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Edukasi dan Sosialisasi Pencegahan Virus Covid-19 Berawal Dari Diri Sendiri Di Desa Kampung Anyar Kecamatan Glagah Kabupaten Banyuwangi Feby Indriana Yusuf; Dzurotul Mutimmah; Novi Prayekti; Reny Eka Evi Susanti; Fitri Nurmasari
JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) Vol 5 No 1 (2021): Jati Emas (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat)
Publisher : Dewan Pimpinan Daerah (DPD) Perkumpulan Dosen Indonesia Semesta (DIS) Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36339/je.v5i1.405

The Corona virus is one of the viruses that has caused SARS, MERS, and Covid-19. Banyuwangi Regency is one of the areas with a graph of the development of Covid-19 which shows a fairly high increase. Based on data from the corona.banyuwangikab.go.id website in August, 237 people were declared infected with Covid-19, in December there were 3963 people. This is the main concern of many parties, especially local governments, in an effort to prevent the spread of the Covid-19 virus. Glagah sub-district is one of the sub-districts located in the western part of the Banyuwangi region. Kampung Anyar Village is one of the villages in Glagah District. Many people in Kampung Anyar village still do not comply with health protocols, so that good activities in the form of socialization through banners, through social networks and through other community activities are needed to be able to successfully break the chain of the Covid-19 virus. In addition to socialization related to health protocols, education to residents must be provided so that in implementing health protocols it can be carried out according to rules and recommendations, so that the community, through the smallest scope, namely families, can protect and protect each other from being infected with the Covid-19 virus. This activity raises the awareness of the village community in Kampung Anyar that early prevention is not as complicated as heard through social media or television, besides that women who participate in these activities agree and are committed to being the front guard in their families in preventing the spread of Covid-19.

Powerpoint-based educational games on flat face three dimensional objects combined volume learning Nurma Haya Julianti; Rachmaniah Mirza Hariastuti; Feby Indriana Yusuf
Math Didactic: Jurnal Pendidikan Matematika Vol 8 No 3 (2022)
Publisher : STKIP PGRI Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33654/math.v8i3.1935

Lemahnya kemampuan visualisasi siswa menyebabkan siswa kesulitan menginterpretasi bentuk bangun ruang. Oleh karena itu, diperlukan media pembelajaran yang dapat membantu siswa dalam mempelajari bangun ruang sisi datar, salah satunya dengan memanfaatkan PowerPoint sebagai game edukasi. Penelitian ini bertujuan mendeskripsikan kualitas hasil pengembangan game edukasi berbasis PowerPoint pada materi volume gabungan bangun ruang sisi datar di kelas VIII SMP. Penelitian pengembangan dilakukan dengan model ADDIE. Subjek penelitian ini adalah 60 siswa kelas VIII SMPIT Al-Uswah Banyuwangi. Pengumpulan data dilakukan dengan metode wawancara, observasi, kuesioner, tes, dan dokumentasi. Analisis data dilakukan dengan metode gabungan (kuantitatif dan kualitatif). Hasil penelitian menunjukkan bahwa game edukasi valid dengan nilai rata-rata 4,39, praktis dengan nilai rata-rata sebesar 4,67 serta respon siswa termasuk kategori cukup baik dengan nilai rata-rata sebesar 3,94, serta tidak efektif sesuai analisis hasil tes siswa yang menunjukkan . Sehingga kualitas hasil pengembangan game edukasi berbasis PowerPoint pada materi volume gabungan bangun ruang sisi datar belum baik dan perlu dilakukan perbaikan. Perbaikan dapat dilakukan khususnya dalam hal suara agar dapat terdengar lebih jelas.

METODE TWO STAGE LEAST SQUARE (Studi Kasus di Kabupaten Banyuwangi) Feby Indriana Yusuf
TRANSFORMASI Vol 7 No 1 (2023): TRANSFORMASI: Jurnal Pendidikan Matematika dan Matematika
Publisher : Pendidikan Matematika FMIPA Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/tr.v7i1.3173

The Two-Stage Least Squares (2SLS) method is used to ascertain the relationship between simultaneous equations, where each dependent variable in the model has a simultaneous relationship. This study explains the process that can be undertaken to estimate simultaneous equation models using the 2SLS method. The case study selected is about the relationship between residential area variables and employment variables. Based on the analysis results, the final conclusion is that the 2SLS steps have been executed, and there is a significant relationship between the residential area and the employment of the population in BanyuwangiRegency.

Powerpoint-based educational games on flat face three dimensional objects combined volume learning Julianti, Nurma Haya; Hariastuti, Rachmaniah Mirza; Yusuf, Feby Indriana
Math Didactic: Jurnal Pendidikan Matematika Vol 8 No 3 (2022): September - Desember 2022
Publisher : Universitas PGRI Kalimantan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33654/math.v8i3.1935

Lemahnya kemampuan visualisasi siswa menyebabkan siswa kesulitan menginterpretasi bentuk bangun ruang. Oleh karena itu, diperlukan media pembelajaran yang dapat membantu siswa dalam mempelajari bangun ruang sisi datar, salah satunya dengan memanfaatkan PowerPoint sebagai game edukasi. Penelitian ini bertujuan mendeskripsikan kualitas hasil pengembangan game edukasi berbasis PowerPoint pada materi volume gabungan bangun ruang sisi datar di kelas VIII SMP. Penelitian pengembangan dilakukan dengan model ADDIE. Subjek penelitian ini adalah 60 siswa kelas VIII SMPIT Al-Uswah Banyuwangi. Pengumpulan data dilakukan dengan metode wawancara, observasi, kuesioner, tes, dan dokumentasi. Analisis data dilakukan dengan metode gabungan (kuantitatif dan kualitatif). Hasil penelitian menunjukkan bahwa game edukasi valid dengan nilai rata-rata 4,39, praktis dengan nilai rata-rata sebesar 4,67 serta respon siswa termasuk kategori cukup baik dengan nilai rata-rata sebesar 3,94, serta tidak efektif sesuai analisis hasil tes siswa yang menunjukkan . Sehingga kualitas hasil pengembangan game edukasi berbasis PowerPoint pada materi volume gabungan bangun ruang sisi datar belum baik dan perlu dilakukan perbaikan. Perbaikan dapat dilakukan khususnya dalam hal suara agar dapat terdengar lebih jelas.

Intrinsic Cognitive Load in Online Learning Model of School Mathematics 1 in Covid-19 Pandemic Period Yohanes, Barep; Yusuf, Feby Indriana
JIPM (Jurnal Ilmiah Pendidikan Matematika) Vol 9, No 2 (2021)
Publisher : Universitas PGRI Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25273/jipm.v9i2.7292

The study aims at determining the emergence of intrinsic cognitive load in online learning models of School Mathematics 1 in Covid-19 pandemic period. This research is a descriptive qualitative one the data of which are obtained from observation sheets, questionnaires and interview results. Validity checking uses the triangulation method. The results of the study show that the intrinsic cognitive load is caused by the interactivity and isolated/interacting elements contained in the learning process. Elements of interactivity are in the form of terms or concepts in Mathematics learning. These terms or concepts, for examples, are the meaning of Knowledge, Standard Measurement, Mathematical Approach, Intertwined Principles, Content, Context, Competence, PISA Learning Concepts, De-conceptualization, Systems Approach, Conceptual Approach, etc. Isolated/interacting elements are seen from looking for examples of implementation in the real world and actualization of events in Indonesia. An example of implementation in the real world is an element that interacts in real situations in the learning practice of Mathematics.

Penerapan Collective Risk Model dalam Penentuan Premi Asuransi Bencana Alam Yusuf, Feby Indriana; Adi, Puti Zakiyah Raisa; Saragih, Trecy Elisabet Tioralina
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 12 Issue 2 December 2024
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v12i2.28632

Indonesia is prone to natural disasters such as volcanic eruptions, earthquakes, and tsunamis due to tectonic activity involving the Indo-Australian and Eurasian plates. Therefore, the government introduced natural disaster insurance in 2018 to mitigate financial losses caused by such events. This study employs the Collective Risk Model (CRM) to determine premium rates. The Poisson process and Gamma distribution are utilized to estimate the frequency and severity of natural disasters. Estimation is performed using Maximum Likelihood Estimation (MLE), while premiums are calculated based on the expected value and variance of aggregate risk using the Expected Value Principle and the Standard Deviation Principle. The results show that the expected value and variance of claim frequency are both . Furthermore, claims for losses follow the Gamma distribution, with an expected value and variance of and . The mean and variance of aggregate claims are Rp and Rp . The Standard Deviation Principle produces lower premiums than the Expected Value Principle under the same loading factor.

Health Risk Classification Using XGBoost with Bayesian Hyperparameter Optimization Anam, Syaiful; Purwanto, Imam Nurhadi; Mahanani, Dwi Mifta; Yusuf, Feby Indriana; Rasikhun, Hady
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 3 (2025): June 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i3.6307

Health risk classification is important. However, health risk classification is challenging to address using conventional analytical techniques. The XGBoost algorithm offers many advantages over the traditional methods for risk classification. Hyperparameter Optimization (HO) of XGBoost is critical for maximizing the performance of the XGBoost algorithm. The manual selection of hyperparameters requires a large amount of time and computational resources. Automatic HO is needed to avoid this problem. Several studies have shown that Bayesian Optimization (BO) works better than Grid Search (GS) or Random Search (RS). Based on these problems, this study proposes health risk classification using XGBoost with Bayesian Hyperparameters Optimization. The goal of this study is to reduce the time required to select the best XGBoost hyperparameters and improve the accuracy and generalization of XGBoost performance in health risk classification. The variables used were patient demographics and medical information, including age, blood pressure, cholesterol, and lifestyle variables. The experimental results show that the proposed approach outperforms other well-known ML techniques and the XGBoost method without HO. The average accuracy, precision, recall and f1-score produced by the proposed method are 0.926, 0.920, 0.928, and 0.923, respectively. However, improvements are needed to obtain a faster and more accurate method in the future.

Implementasi Metode Bayesian untuk Menghitung Premi Produk Asuransi Kendaran Bermotor dengan Pendekatan Monte Carlo Markov Chain Situmorang, Boy Nathanael; A’la, Kevina Alal; Arvianti, Aurellia; Yusuf, Feby Indriana; Handamari, Endang Wahyu
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 2 August 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i2.32930

Accurate premium determination is a fundamental aspect of risk management in motor vehicle insurance. This study implements the Bayesian method using a Markov Chain Monte Carlo (MCMC) approach to calculate the net premium. The aggregate claim model is constructed from a claim frequency distribution (Poisson) and a claim severity distribution (Generalized Extreme Value (GEV)), with the GEV distribution specifically chosen to model extreme claim risk. The analysis utilizes generated data for the period 2018–2024, with parameters derived from the historical data of PT Asuransi Jasa Indonesia Purwokerto (2013–2017). Parameter estimation, performed via OpenBUGS software, was validated to have achieved good convergence (MC-error ). Based on the estimated parameters, a premium of IDR 397.502.000 was obtained, calculated using the net premium principle from the expected value of aggregate claims. These results demonstrate that the Bayesian MCMC approach is effective for producing a robust premium estimation, contributing a pricing framework that explicitly accounts for extreme value claims.

GWO-Enhanced Hybrid Deep Learning with SHAP for Explainable TLKM.JK Stock Forecasting Bukhori, Hilmi Aziz; Bukhori, Saiful; Anam, Syaiful; Yusuf, Feby Indriana; Sari, Meylita
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5205

This study presents an innovative Grey Wolf Optimization (GWO)-enhanced hybrid deep learning model integrating Convolutional Neural Networks (CNN), Bidirectional Long Short-Term Memory (BiLSTM), and Transformer, combined with SHAP for interpretable stock price forecasting of TLKM.JK from July 29, 2024, to July 29, 2025. Addressing non-linear market dynamics, the model evaluates seven experimental cases, with the GWO-optimized configuration (Case 2) achieving superior performance, with a Root Mean Squared Error (RMSE) of 75.23, Mean Absolute Error (MAE) of 58.14, and Directional Accuracy (DA) of 76.2%, surpassing the baseline by 17.4% in RMSE and 8.1% in DA. Notably, Case 2 excels during the April 2025 surge (11.8% increase, MAE 53, DA 82%) and the high-volume day of May 28, 2025 (531,309,500 shares, MAE 48), leveraging Volume (SHAP 0.45) and RSI (0.28) as key predictors. With a 4-hour convergence time on an NVIDIA RTX 3060 GPU, the model ensures computational efficiency and interpretability, making it a robust tool for traders. Despite limitations in single-stock focus and GPU dependency, this framework advances AI-driven financial forecasting by offering transparent, high-accuracy predictions, paving the way for multi-stock applications and real-time SHAP updates.

ETNOMATEMATIKA PADA PEMBUATAN ROSTER DI KABUPATEN BANYUWANGI Nada, Qothrun; Yusuf, Feby Indriana; Yohanes, Barep
Differential: Journal on Mathematics Education Vol. 2 No. 1 (2024): Differential: Journal on Mathematics Education
Publisher : Universitas Muhammadiyah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32502/differential.v2i1.125

Etnomatematika merupakan konsep matematika yang diterapkan dalam kegiatan budaya tertentu yang berhubungan dengan kehidupan dan aktivitas sehari-hari. Konsep matematika yang berkaitan dalam budaya salah satunya yaitu Roster. Penelitian ini bertujuan mengetahui dan mendeskripsikan konsep-konsep matematika yang terdapat pada pembuatan Roster di kabupaten Banyuwangi. Jenis penelitian ini adalah kualitatif. Subjek penelitian ini adalah adalah 2 orang pemilik pabrik pembuatan roster masing-masing 1 orang di daerah kecamatan Kabat dan 1 orang di daerah kecamatan Sempu serta 2 orang pekerja yang mempunyai pengalaman dalam pembuatan roster di kedua daerah tersebut. Metode pengumpulan data yang digunakan dalam penelitian ini adalah observasi, wawancara, dan dokumentasi. Metode analisis data yang digunakan dalam penelitian ini adalah reduksi data, penyajian data, dan verifikasi data atau penarikan kesimpulan. Hasil penelitian ini menunjukkan terdapat konsep matematika pada pembuatan Roster berupa konsep angka, konsep pola, konsep pengukuran, dan konsep geometri.

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