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All Journal Jurnal Pengabdian UntukMu NegeRI Indonesian Journal of Applied Statistics Jambura Journal of Mathematics International Journal of Quantitative Research and Modeling Buletin Sistem Informasi dan Teknologi Islam Journal of Data Insights Jurnal Pengabdian Masyarakat dan Riset Pendidikan
Rizka Amalia Putri
Statistics Study Program, Department of Mathematics, Riau University, Riau
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Physics Social Sciences Other

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Studi Korelasi antara Keterampilan Digital dan Sikap Guru dalam Integrasi Pembelajaran berbasis Information and Communication Technology (ICT) di Sekolah Menengah: Penelitian Putri Rahma Dianti; Rizka Amalia Putri; Asih Rahayu Ajeng Agesti; Surtika
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 1 (2025): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 1 (Juli 2025 -
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i1.2153

Abstract

This article aims to analyze the relationship between ICT skills and teachers' attitudes toward the integration of ICT-based learning in secondary schools. The implementation of ICT-based learning in schools is an effort to enhance the use of technology and improve teacher competencies. This research employed a descriptive correlational design using a survey method. The sample consisted of 50 teachers selected through simple random sampling using an online picker wheel method. Data analysis was conducted using an Independent T-test, while the relationships between variables were analyzed using partial correlation tests. The results of the study indicate a significant correlation (p < 0.05) between ICT skills and teachers' attitudes toward ICT integration in classroom learning. Teachers with higher ICT skills tend to have more positive attitudes and are more capable of effectively implementing technology in the learning process. These findings highlight the importance of strengthening teachers’ digital competencies as a prerequisite for the successful implementation of ICT-based learning in schools.
Aplikasi Sistem Monitoring Produksi dengan Diagram Kontrol Fuzzy Multivariat Berbasis Alpha-cut dan Transformasi Median Safitriani, Nur Rezky; Widyaningrum, Erlyne Nadhilah; Putri, Rizka Amalia; Khoirunnisa, Husna Afanyn; Fathan, Morina A.
Buletin Sistem Informasi dan Teknologi Islam (BUSITI) Vol 6, No 3 (2025)
Publisher : Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/busiti.v6i3.2874

Abstract

Pengendalian kualitas produksi yang adaptif menjadi kebutuhan mendesak dalam menghadapi data multivariat dengan ketidakpastian, disertai tuntutan untuk meningkatkan kualitas produk. Hal ini dapat diatasi menggunakan teori himpunan fuzzy melalui alat Statistical Process Control berupa diagram kontrol. Penelitian ini mengembangkan aplikasi sistem monitoring produksi menggunakan diagram kontrol multivariat fuzzy T2 Hotelling berbasis alpha-cut dan transformasi median. Aplikasinya dilakukan pada industri material bangunan di UD Tiga Beton sebagai penghasil batako press. Monitoring dilakukan pada dua karakteristik kualitas yang saling berkorelasi, yaitu kondisi fisik dan bidang permukaan, yang direpresentasikan dalam bentuk linguistik. Data pengamatan dikonversi ke dalam bilangan fuzzy menggunakan Triangular Fuzzy Number dan proses defuzzifikasi melalui transformasi median serta tambahan alpha-cut sebesar 0,6 agar dapat monitoring pergeseran mean yang kecil. Hasil penerapannya menunjukkan bahwa empat pengamatan terdeteksi berada di luar batas sehingga mengindikasikan proses produksi berada dalam keadaan out of control. Dengan demikian, aplikasi sistem ini terbukti mampu mendeteksi penyimpangan proses secara lebih akurat dan praktis. Diagram kontrol fuzzy multivariat berbasis alpha-cut dan transformasi median menjadi alternatif yang adaptif dalam pengendalian kualitas pada berbagai produksi.
Panel Data Regression Approach to Identify Factors Affecting Unemployment in East Java Province: Pendekatan Regresi Data Panel untuk Mengidentifikasi Faktor-Faktor yang Mempengaruhi Pengangguran di Provinsi Jawa Timur Amalia Putri, Rizka; Fadlurohman, Alwan; Mughni, Mardiyah
Journal of Data Insights Vol 3 No 1 (2025): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v3i1.722

Abstract

The Open Unemployment Rate (OOP) in East Java Province is a multidimensional problem influenced by economic and social factors, with significant disparities between districts/cities. This study analyses the effect of Poverty Percentage, Labour Force Participation Rate (TPAK), and Economic Growth on the open unemployment rate using a panel data regression approach to accommodate spatial and temporal heterogeneity. Cross-section (38 districts/cities) and time series (2019-2021) data were analysed through three models: Common Effect Model (CEM), Fixed Effect Model (FEM), and Random Effect Model (REM). The results of statistical tests (Chow, Hausman, and Lagrange Multiplier) show the FEM as the best model with a coefficient of determination of 0.555, explaining 55.5% of the variation in the unemployment rate. The FEM estimation reveals that the Poverty Percentage has a significant positive effect on increasing the unemployment rate, while Economic Growth has a negative impact on reducing the unemployment rate. This finding confirms the need for policies focused on poverty alleviation and increasing economic growth based on regional leading sectors. This study enriches the methodological literature through the application of FEM that controls for region-specific heterogeneity, while providing practical recommendations for policy makers in designing precise unemployment reduction interventions, such as skills training based on industry needs and strengthening labour-intensive programmes.
Enhancing Teachers' Knowledge of Artificial Intelligence and Information Technology at SMPN 11 Pekanbaru: Penguatan Literasi Teknologi Informasi dan Artificial Intelligence bagi Pendidik SMPN 11 Pekanbaru Sujana, Teguh; Amalia Putri, Rizka; Nasfianti, Iis; Wulandari, Nindya; Fawrin, Heralda
Jurnal Pengabdian UntukMu NegeRI Vol. 9 No. 3 (2025): Pengabdian Untuk Mu negeRI
Publisher : LPPM UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jpumri.v9i3.10349

Abstract

Rapid technological advancements necessitate that educators constantly adjust to new advances, such as the application of artificial intelligence (AI) and information technology in the classroom. The fact remains that many educators are still not accustomed to incorporating technology into their lessons. By promoting the use of AI as a learning aid and adopting IT-based learning, this community service project seeks to improve the knowledge and abilities of SMPN 11 Pekanbaru instructors. The Participatory Rural Appraisal (PRA) method was used in the activity, which was conducted as a workshop with materials, discussions, and practical application. A variety of applications that can aid in the learning process were presented to the teachers. The activity's outcomes demonstrated a rise in teachers' technological knowledge and proficiency as well as the appearance of motivation to innovate in the classroom. Teachers can better prepare for the difficulties of teaching in the digital age by starting with this activity.
Modeling East Java Province Poverty Cases Using Birespon Truncted Spline Regression Rizka Amalia Putri; Nindya Wulandari; Erlyne Nadhilah Widyaningrum; Morina A. Fathan; Nur Rezky Safitriani
Indonesian Journal of Applied Statistics Vol 8, No 1 (2025)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v8i1.100915

Abstract

An analytical method for determining the relationship between predictor and response variables is regression. For data that shows unidentified patterns, nonparametric regression is a suitable data analysis technique. A nonparametric regression technique is the truncated spline. Due to the widespread use of truncated spline with a single response variable, this study employs biresponse truncated spline, which uses two response variables to produce a better model than single-response modeling. The purpose of this study is to obtain the best model and to identify which variables influence the poverty case in East Java Province using biresponse truncated spline regression. The best knot points were chosen for this investigation using Generalized Cross Validation (GCV). With three knot points and a model goodness of fit () of 95.83%, GCV gives the best modeling results. Applying this model to the East Java Province case of poverty using data on the poverty depth index and the percentage of the population living in poverty in 2023 reveals that the Labor Force Participation Rate (TPAK), Average Years of Schooling (RLS), and Open Unemployment Rate (TPT) all have a significant effect.Keywords: biresponse truncated spline; nonparametric regression; poverty
Comparative Analysis of Hierarchical Cluster Methods in Inflationary Cities in Indonesia Based on Sectoral Inflation Patterns Khoirunissa, Husna Afanyn; Safitriani, Nur Rezky; Widyaningrum, Erlyne Nadhilah; Putri, Rizka Amalia; Fathan, Morina A.; Nisa, Nabilla Rida Tri
Jambura Journal of Mathematics Vol 8, No 1: February 2026
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v8i1.35105

Abstract

This study aims to assess the performance of single linkage, complete linkage, and average linkage hierarchical clustering algorithms in grouping cities used as inflation benchmarks in Indonesia into clusters based on sectoral inflation patterns. The data utilized are 150 regencies/cities divided into 11 sectors that drive inflation, identified by BPS Indonesia. Prior to clustering, a distance analysis using Euclidean distances was conducted to measure similarity between regions. Evaluation of the optimal number of clusters was conducted by applying the stability measure approach (APN, AD, ADM, and FOM), which showed that creating five clusters produced the most stable results. The results of the analysis revealed that the single linkage approach had the lowest within-cluster to between-cluster standard deviation ratio compared to the other two approaches, which revealed a greater level of homogeneity between the clusters. From an economic perspective, this clustering pattern revealed impressive differences in sectoral inflation pressures between provinces, even between cities within a province. Consequently, the single linkage method is proposed as the optimal method for identifying spatial variations in sectoral inflation in Indonesia.
Comparison of Poisson and Negative Binomial Regression Models in Identifying Factors Influencing Covid-19 Deaths in Indonesia. Nabilla Rida Tri Nisa; Amanatullah Pandu Zenklinov; Husna Afanyn Khoirunissa; Nur Rezky Safitriani; Erlyne Nadhilah Widyaningrum; Rizka Amalia Putri; Morina A. Fathan
International Journal of Quantitative Research and Modeling Vol. 6 No. 4 (2025): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i4.1126

Abstract

This research compares Poisson Regression and Generalized Negative Binomial (GNB) Regression to underscore the factors that influence the growth of COVID-19 deaths in Indonesia. Count data such as mortality cases often violates the Poisson assumption of equidispersion (null mean equals variance) causing overdispersion. The GNB model is suggested as a remedy for overdispersed data crime prevention has become increasingly necessary for systematic development because secondary data from the Indonesian government has included dependable variables such as mortality rates for people aged over 60, diabetes mellitus, heart disease, lung disease, healthcare worker percentages, referral hospitals, and the population. The Poisson Regression reported R² of 87.67% and experienced overdispersion (θ₁ = 356.27, θ₂ = 417,597). The GNB model, in contrast, with a lower AIC (499.5566), overtook Poisson. Important factors that had significant impact on both models were mortality rates for individuals over 60, diabetes mellitus, healthcare workers, and referral hospitals, whereas heart and lung disease mortality rates were the ones that were not material. The GNB model had a better fit and tackled the issues of overdispersion in the Poisson Regression.
Co-Authors Alwan Fadlurohman Amanatullah Pandu Zenklinov Asih Rahayu Ajeng Agesti Erlyne Nadhilah Widyaningrum Fathan, Morina A. Fawrin, Heralda Husna Afanyn Khoirunissa Husna Afanyn Khoirunissa Khoirunnisa, Husna Afanyn Morina A. Fathan Morina A. Fathan Mughni, Mardiyah Nabilla Rida Tri Nisa Nasfianti, Iis Nindya Wulandari Nisa, Nabilla Rida Tri Nur Rezky Safitriani Nur Rezky Safitriani Putri Rahma Dianti Safitriani, Nur Rezky Surtika Teguh Sujana