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All Journal Jurnal Teknik Sinergi ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JOIN (Jurnal Online Informatika) Desimal: Jurnal Matematika MAJAMATH: Jurnal Matematika dan Pendidikan Matematika M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika JISA (Jurnal Informatika dan Sains) Abdimasku : Jurnal Pengabdian Masyarakat JURNAL ABDI MASYARAKAT INDONESIA (JAMIN) Jurnal Pengabdian Masyarakat dan aplikasi Teknologi
Puspa, Sofia Debi
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Social Sciences Other

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The PENINGKATAN KETERAMPILAN GURU MELALUI PELATIHAN DASAR CODING & ANALISIS DATA STATISTIK UNTUK MENDUKUNG REVOLUSI INDUSTRI 4.0 Puspa, Sofia Debi; Riyono, Joko; Puspitasari, Fani; Pujiastuti, Christina Eni
Jurnal Abdi Masyarakat Indonesia (JAMIN) Vol 4 No 2 (2022): JURNAL ABDI MASYARAKAT INDONESIA (JAMIN)
Publisher : Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/jamin.v4i2.14132

Abstract

Seiring dengan perkembangan Revolusi Industri 4.0 di Indonesia, banyak sektor yang berdampak akibat Revolusi Industri 4.0 salah satunya yaitu pada bidang pendidikan. Dalam mewujudkan SDM unggul Indonesia yang mampu beradapatasi dengan perkembangan teknologi dibutuhkan kemampuan berpikir tingkat tinggi, berpikir kritis, kreatif dan inovatif. Selain itu, kemampuan computational thinking, dasar pemrograman komputer (coding) serta kemampuan analisis data statistik juga akan dibutuhkan. Tujuan dari kegiatan pelatihan dasar coding dan analisis data statistik adalah untuk meningkatkan pengetahuan dan meningkatkan keterampilan guru terkait dasar coding dan analisis data statistik dalam rangka mendukung Revolusi Industri 4.0. Kegiatan ini diikuti oleh 55 peserta dan pelatihan dilaksanakan secara daring. Berdasarkan hasil analisis kuantitatif dengan menggunakan data nilai pre-test dan post-test pada uji t berpasangan diperoleh p-value sebesar 0.00 lebih kecil dari taraf signifikansi (5%) sehingga H0 ditolak maka terdapat perbedaan yang signifikan antara rata-rata kemampuan sebelum dan sesudah pelatihan. Diketahui peningkatan rata-rata kemampuan peserta pelatihan sebesar 37.109 atau sekitar 88.7% dari rata-rata sebelum pelatihan.
PELATIHAN ANALISIS KORELASI DAN REGRESI DENGAN MENGGUNAKAN PERANGKAT LUNAK “R” UNTUK MENINGKATKAN KETERAMPILAN PENGOLAHAN DATA BAGI GURU Puspa, Sofia Debi; Joko Riyono; Fani Puspitasari; Christina Eni Pujiastuti
Jurnal Abdi Masyarakat Indonesia (JAMIN) Vol 6 No 1 (2024): JURNAL ABDI MASYARAKAT INDONESIA (JAMIN)
Publisher : Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/jamin.v6i1.17408

Abstract

Regression analysis is a statistical method that aims to determine the relationship between one or more independent variables and the dependent variable. Correlation expresses the degree of linear relationship between the two variables. The application of regression and correlation analysis is needed, especially for teachers, to determine what factors influence students' understanding of learning and it can be seen how strongly a variable influences other variables. This Community Service Activity is motivated by the need for educators to analyze the causes of factors that influence students's understanding of learning through data. This Community Service for partners aims to provide understanding related to Correlation and regression Analysis with" R" software. It is hoped that this Community service will make it easier for educators to decide on suitable learning models in class after knowing what factors influence student understanding in learning. Fifty-one participants attended this activity, and the training was carried out online. Based on the comparison of pre-test and post-test scores, there is an increased understanding of Correlation and Regression Analysis. The average increase in the trainees' ability was 34.14, 83.67% of the average before the training.
Pelatihan Pengolahan Data Penelitian: Estimasi Parameter dan Analisa Regresi Menggunakan R Untuk Guru SMA Di Jakarta dan Sekitarnya riyono, joko; Pujiastuti, Christina Eni; Syaifudin, - -; Puspa, Sofia Debi
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 6, No 3 (2023): September 2023
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v6i3.1567

Abstract

Kompetensi Pengolahan Data Penelitian sangat diperlukan oleh pendidik terkait dengan kewajiban dalam penulisan naskah ilmiah sebagai prasyarat kenaikan pangkat. Guru sebagai ujung tombak kemajuan pendidikan di Indonesia diharapkan mempunyai pengetahuan yang bagus dalam pengolahan data penelitian guna menambah kemampuan dalam melukakan kegiatan penelitian tindakan.  Bahasa R   merupakan perangkat lunak terpadu open source yang dapat digunakan untuk manipulasi data, kalkulasi, simulasi dan peragaan grafik. Dalam rangka memberikan tambahan pengetahuan pengolahan data penelitian memanfaatkan open source R kepada para Guru  Sekolah Menengah Atas di wilayah Jakarta dan sekitarnya maka progam Pengabdian Kepada Masyarakat ini diberikan kepada mereka. Penyampaian materi dalam pelatihan ini dilakukan secara daring  menggunakan Zoom Meeting diikuti dengan sesi diskusi dan tanya jawab. Berdasarkan  hasil pre test dan post test  para peserta, terlihat kenaikan pengetahuan peserta dalam pemahaman pemakaian Bahasa R untuk pengolahan data penelitian dari skor nilai 3.095 menjadi 6,782. Guna mengetahui pendapat peserta mengenai manfaat yang diperoleh dengan mengikuti pelatihan PKM maka diakhir pelatihan para peserta diminta mengisi kuesioner,diperoleh  Nilai Indeks skala Likert 88,122% yang mengisyaratkan bahwasannya pelaksanaan pelatihan baik mengenai materi dan cara penyampaiannya dirasa sangat dapat diikuti oleh mitra.
Literacy Review Study on the Implementation of Convolutional Neural Network Architecture in Segmentation and Classification of Lung Medical Images Riyono, Joko; Supriyadi, Supriyadi; Pujiastuti, Christina Eni; Puspa, Sofia Debi; Putri, Aina Latifa Riyana
JISA(Jurnal Informatika dan Sains) Vol 8, No 1 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i1.2172

Abstract

Medical image processing has become an essential aspect of healthcare, enabling accurate disease diagnosis and monitoring through advanced technologies. One of the most widely used methods in this domain is the Convolutional Neural Network (CNN), which has demonstrated high effectiveness in segmentation and classification tasks, particularly for chest X-ray images used in diagnosing lung-related diseases. This study aims to evaluate and analyze various CNN architectures implemented in lung X-ray imaging through a Systematic Literature Review (SLR) approach. The research explores the application, accuracy, challenges, and future opportunities of CNN-based models such as VGG, ResNet, AlexNet, and GoogLeNet. A total of 15 relevant studies published between 2019 and 2023 were selected after applying rigorous inclusion and exclusion criteria. The findings indicate that CNN architectures significantly enhance the accuracy of lung disease detection and support both segmentation and classification tasks. However, challenges such as dataset variability, model generalization, and ethical implications remain. This review provides comprehensive insights into CNN applications in medical imaging, emphasizing their potential and highlighting areas for further research.
Simulasi Clustering Provinsi di Indonesia dalam Penyebaran Covid-19 Berdasarkan Indikator Kesehatan Masyarakat Menggunakan Algoritma Gaussian Mixture Model Joko Riyono; Puspa, Sofia Debi; Pujiastuti, Christina Eni
MAJAMATH: Jurnal Matematika dan Pendidikan Matematika Vol. 5 No. 1 (2022): Vol. 5 No. 1 Maret 2022
Publisher : Prodi Pendidikan matematika Universitas Islam Majapahit (UNIM), Mojokerto, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36815/majamath.v5i1.1699

Abstract

Gaussian Mixture Model adalah suatu metode yang mengkontruksikan Clustering suatu dataset menjadi beberapa kelompok data yang memiliki distribusi Gaussian atau Normal. Pada penelitian ini akan dibahas gagasan untuk menentukan Clustering penyebaran Covid-19 pada 34 provinsi di Indonesia menggunakan Gaussian Mixture Model berdasarkan nilai indikator kesehatan masyarakat. Mengingat masih berlangsungnya pandemi Covid-19 di beberapa provinsi di Indonesia hingga saat ini, penelitian ini dipilih dengan tujuan sebagai masukan kepada pemerintah selaku pembuat kebijakan untuk bahan acuan penanganan pandemi Covid-19 sehingga program-program pencegahan penyebaran Covid-19 di tiap provinsi dapat tertangani secara lebih optimal. Hasil analisis data diperoleh 6 cluster optimal yaitu cluster yang berpotensi sangat tinggi berisi 1 provinsi, tinggi 4 provinsi, sedang 13 provinsi, cukup rendah 4 provinsi, rendah 2 provinsi, sangat rendah 10 provinsi dalam penyebaran Covid-19.
Evaluation of Lock Cover and STEM Dimensional Variations on Separation Force Using Multiple Regression and Statistical Process Control Puspa, Sofia Debi; Joko Riyono; Christina Eni Pujiastuti; Sentot Novianto; Larasati Rizky Putri; Ghiffari Awliya Muhammad Ashfania; Joseph Andrew Leo
Desimal: Jurnal Matematika Vol. 9 No. 1 (2026): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v9i1.30842

Abstract

This study addresses a critical limitation in conventional manufacturing analysis by demonstrating that dimensional variation in injection-molded press-fit systems should be interpreted as an interaction-driven phenomenon rather than independent geometric effects. The research focuses on lock stem and cover dimensions produced in a multi-cavity injection molding system, where geometric dependency leads to strong multicollinearity among variables. A quantitative approach was applied using actual production data, including dimensional measurements and separation force testing. Multiple linear regression was employed to model the relationship between geometric parameters and mechanical performance, supported by classical assumption testing and multicollinearity diagnostics. The results indicate a very high coefficient of determination, showing that dimensional variation collectively explains most of the separation force variability. However, severe multicollinearity limits the reliability of individual parameter interpretation and highlights the need for system-level analysis. Statistical Process Control confirms that the process operates within stable limits, while process capability analysis shows compliance with specification requirements. Despite this, variation in separation force persists, indicating high sensitivity to small geometric deviations. These findings emphasize that process stability alone is insufficient to ensure consistent performance. This study introduces an integrated framework combining regression, SPC, and capability analysis, providing both theoretical insight and practical guidance for improving dimensional control in precision manufacturing.
Co-Authors ADI, TRI SWASONO Agtirey, Novan Rojabil Amal Witonohadi Bijlsma, David Leon Christina Eni Pujiastuti Dany Nugraha Tantra Fani Puspitasari Ghiffari Awliya Muhammad Ashfania Himawan, Riswanda Iveline Anne Marie Joko Riyono Joseph Andrew Leo Kurniawati, Nazmia Larasati Rizky Putri Leo, Joseph Andrew Parwadi Moengin Pujiastuti, Christina Eni Puspitasari, Fani Putri, Aina Latifa Riyana Putri, Dianing Novita Nurmala Putri, Fayza Nayla Riyana Sally Cahyati Sentot Novianto Supriyadi Supriyadi Supriyadi Syaifudin, - - Tono Sukarnoto Yojana, Ratna Mira Yuli Kurnia Ningsih