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All Journal EKSAKTA: Journal of Sciences and Data Analysis CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Wilayah dan Lingkungan Dinamisia: Jurnal Pengabdian Kepada Masyarakat JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Litbang Sukowati : Media Penelitian dan Pengembangan Jurnal Statistika dan Aplikasinya Jurnal Pengabdian kepada Masyarakat Nusantara Kafa’ah: Journal of Gender Studies Jurnal Abdimas Ekonomi dan Bisnis TIERS Information Technology Journal Jurnal Pengabdian Ilung (Inovasi Lahan Basah Unggul) VARIANSI: Journal of Statistics and Its Application on Teaching and Research International Journal of Multidisciplinary Sciences and Arts RAGAM: Journal of Statistics and Its Application Jurnal Teknoinfo
Yeni Rahkmawati
Universitas Lambung Mangkurat
Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Statistics Enthusiast Movement: Enhancement of Posyandu and PKK Cadre Competencies in Desa Simpang Tiga for Monitoring Maternal and Child Health : Gerakan Cinta Statistik: Peningkatan Kompetensi Kader Posyandu dan PKK Desa Simpang Tiga dalam Pemantauan Kesehatan Ibu dan Anak Anggraini, Dewi; Rahkmawati , Yeni; Zulliati, Zulliati; Maulida, Maisya; Cahyadi, Rizqa Nabiilah; Nazili, Muhammad Haqin; Al Atqiaa , Muhammad Azkaa; Siahaan, Priscilla Aquirera Iory; Viranty, Miftah Rizky
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 9 No. 2 (2025): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v9i2.25013

Abstract

Local area monitoring of maternal and child health is crucial for assessing health service quality. In Desa Simpang Tiga, challenges include a manual and unintegrated maternal and child health documentation system and limited cadre competencies in anthropometric measurements, antenatal care data management, and analysis. This community-based empowerment program aimed to address these issues through community partnership empowerment. The program involved focus group discussions and scientific and technical training for Posyandu and PKK cadres. A Wilcoxon Test evaluated the program's effectiveness by comparing pre- and post-training cadre competencies. Results showed significant improvements: cadre competency in anthropometric measurements increased by 20.8% (from 53% to 73.8%) (p < 0.05). Competency in maternal and child health data management and analysis increased by 43.8% (from 33.5% to 77.3%) (p < 0.05). These findings demonstrate the program's success in enhancing cadre competencies in basic maternal and child health measurements and data management in Desa Simpang Tiga.
PEMODELAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) MENGGUNAKAN PEMBOBOT KERNEL PADA KASUS TINGKAT PENGANGGURAN TERBUKA DI KALIMANTAN Viona Oktafiani; Dewi Sri Susanti; Yeni Rahkmawati
RAGAM: Journal of Statistics & Its Application Vol 3, No 1 (2024): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v3i1.12822

Abstract

AbstractUnemployment is one of the serious problems in Indonesia's economic development. This unemployment describes human resources that have not been utilized optimally, as a result of which people's productivity and income have not been maximized, this can also be one of the causes of poverty and other social problems. This study aims to find out the general picture of the open unemployment rate in the Kalimantan region, get the best model and factors that influence the open unemployment rate and illustrate it through thematic maps. The study began with testing assumptions and spatial effects then continued with testing global regression modeling and Geographically Weighted Regression. The weighting function used in this study is adaptive gaussian kernel. The variable that has a positive effect on the open unemployment rate in the Kalimantan region is population density. While the variable that negatively affects the open unemployment rate is the Labor Force Participation Rate. Keywords:   Open Unemployment Rate, Kalimantan Island, Spatial, GWR
PERAMALAN JUMLAH PENUMPANG BUS RAPID TRANSIT (BRT) BANJARBAKULA DENGAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE WITH EXOGENOUS VARIABLE (ARIMAX) DENGAN EFEK VARIASI KALENDER Eka Ayu Frasetyowati; Nur Salam; Yeni Rahkmawati
RAGAM: Journal of Statistics & Its Application Vol 3, No 1 (2024): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v3i1.12789

Abstract

Banjarbakula Bus Rapid Transit (BRT) is an inner-city bus-based mass transit system that provides a sense of comfort, safety, speed in mobility, and low cost in serving the citizens of Banjarmasin City and Banjarbaru City. Based on data on the number of passengers on the Banjarbakula BRT for the period April 2020 - February 2023, public interest in using the Banjarbakula BRT as a mode of transportation is quite high. However, the limited units and operational schedules make the Banjarbakula BRT unable to fully meet the needs of the public. Forecasting the number of passengers of BRT Banjarbakula for the next 12 periods is one of the measures to prepare the infrastructure, quality and units of BRT Banjarbakula in order to facilitate the public and create a better transportation system. In the Banjarbakula BRT passenger data, there is an increase in the number of passengers at certain times such as during religious holidays and school holidays, so this increase in passenger numbers is thought to be due to the influence of the calendar variation effect. This research intends to forecast the number of passengers of BRT Banjarbakula using the best ARIMAX model with the effect of calendar variation. The results indicate that the ARIMAX (0, 1, 1) model is the best ARIMAX model to forecast the number of passengers of BRT Banjarbakula for the next 12 periods. The forecast results indicate an increase in the month where the Christmas celebration and also the memorial haul guru sekumpul, so that the variable Christmas celebration and memorial haul guru sekumpul significantly affect the number of passengers of BRT Banjarbakula.Keywords: Forecasting, BRT Banjarbakula, ARIMAX with calendar variation effects
Comparison of SMOTE and ADASYN in Optimizing Random Forest Model for Imbalanced Financial Ratio Bankruptcy Prediction Novanda Rizky Ramadhana; Fuad Muhajirin Farid; Yeni Rahkmawati
Jurnal Teknoinfo Vol. 20 No. 1 (2026): Period January 2026
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/teknoinfo.v20i1.1056

Abstract

Classification is a data analysis process that can predict classes based on predefined characteristics. In the era of big data, classification can be performed using machine learning. The problem of machine learning in classification analysis is imbalance data which often affect model performance. SMOTE and ADASYN are oversampling techniques to solve this problem. This study aims to evaluate the effectiveness of SMOTE and ADASYN in improving the performance of the Random Forest model on imbalanced data in the case of company bankruptcy using financial ratios. Models were built using training data with various splitting data and oversampling techniques. Then, the resulting models will be tested using testing data. The results show that the best model was achieved with a combination of splitting data 70:30 using SMOTE technique, which produced the highest f1-score of 40.57%, compared to ADASYN technique with 36.11% (a decrease of 4.46%), and without oversampling techniques with 19.51% (a decrease of 21.06%). The findings indicate SMOTE and ADASYN can identify minority values which are the main problem of imbalance data, with SMOTE showing better performance compared to ADASYN.
Role of Motivational Content on Instagram in Enhancing Generation Z’s Self-Esteem: An Empirical Analysis Rahkmawati, Yeni; Anggraini, Dewi; Sukmawaty, Yuana; Annisa, Selvi; Al Fajrin, Muhammad Agha Putra; Putri, Dwi Cahyaning; Ananda, Saira Aulia; Nabilah, Dwi Anisatun
International Journal of Multidisciplinary Sciences and Arts Vol. 5 No. 1 (2026): International Journal of Multidisciplinary Sciences and Arts, Article January 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v5i1.7810

Abstract

Generation Z (Gen Z) is a generation that grew up in the digital era with intensive use of social media, including Instagram. As the largest user group, Gen Z consumes a wide range of influencer-generated content, including motivational content that may affect psychological well-being, particularly self-esteem. However, empirical studies specifically examining the influence of motivational content from Instagram influencers on Gen Z’s self-esteem remain limited. This study aims to analyze Gen Z’s interest in motivational content on Instagram and to examine changes in self-esteem before and after exposure to such content. A quantitative approach using a quasi-experimental one-group pretest–posttest design was employed. The sample consisted of 150 university students in Banjarbaru City selected through purposive sampling. Data were collected using the Rosenberg Self-Esteem Scale (RSES) administered via questionnaires. The Wilcoxon Signed-Rank Test was used to analyze differences in self-esteem scores before and after treatment. The results indicate a significant increase in self-esteem following exposure to motivational content on Instagram. The average post-treatment self-esteem score was higher than the pre-treatment score, confirming the positive impact of motivational content. In addition, although most respondents reported only occasional exposure to motivational content, the majority expressed liking and interest in such content. These findings suggest that motivational content on Instagram contributes positively to enhancing Gen Z’s self-esteem and may serve as an effective medium for psychological empowerment.
Pemodelan Regresi Spasial Berbasis Area Pada Indeks Kualitas Lingkungan Hidup (IKLH) di Provinsi Kalimantan Selatan Hafidhah, Nor Jinan; Sukmawaty, Yuana; Rahkmawati, Yeni
Jurnal Wilayah dan Lingkungan Vol 13, No 3 (2025): Desember 2025
Publisher : Department of Urban and Regional Planning, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jwl.13.3.41-60

Abstract

Indeks Kualitas Lingkungan Hidup (IKLH) merupakan indikator yang dapat memberikan gambaran tentang kualitas lingkungan hidup di suatu wilayah. IKLH digunakan sebagai alat evaluasi dalam berbagai program perbaikan kualitas lingkungan hidup dan sumber informasi untuk mendukung pengambilan kebijakan mengenai perlindungan dan pengelolaan lingkungan hidup. Dalam perhitungan IKLH terdapat empat indikator, yaitu Indeks Kualitas Air (IKA), Indeks Kualitas Udara (IKU), Indeks Kualitas Lahan (IKTL), dan Indeks Kualitas Air Laut (IKAL). Penelitian ini bertujuan untuk menganalisis pengaruh persentase jumlah penduduk, Produk Domestik Regional Bruto (PDRB), dan jumlah kendaraan bermotor terhadap IKLH di Provinsi Kalimantan Selatan tahun 2022. Metode penelitian yang digunakan dalam penelitian ini adalah analisis regresi spasial berbasis area. Data yang digunakan merupakan data sekunder tahun 2022 dari Badan Pusat Statistik (BPS) dan Dinas Lingkungan Hidup (DLH) Provinsi Kalimantan Selatan, meliputi 13 kabupaten/kota sebagai area pengamatan. Hasil penelitian menunjukkan bahwa model Spatial Autoregressive Moving Average (SARMA) merupakan model terbaik untuk memodelkan faktor-faktor yang diduga berpengaruh terhadap IKLH. Dari model SARMA diperoleh bahwa persentase jumlah penduduk, PDRB dan jumlah kendaraan bermotor berpengaruh signifikan terhadap IKLH di Provinsi Kalimantan Selatan. Koefisien determinasi sebesar 80,65% menunjukkan bahwa model mampu menjelaskan keragaman IKLH secara kuat. Kebaruan penelitian ini terletak pada penggunaan model SARMA yang mampu menangkap pengaruh spasial lag dan eror secara simultan, serta temuan hubungan positif PDRB terhadap IKLH yang mengindikasikan bahwa pertumbuhan ekonomi di Kalimantan Selatan dapat berjalan seiring dengan peningkatan kualitas lingkungan.
Analysis of Food Inflation in Indonesia using the Nonlinear Autoregressive Distributed Lag Approach Salsabila, Nur; Rahkmawati, Yeni; Muslim, Agus; Rahman, Mizan Ikhlasul
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i2.35352

Abstract

Food Inflation remains one of the most persistent sources of price volatility in Indonesia and poses a significant challenge for macroeconomic stability and household welfare. This study conducts quantitative empirical time series research to examine the asymmetric effects of Money Supply (M2) and Farmers Terms of Trade (FTT) on Food Inflation. The analysis uses monthly data from 2011 to 2023 obtained from Bank Indonesia and Statistics Indonesia and applies the Nonlinear Autoregressive Distributed Lag (NARDL) model, which is appropriate for capturing asymmetry and accommodating variables integrated at different orders. The selection of M2 is based on monetary theory which states that changes in liquidity influence aggregate demand and inflation, while the use of FTT is supported by agricultural and development literature showing that farmers purchasing power affects food production capacity and food price dynamics. The results reveal significant asymmetric effects in both the short and long run. Increases and decreases in M2 both raise Food Inflation, and the stronger effect during declining M2 reflects downward price rigidity and the dominance of quasi money in Indonesia. A decline in FTT significantly increases long run inflation through constraints on agricultural input access and reduced food supply. The findings also confirm inflation persistence. These results imply that liquidity management and policies that strengthen farmer purchasing power are essential to stabilize food prices. The study recommends integrating monetary policy with agricultural support measures to mitigate future food inflation pressures.
Long-Memory Modeling of Farmers' Terms of Trade in Indonesia: A Comparative Analysis of SARIMA and SARFIMA Approaches Viranty, Miftah Rizky; Rahkmawati, Yeni; Asianingrum, Al Hujjah
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 7, ISSUE 1, April 2026
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol7.iss1.art6

Abstract

Indonesia, as an agrarian country, places the agricultural sector as a vital pillar of its economy and food security, with farmers’ welfare measured through the Farmers’ Terms of Trade (FTT). This study aims to compare the performance of the Seasonal Autoregressive Integrated Moving Average (SARIMA) and the Seasonal Autoregressive Fractionally Integrated Moving Average (SARFIMA) models in forecasting FTT using monthly data from 2009 to 2024 obtained from BPS (Statistics Indonesia). The results show that the SARIMA(0,1,1)(0,1,1)₁₂ model demonstrates higher accuracy with a MAPE value of 5.29%, compared to SARFIMA(1,0.2688,0)(0,1,1)₁₂ with a MAPE of 5.97%. However, the relatively small difference in MAPE indicates the presence of long-memory characteristics in the FTT data, although it does not significantly improve forecasting accuracy. The forecast results based on the best SARIMA model predict that FTT will gradually increase throughout 2025, peaking at 127.2920 in December, with a temporary decline from March to May. These findings can serve as a basis for the government to formulate targeted agricultural policies, price control measures, subsidy distribution, and marketing strategies that enhance farmers’ welfare and support national food security.
Comparison of ARIMA, Random Forest, and Hybrid ARIMA-Random Forest Models in Forecasting Indonesian Crude Oil Prices Rahkmawati, Yeni; Annisa, Selvi; Hafid, Hardianti; Nuramaliyah, Nuramaliyah; Safitri, Emeylia
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.36540

Abstract

The price of Indonesian crude oil (ICP) is highly volatile due to fluctuations in global demand, energy policies, and geopolitical tensions, making accurate forecasting challenging. This study compares three forecasting models: ARIMA, Random Forest, and Hybrid ARIMA–Random Forest. The models are evaluated using Time-Series Cross-Validation (TSCV) with MAPE, sMAPE, and RMSE as performance metrics. The results indicate that the Hybrid ARIMA–Random Forest model achieves the lowest MAPE and sMAPE, while Random Forest attains the lowest RMSE, and ARIMA exhibits the highest forecast errors. Diebold–Mariano (DM) tests confirm that ARIMA’s predictive accuracy is significantly lower than both machine-learning-based models, whereas no significant difference is found between Random Forest and the hybrid model. Out-of-sample forecasts for January–June 2026 show relatively stable price movements within 59–63 USD per barrel, with short-term fluctuations reflected in wide prediction intervals. These findings suggest that Indonesian crude oil prices contain both linear and non-linear components, which are effectively captured by the hybrid approach. Overall, the Hybrid ARIMA–Random Forest model provides the most accurate forecasts in percentage-based metrics, offering a robust and reliable tool for policymakers, investors, and market participants navigating volatile oil markets.
Co-Authors Adzim, Muhammad Fauzan Al Atqiaa , Muhammad Azkaa Al Fajrin, Muhammad Agha Putra Al Hujjah Asianingrum Ananda, Saira Aulia Cahyadi, Rizqa Nabiilah Dewi Anggraini Dewi Anggraini Dewi Sri Susanti Eka Ayu Frasetyowati Farid, Fuad Muhajirin Fidiyaningsih, Yani Fuad Muhajirin Farid Fuad Muhajirin Farid Genardi, Angelina Ivanna Hafidhah, Nor Jinan Hardianti Hafid Ivanna Genardi, Angelina Maisarah Maisarah, Maisarah Maulida, Maisya Mizan Ikhlasul Rahman Muhajirin Farid, Fuad Muhammad Jimmy Saputra Muhammad Munawwir Muhammad Reza Faisal, Muhammad Reza Muhammad Riza Hafizi Muslim, Agus Nabilah, Dwi Anisatun Nazili, Muhammad Haqin Noordyanti, Erna Novanda Rizky Ramadhana Nur Salam Nuramaliyah, Nuramaliyah Oktaviani, Viona Putri, Dwi Cahyaning Riza, Yusi Safitri, Emeylia Salsabila, Nur Salsabila, Nur Selvi Annisa Siahaan, Priscilla Aquirera Iory Sidauruk, Verina Rosalin Br Sukmawaty, Yuana Syamsiar, Syamsiar Uthami, Mariza Viona Oktafiani Viranty, Miftah Rizky Yuana Sukmawaty Zulliati Zulliati, Zulliati