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All Journal Ensiklopedia of Journal Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Ilmu Pendidikan Indonesia
Dina Jumiatul Fitri
Universitas Cenderawasih
Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Economics, Econometrics & Finance Education Health Professions Law, Crime, Criminology & Criminal Justice Mathematics Physics Public Health Social Sciences Other

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CLASSIFICATION OF PNEUMONIA DISEASE USING THE MINI XCEPTION MODEL ON X-RAY DATA Anggrainy Togi Marito Siregar; Dina Jumiatul Fitri; Happy Alyzhya Haay; Rasi Kasim Samosir
Jurnal Ilmu Pendidikan Indonesia Vol 14 No 2 (2026): JURNAL ILMU PENDIDIKAN INDONESIA
Publisher : Master of Science Education Program, Postgraduate Program of Cenderawasih University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31957/jipi.v14i2.5602

Abstract

Pneumonia is a disease that often causes death in Indonesia. In general, many that cause a person to develop pneumonia include pneumonia due to bacterial, viral, mycoplasma pneumonia, fungal pneumonia. There are many ways to detect a patient grouped into one type of pneumonia. One way is to use an X-ray machine. X-ray is technology that can send waves of electromagnetic radiation briefly to scan the condition of the inside of the body. In this study, we tried to classify patients affected by bacterial pneumonia and viral pneumonia as well as normal people. The data we use is a picture of the lungs taken from the X-ray results. This research was conducted by applying the mini Xception model using the python program. The model can predict the results of X-ray scans that belong to the class of bacterial pneumonia very well, as seen from the value of precision and sensitivity of 80 and 97 percent, respectively. Viral pneumonia class can not be predicted as good as the two previous classes, but the results obtained are quite good as seen from the value of precision and sensitivity of 85 and 67 percent, respectively. The overall accuracy of the model obtained is 0.86.
KOMPARASI REGRESI ZIP DAN REGRESI ZINB PADA DATA KEMATIAN BAYI DI JAWA BARAT Dina Jumiatul Fitri; Anggrainy Togi Marito Siregar; Happy Alyzhya Haay; Rasi Kasim Samosir
Ensiklopedia of Journal Vol 8, No 1 (2025): Vol. 8 No. 1 Edisi 2 Oktober 2025
Publisher : Lembaga Penelitian dan Penerbitan Hasil Penelitian Ensiklopedia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33559/eoj.v8i1.3439

Abstract

Poisson regression analysis is a nonlinear regression that is usually used for discrete data and assumes equidispersion. In practice, there is often a violation of assumptions equidispersion, one of the violations is overdispersion (the variance is greater than the average value). One of the causes of overdispersion is the excessive number of zero values (Excess Zero) on the response variable. Excess zeros can be seen in the proportion of response variables which is zero greater than any other discrete data. There are many methods to overcome overdispersion: Zero Inflated Poisson (ZIP) regression and Zero Inflated regression Negative Binomial (ZINB). The purpose of this study is to determine the regression model which is better used on data that experience overdispersion. Data used to analyze ZIP and ZINB regression is the data of infant death in West Java Province in 2021. Based on the study’s result, it is known that the Akaike Information Criterion (AIC) value in the ZINB regression is smaller than the ZINB regression AIC value. So the ZINB regression is better used as well as the factor of infant death.Keywords: Overdispersion; Poisson Regression; ZIP; ZINB; Infant Death
Perbandingan Model Long Short-Term Memory (LSTM) dan ARIMA untuk Prediksi Inflasi dan Indeks Harga Konsumen (IHK) di Kota Jayapura Happy Alyzhya Haay; Anggrainy Togi Marito Siregar; Dina Jumiatul Fitri; Rasi Kasim Samosir
Saintifik: Jurnal Matematika, Sains, dan Pembelajarannya Vol 12 No 2 (2026): Saintifik: Jurnal Matematika, Sains, dan Pembelajarannya
Publisher : Universitas Sulawesi Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31605/saintifik.v12i2.677

Abstract

Inflasi dan Indeks Harga Konsumen (IHK) merupakan indikator makroekonomi penting yang memerlukan model prediksi yang andal untuk mendukung pengambilan keputusan. Penelitian ini membandingkan kinerja model Long Short-Term Memory (LSTM) dan Autoregressive Integrated Moving Average (ARIMA) dalam memprediksi Inflasi dan IHK menggunakan data deret waktu bulanan. Model LSTM dilatih dengan mekanisme EarlyStopping untuk mencegah overfitting, dan diuji pada empat konfigurasi panjang timesteps (3, 6, 9, dan 12). Hasil terbaik diperoleh pada timesteps = 9, yang kemudian dibandingkan dengan model ARIMA(1,1,1).. Evaluasi dengan metrik Mean Squared Error (MSE), Mean Absolute Error (MAE), dan koefisien determinasi (R²) menunjukkan bahwa untuk variabel Inflasi, kedua model menghasilkan R² negatif (LSTM = -0,012; ARIMA = -0,027), yang mengindikasikan kedua model belum mampu mengungguli prediksi nilai rata-rata sederhana. Untuk variabel IHK, LSTM menunjukkan performa lebih baik dibandingkan ARIMA (R² = 0,197 berbanding -0,002), meskipun kemampuan penjelasan variansnya masih tergolong rendah. Penelitian ini mengonfirmasi bahwa keterbatasan jumlah data historis menjadi kendala utama bagi model deep learning seperti LSTM, sehingga model sederhana seperti ARIMA tetap kompetitif pada kondisi data yang minim.
PENERAPAN METODE GASING DALAM PEMBELAJARAN MATEMATIKA DASAR BAGI SISWA SEKOLAH DASAR DI KAMPUNG KAYU PULO KOTA JAYAPURA Dina Jumiatul Fitri; Anggrainy Togi Marito Siregar; Happy Alyzhya Haay; Rasi Kasim Samosir; Johannes Ferdinand Wally; Alfrida Milka Yaru
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 7 No. 4 (2026): Inpress Vol. 7 No. 4 (2026)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v7i4.60163

Abstract

Kegiatan pengabdian ini berfokus pada rendahnya kemampuan numerasi dasar siswa Sekolah Dasar di Kampung Kayu Pulo, Kota Jayapura. Tujuan kegiatan adalah meningkatkan pemahaman konsep operasi hitung melalui penerapan metode GASING (Gampang, Asyik, dan Menyenangkan). Metode yang digunakan berupa pembelajaran interaktif dengan pendekatan bertahap, dimulai dari penyampaian konsep sederhana, latihan interaktif, hingga aktivitas yang menyenangkan. Kegiatan dilaksanakan selama satu hari dengan melibatkan 15 siswa. Hasil menunjukkan adanya peningkatan kemampuan numerasi dasar, dengan capaian siswa antara 2 hingga 5 soal benar dari total 5 soal, serta rata-rata sebesar 3,6. Selain itu, terjadi peningkatan partisipasi, motivasi, dan kepercayaan diri siswa dalam belajar matematika. Metode GASING terbukti efektif dalam menciptakan pembelajaran yang lebih mudah dipahami, interaktif, dan menyenangkan.
Co-Authors Alfrida Milka Yaru Anggrainy Togi Marito Siregar Happy Alyzhya Haay Johannes Ferdinand Wally Rasi Kasim Samosir