Matematika menjadi unggul, maka menguji dan mengembangkan Monitoring Analytics Tools pada Program Studi Matematika FST UIN Syarif Hidayatullah sangat diperlukan. Oleh karena itu tujuan dari penelitian ini adalah mengembangkan Monitoring Analytics Tools merupakan suatu proses kompleks yang saling terkait guna menghasilkan MAT yang handal. Monitoring Analytics Tools (MAT) pada penelitian ini difokuskan pada dua pengembangan Mutu Program Studi yaitu Monitoring Analytics Tools (MAT) Pengembangan Mutu Dosen dalam Proses Pembelajaran melalui survey Evaluasi Dosen Oleh Mahasiswa dan Monitoring Analytics Tools (MAT) Pengembangan Lulusan melalui Survei Pengguna Lulusan. Hasil pembahasan menunjukkan bahwa dimensi responsieness (ketepatan waktu dalam menjalankan aktivitas pembelajaran) menunjukkan indeks kepuasan paling rendah. Sementara untuk mutu lulusan, dimensi keterampilan khusus menunjukkan indeks kepuasan pengguna lulusan rendah, yaitu kemampuan presentasi para lulusan dan kemampuan menulis laporan.Kata Kunci: Monitoring Analytic Tools, Mutu Layanan, Surver Kepuasan Layanan

PENYELESAIAN MODEL ALIRAN FLUIDA NAVIER-STOKES-KORTEWEG DI HALF-SPACE PADA RUANG DIMENSI TIGA Alfiyyah, Rizka; Inna, Suma; Liebenlito, Muhaza
MES: Journal of Mathematics Education and Science Vol 10, No 1 (2024): Edisi Oktober (Progress)
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/mes.v10i1.9513

Model Navier-Stokes-Korteweg adalah model yang menggambarkan aliran fluida dua fase dalam kondisi transisi di antarmuka kedua fase tersebut yang sering disebut sebagai efek kapiler. Artikel ini bertujuan untuk mencari operator solusi dari model Navier-Stokes-Korteweg di half-space pada dimensi tiga dengan syarat batas slip, melalui beberapa tahapan seperti mereduksi sistem persamaan resolvent tak homogen dari model Navier-Stokes-Korteweg menjadi sistem persamaan resolvent homogen dan melakukan transformasi fourier parsial pada sistem persamaan resolvent homogen tersebut untuk memperoleh sistem persamaan diferensial biasa. Berdasarkan artikel ini ditunjukkan bahwa terdapat operator solusi dari persamaan resolvent model Navier-Stokes-Korteweg di dengan kondisi batas slip untuk kasus koefisien .

Active learning on Indonesian Twitter sentiment analysis using uncertainty sampling Liebenlito, Muhaza; Inayah, Nur; Choerunnisa, Esti; Sutanto, Taufik Edy; Inna, Suma
Journal of Applied Data Sciences Vol 5, No 1: JANUARY 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i1.144

Nowadays, sentiment analysis research in social media is rapidly developing. Sentiment analysis typically falls under supervised learning, which requires annotating data. However, the annotation process for sentiment analysis tasks is notoriously time-consuming. Fortunately, an effective strategy to overcome this challenge has emerged, known as active learning. Active learning involves labeling only a small subset of the dataset, leaving the rest for annotation through sampling strategies. This study focuses on comparing two active learning strategies: random sampling and boundary sampling. These strategies are applied to machine learning models such as logistic regression and random forests. In addition, we present an evaluation of the model performance and data savings achieved by implementing these strategies in the context of traditional machine learning for sentiment analysis on Twitter. The dataset considered consists of two labels: positive and negative sentiments. The results of our investigation show that active learning can significantly reduce the amount of training data required, saving up to 65% of the total training data required to achieve peak model accuracy. The most successful model identified uses a random forest with a margin sampling strategy, yielding an accuracy of 81.12% and an F1 score of 88.60%. This research highlights the effectiveness of active learning strategies in sentiment analysis, demonstrating their potential to improve model performance and resource efficiency. The results underscore the viability of employing active learning methods, particularly the combination of random forest models with margin sampling, for more efficient sentiment analysis in social media.

Pengaruh Variabel Eksogen terhadap Pemodelan Curah Hujan di Kota Bandung Mahmudi; Mehri, Hilmah Amalia; Inna, Suma
Jurnal Absis: Jurnal Pendidikan Matematika dan Matematika Vol. 6 No. 2 (2024): Jurnal Absis
Publisher : Program Studi Pendidikan Matematika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/absis.v6i2.2375

This research is motivated by the significant role of rainfall as a natural occurrence that has a significant impact on various sectors. The main objective of this study is to evaluate the influence of exogenous variables in rainfall forecasting by comparing the accuracy of SARIMA, SARIMAX, hybrid SARIMA-ANN, and hybrid SARIMAX-ANN models. The initial modeling of this research did not involve exogenous variables and resulted in a MAPE (Mean Absolute Percentage Error) of 43,65% for the SARIMA model and 42,86% for the hybrid SARIMA-ANN model. The findings show that incorporating the exogenous variable of sunlight duration positively contributes to improving the accuracy of rainfall forecasting using the SARIMAX model with a MAPE of 28.69% and the hybrid SARIMAX-ANN model with a MAPE of 27,03%. This research contributes to the development of rainfall forecasting methods by incorporating other influencing variables.

Analysis of the linear navier stokes korteweg model with neumann boundary conditions in three dimensional half-space Khasanah, Dwi Windari Nur; Inna, Suma; Wijaya, Madona Yunita; Hasanah, Sri Indriati
Jurnal Absis: Jurnal Pendidikan Matematika dan Matematika Vol. 7 No. 1 (2024): Jurnal Absis (In Press)
Publisher : Program Studi Pendidikan Matematika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/absis.v7i1.2589

This study discusses the solution of the Navier-Stokes Korteweg model, which describes two-phase fluid flow with capillary effects, with Neumann boundary conditions in the half-space. The main objective is to detail the resolution process of the resolvent equation system in the half-space related to the Navier-Stokes Korteweg model with Neumann boundary conditions. The resolution is carried out in several steps. First, the resolvent equation system is reduced using even and odd extensions. Then, a partial Fourier transform is applied, resulting in a simpler ordinary differential equation. The findings of this research indicate the existence of a solution operator for the resolvent equation of the Navier-Stokes Korteweg model with Neumann boundary conditions in the half-space. This solution applies for two cases involving the coefficients, depending on certain conditions related to the fluid properties.

PENYELESAIAN MODEL ALIRAN FLUIDA NAVIER-STOKES-KORTEWEG DI HALF-SPACE PADA RUANG DIMENSI TIGA Alfiyyah, Rizka; Inna, Suma; Liebenlito, Muhaza
MES: Journal of Mathematics Education and Science Vol 10, No 1 (2024): Edisi Oktober
Publisher : Universitas Islam Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30743/mes.v10i1.9513

Model Navier-Stokes-Korteweg adalah model yang menggambarkan aliran fluida dua fase dalam kondisi transisi di antarmuka kedua fase tersebut yang sering disebut sebagai efek kapiler. Artikel ini bertujuan untuk mencari operator solusi dari model Navier-Stokes-Korteweg di half-space pada dimensi tiga dengan syarat batas slip, melalui beberapa tahapan seperti mereduksi sistem persamaan resolvent tak homogen dari model Navier-Stokes-Korteweg menjadi sistem persamaan resolvent homogen dan melakukan transformasi fourier parsial pada sistem persamaan resolvent homogen tersebut untuk memperoleh sistem persamaan diferensial biasa. Berdasarkan artikel ini ditunjukkan bahwa terdapat operator solusi dari persamaan resolvent model Navier-Stokes-Korteweg di dengan kondisi batas slip untuk kasus koefisien .

Analysis of the linear navier stokes korteweg model with neumann boundary conditions in three dimensional half-space Khasanah, Dwi Windari Nur; Inna, Suma; Wijaya, Madona Yunita; Hasanah, Sri Indriati
Jurnal Absis: Jurnal Pendidikan Matematika dan Matematika Vol. 7 No. 1 (2024): Jurnal Absis
Publisher : Program Studi Pendidikan Matematika Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/absis.v7i1.2589

This study discusses the solution of the Navier-Stokes Korteweg model, which describes two-phase fluid flow with capillary effects, with Neumann boundary conditions in the half-space. The main objective is to detail the resolution process of the resolvent equation system in the half-space related to the Navier-Stokes Korteweg model with Neumann boundary conditions. The resolution is carried out in several steps. First, the resolvent equation system is reduced using even and odd extensions. Then, a partial Fourier transform is applied, resulting in a simpler ordinary differential equation. The findings of this research indicate the existence of a solution operator for the resolvent equation of the Navier-Stokes Korteweg model with Neumann boundary conditions in the half-space. This solution applies for two cases involving the coefficients, depending on certain conditions related to the fluid properties.

Studi Empiris Model BERT dan DistilBERT Analisis Sentimen pada Pemilihan Presiden Indonesia Mahira Putri; Sutanto, Taufik Edy; Inna, Suma
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i5.3445

Peningkatan jumlah pengguna media sosial di Indonesia sejak tahun 2014 menyebabkan data yang dihasilkan semakin besar dan kompleks, sehingga komputasi yang diperlukan untuk mengolahnya juga semakin besar. Untuk melakukan komputasi pada data yang besar diperlukan model yang kompatibel, efektif, dan efisien. Penelitian ini adalah kajian numerik dari dua model terbaik Deep Learning saat paper ini ditulis, yaitu BERT dan DistilBERT pada kasus analisis sentimen menggunakan ratusan ribu tweet terkait pemilihan presiden Indonesia tahun 2014 dan 2019. Analisis yang dilakukan meliputi waktu eksekusi dan konsumsi memori. Pada model dengan nilai hyperparameter optimal, tercatat bahwa DistilBERT melakukan proses pelatihan dan prediksi 84% lebih cepat dengan penggunaan memori GPU 79% lebih efisien dengan nilai akurasi tidak terpaut jauh, yaitu 0.89 dan 0.85 untuk BERT dan DistilBERT. Hasil kajian ini dapat digunakan untuk memperkirakan besarnya sumberdaya komputasi atau biaya yang dibutuhkan ketika menggunakan model BERT atau DistilBERT pada data yang besar.

Indonesia’s total fertility rate (TFR) using the brown and holt double exponential smoothing with grid search Rahma, Chelsea Fatihah; Fitriyati, Nina; Inna, Suma; Adjie, Dharma Syadhi Putra
Desimal: Jurnal Matematika Vol. 8 No. 1 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v8i1.26332

The Brown and Holt DES method effectively captures trends in time-series data. Its forecasting accuracy heavily depends on the selection of optimal smoothing parameters. Often, the smoothing parameters are selected manually using trial and error methods. This method is time-consuming, unsystematic, prone to bias, not scalable, less reproducible, and increases the risk of overfitting or underfitting. To overcome these problems, in this study, we propose optimization of smoothing parameters using Grid Search. This new approach will be applied to predict Indonesia’s TFR. Grid Search optimization is employed to systematically explore the parameter space and identify the best combination that minimizes forecasting errors. To ensure model robustness, cross-validation is implemented, allowing the evaluation of model performance across multiple training and validation splits. The results show that the Holt DES method with Grid Search is more accurate than the Brown DES with Grid Search, with the smallest Mean Absolute Percentage Error (MSE) value of 0.00972 at and . Predictions with Holt DES with Grid Search show a downward trend in the national TFR until 2027, potentially falling below the ideal level of 2.1. TFR predictions at the provincial level show pattern variations, with several regions experiencing significant declines. The difference in results between the Brown and Holt methods emphasizes the importance of optimizing smoothing parameters and selecting an appropriate population-analysis prediction model to support demographic policy.

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