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All Journal EIGEN MATHEMATICS JOURNAL Mattawang: Jurnal Pengabdian Masyarakat JINAV: Journal of Information and Visualization Quantitative Economics and Management Studies Panrannuangku Jurnal Pengabdian Masyarakat Daengku: Journal of Humanities and Social Sciences Innovation ARRUS Journal of Social Sciences and Humanities ARRUS Journal of Mathematics and Applied Science VARIANSI: Journal of Statistics and Its Application on Teaching and Research Ininnawa: Jurnal Pengabdian Masyarakat ARRUS Jurnal Pengabdian Kepada Masyarakat Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat (JHP2M) Jurnal MediaTIK Journal of Mathematics, Computation and Statistics (JMATHCOS)
Sitti Masyitah Meliyana R.
Universitas Negeri Makassar
Religion Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Public Health Social Sciences Other

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Optimalisasi Partisipasi Masyarakat Melalui Focus Group Discussion (FGD) dalam Program Kampung Bersih Nusantara di Kelurahan Pannampu, Kecamatan Tallo, Kota Makassar Meliyana, Sitti Masyitah; Ahmar, Ansari Saleh; Rusli, R.; Rahman, Abdul; Musa, Hastuty
Panrannuangku Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2025)
Publisher : Lembaga Penelitian dan Pengembangan Teknologi dan Rekayasa, Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/panrannuangku3926

Abstract

Program Kampung Bersih Nusantara merupakan salah satu inisiatif strategis dalam mendukung pembangunan berkelanjutan dan peningkatan kualitas lingkungan permukiman. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk mengidentifikasi permasalahan kebersihan lingkungan dan menyusun solusi berbasis partisipasi masyarakat melalui pendekatan Focus Group Discussion (FGD) di Kelurahan Pannampu, Kecamatan Tallo, Kota Makassar. Metode pelaksanaan mencakup observasi lapangan, pelibatan tokoh masyarakat dan warga setempat, serta pelaksanaan FGD sebagai sarana komunikasi partisipatif. Hasil kegiatan menunjukkan bahwa FGD mampu menjadi media efektif dalam menggalang komitmen warga, menggali aspirasi lokal, dan menyusun rencana aksi kampung bersih secara kolektif. Kegiatan ini juga menghasilkan peta masalah lingkungan dan rencana tindak lanjut yang disepakati bersama. Program ini diharapkan dapat direplikasi pada kelurahan lain dengan penyesuaian konteks sosial dan budaya lokal.
Optimalisasi Media Sosial Sanggar Seni Budaya Saorajae Sulawesi Selatan Melalui Pemanfaatan Canva Sebagai Aplikasi Desain Grafis Hafid, Hardianti; Meliyana, Sitti Masyitah; Pratama, Muh. Isbar; Hamka, Rezky Amalia
Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat Vol. 2 No. 1 (2023): Volume 02 Nomor 01 (April 2023)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jhp2m.v2i1.134

Abstract

Pengabdian kepada masyarakat ini bertujuan untuk memberikan pelatihan pada anggota Sanggar Seni Budaya Saorajae tentang penggunaan aplikasi Canva dalam mempromosikan karya seni dan budaya. Sanggar Seni Budaya Saorajae adalah salah satu lembaga seni dan budaya di Indonesia yang berperan penting dalam melestarikan seni dan budaya lokal. Namun, promosi kegiatan seni dan budaya masih terbatas dan kurang efektif karena minimnya penggunaan media sosial dan desain grafis yang menarik. Oleh karena itu, kegiatan ini bertujuan untuk mengoptimalkan penggunaan media sosial Sanggar Seni Budaya Saorajae melalui pemanfaatan Canva sebagai aplikasi desain grafis. Metode yang digunakan dalam kegiatan ini meliputi studi literatur, identifikasi kebutuhan, pelatihan penggunaan Canva, implementasi, dan evaluasi. Pengelola dan seniman di Sanggar Seni Budaya Saorajae dilatih untuk menggunakan Canva dalam membuat desain grafis yang menarik dan kreatif untuk mempromosikan kegiatan seni dan budaya di media sosial. Evaluasi dilakukan untuk mengukur efektivitas penggunaan Canva dalam mempromosikan seni dan budaya di media sosial. Hasil kegiatan menunjukkan bahwa penggunaan Canva sebagai aplikasi desain grafis dapat meningkatkan efektivitas promosi seni dan budaya di media sosial. Para pengelola dan seniman di Sanggar Seni Budaya Saorajae dapat membuat desain grafis yang menarik dan kreatif dengan mudah menggunakan fitur-fitur Canva. Selain itu, penggunaan Canva juga membantu menghemat waktu dan biaya dalam pembuatan desain grafis. Sehingga kegiatan ini menunjukkan bahwa pemanfaatan Canva sebagai aplikasi desain grafis dapat membantu Sanggar Seni Budaya Saorajae dalam mengoptimalkan penggunaan media sosial untuk mempromosikan seni dan budaya secara lebih efektif dan kreatif.
Geographically Weighted Poisson Regression (GWPR) Model with Fixed Gaussian Kernel and Fixed Bi-square Kernel Weights Meliyana, Sitti Masyitah; Ahmar, Ansari Saleh; Siti Nurazizah Auliah
ARRUS Journal of Social Sciences and Humanities Vol. 5 No. 2 (2025)
Publisher : PT ARRUS Intelektual Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/soshum3812

Abstract

This study aims to model the spatial distribution of tuberculosis (TB) cases in Makassar City in 2022 using the Geographically Weighted Poisson Regression (GWPR) approach. This method extends Poisson regression by incorporating spatial heterogeneity, weighting each location based on its geographical proximity. Two types of kernel weighting functions, fixed Gaussian kernel and fixed bi-square kernel, were used to determine the most effective model for identifying key factors influencing TB case numbers. The parameter estimation results indicate that the GWPR model with fixed bi-square kernel performs better than the global Poisson regression model, achieving an Akaike’s Information Criterion (AIC) value of 97.69 and a coefficient of determination (R²) of 99.93%. The findings reveal that the relationship between predictor variables and TB cases varies across districts, with the percentage of the productive-age population and population density emerging as dominant factors. These results highlight the advantages of the GWPR approach in capturing spatial dynamics more effectively than conventional regression models, making it a powerful analytical tool for designing targeted, region-specific public health interventions.
Training on Structural Equation Modelling (SEM) Analysis for Lecturers at Patompo University: Pelatihan Analisis Structural Equation Modelling (SEM) Bagi Dosen Universitas Patompo Ruliana, Ruliana; Sudarmin, Sudarmin; Meliyana, Sitti Masyitah; Rais, Zulkifli
Mattawang: Jurnal Pengabdian Masyarakat Vol. 6 No. 2 (2025)
Publisher : Yayasan Ahmar Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.mattawang3180

Abstract

This community service project aims to enhance the understanding and skills of lecturers at Universitas Patompo in using Structural Equation Modelling (SEM) for research data analysis. The activity took place on September 18, 2024, and was attended by 28 lecturers. The main issues faced by the participants were a lack of understanding of SEM techniques and limited skills in using statistical software for analysis. The solution offered was an intensive training session that included the introduction of statistical software and the application of SEM using the Jamovi software. In addition, a community action planning process was implemented, involving the lecturers in the organization of the training. The results of this project showed a significant improvement in the participants' understanding and skills in SEM analysis.
Fuzzy Geographically Weighted Clustering Analysis of Poverty Indicators in South Sulawesi, Indonesia Annisa, Nurawalia; Aidid, Muhammad Kasim; Meliyana, Sitti Masyitah
JINAV: Journal of Information and Visualization Vol. 6 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav3949

Abstract

Cluster analysis is a method used to group data into several clusters, where the data within a single cluster exhibit high similarity, while the data between clusters show low similarity. This study aims to classify the regencies and cities in South Sulawesi based on poverty indicators using the Fuzzy Geographically Weighted Clustering (FGWC) method. FGWC is an integration of the classical fuzzy clustering approach with geo-demographic components, incorporating geographical aspects into the analysis. As a result, the clusters formed are sensitive to environmental effects, which influence the values of cluster centers. In this study, the optimal number of clusters was determined using the IFV (Index of Fuzzy Validity) validity index, which indicated an optimal solution of three clusters. Cluster 1 consists of 9 regencies/cities characterized by a high level of poverty. Cluster 2 comprises 7 regencies/cities with a moderate level of poverty. Cluster 3 includes 8 regencies/cities with a low level of poverty.
Regression Analysis of Panel Data on Gross Enrolment Rate (GER) At Junior High School and Equivalent Education Levels in South Sulawesi Province in 2018-2022 Elisa, Nur; Aidid, Muhammad Kasim; Meliyana, Sitti Masyitah
Quantitative Economics and Management Studies Vol. 6 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3932

Abstract

Panel data regression is a combination of time series and cross section data. This research aims to determine the factors that influence the gross participation rate in South Sulawesi Province using panel data regression analysis. The data used is data from 24 districts/cities in South Sulawesi province from 2018 to 2022 which was obtained through the website of the South Sulawesi Provincial Central Statistics Agency. There are three models in panel data regression analysis, namely the Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM). Based on the model selection carried out by carrying out the Chow Test, Hausman Test, and Lagrange Multiplier Test, the best model was obtained, namely the Random Effect Model. The equation of this model is Yit = 82,818 + 0,1485X1it − 0,0784X2it + 0,0053X3it + 0,0011X4it. Based on the results of panel data regression analysis, it was found that the variables that had a significant effect on the Gross Enrollment Rate in South Sulawesi province were the student to teacher ratio (X2), and population density (X4).
A Seasonal ARIMA (SARIMA) Model for Forecasting Domestic Passenger Traffic at Sultan Hasanuddin Airport Meliyana, Sitti Masyitah; Hafid, Hardianti; Mar'ah, Zakiyah; Muthahharah, Isma
Quantitative Economics and Management Studies Vol. 6 No. 1 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3935

Abstract

The growth of the domestic aviation industry in Indonesia has led to a significant increase in passenger numbers, particularly at major airports such as Sultan Hasanuddin Airport. Accurate forecasting of passenger traffic is essential for effective planning and resource allocation. This study aims to develop a suitable time series model to forecast the number of domestic air passengers departing from Sultan Hasanuddin Airport. Using monthly passenger data from January 2019 to April 2024 obtained from the Indonesian Badan Pusat Statistik (BPS), the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied. The modelling process followed the Box-Jenkins methodology, involving data exploration, stationarity testing, model identification, parameter estimation, diagnostic checking, and model validation. Among several candidate models, the ARIMA (0,1,1)(0,0,1)12 model was identified as the most appropriate, producing normally distributed, independent residuals and yielding a Mean Absolute Percentage Error (MAPE) of 4.5%. The results demonstrate that the SARIMA model provides a reliable tool for forecasting short-term domestic passenger flows at the airport.
Forecasting Indonesia’s Wholesale Price Index (WPI) Using the Holt's Exponential Smoothing Method Muthahharah, Isma; Meliyana, Sitti Masyitah; Mar’ah, Zakiyah
Quantitative Economics and Management Studies Vol. 6 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3937

Abstract

The Index of Wholesale Price (WPI) is a key benchmark in analyzing price movements at the wholesale level as it can affect the economic stability of a country. This research purpose to forecast the movement of WPI in Indonesia using Holt's Exponential Smoothing technique, which is effective in analyzing time series data that show trend patterns. This research utilizes secondary data obtained from the BPS for the period 2020-2024. The analysis is carried out by determining the optimal value of α and β parameters using trial and error techniques. Furthermore, the forecasting process is carried out using the best parameters that have been obtained. Based on the analysis results, the combination of parameters α = 0.9 and β = 0.8 provides a Mean Absolute Percentage Error (MAPE) value of 0.22%, which indicates a very good level of forecasting accuracy. WPI forecasting for the year 2025 shows a consistent upward pattern, reflecting a consistent increase in WPI previous historical trends. The results of this study can be a reference in making price and wholesale trade policies by the government and related parties in the economic sector.
Implementation K-Medoids Algorithm for Clustering Indonesian Provinces by Poverty and Economic Indicators Hafid, Hardianti; Meliyana, Sitti Masyitah; Muthahharah, Isma; Mar’ah, Zakiyah
Quantitative Economics and Management Studies Vol. 6 No. 2 (2025)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems3940

Abstract

Regional development disparities in Indonesia remain one of the main challenges in formulating national development policies. This study aims to classify the 38 provinces in Indonesia based on four key indicators: the percentage of the population living in poverty, Gross Regional Domestic Product (GRDP) per capita, the open unemployment rate, and the Human Development Index (HDI), using the K-Medoids algorithm. This method was chosen due to its robustness to outliers and its ability to produce representative clusters. The data used are secondary data obtained from the Central Bureau of Statistics (BPS). The analysis process began with data standardization, determination of the optimal number of clusters using the Elbow and Silhouette methods, followed by clustering implementation and result interpretation. The analysis results identified four main clusters with distinct socioeconomic characteristics. Cluster 1 reflects provinces with moderate conditions, Cluster 2 represents more developed provinces, Cluster 3 highlights regions facing significant development challenges, and Cluster 4 consists of provinces with the most underdeveloped socioeconomic conditions. These findings indicate that the K-Medoids algorithm is effective in identifying inter-provincial disparity patterns and can serve as a foundation for formulating more targeted and inclusive development policies.
Analysis Time Series (ARIMA): To determine the Development of Oil Exports in Indonesia Muthahharah, Isma; Meliyana, Sitti Masyitah
Eigen Mathematics Journal Vol 8 No 1 (2025): June
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v8i1.265

Abstract

Oil exports are the largest export in Indonesia. Indonesia's oil exports from year to year tend to fluctuate and in the end continue to decline, however in the last three years exports of oil products have continued to increase from the previous year. This research aims to analyze the development of oil exports in Indonesia. The data used in this research is doil export data from 1996 to 2023 obtained from data Indonesian Central Statistics Agency (BPS). The method used to analyze development of oil exports in Indonesia is Autoregressive Integrated Moving Average (ARIMA). The research results show that Indonesia's oil exports have experienced significant fluctuations from year to year, with a quite striking decline in export volume in recent years. The ARIMA model (2,2,2) was identified as the best model for predicting future behavior from oil export data. This model succeeds in describing the intrinsic patterns in the export data well. Using the ARIMA (2,2,2) model it is known that forecasting results development of oil exports in Indonesia (2024-2035) will experience an increase from the previous year.
Co-Authors Abdul Rahman Ahmad Yasir Aras Ahmar, Ansari Saleh Aidid, Muhammad Kasim Alok Kumar Panday Angri Lismayani Anisa Nurfadilah Nurdin Annisa, Nurawalia Baso Intang Sappaile Elisa, Nur Erman Syarif Hardianti Hafid Hastuty Musa Isma Muthahharah Isma Muthahharah Jamaluddin Jamaluddin Lince, Ranak Mar'ah, Zakiyah Mar’ah, Zakiyah Miguel Botto-Tobar Muhammad Ammar Naufal Muhammad Ansarullah S. Tabbu Muhammad Isbar Pratama Muthahharah, Isma Nachnoer Arss Parkhimenko Vladimir Anatolievich R. Rusli Rahman, Abdul Rahmat Hidayat Rais, Zulkifli Rezky Amalia Hamka Ruliana Ruliana, Ruliana Ruliana, R. Rusli Rusli Rusli Rusli Rustam, Sitti Nail Rustam, Sitti Nailah S. Sudarmin, S. Siti Nurazizah Auliah Sitti Nailah Rustam Sitti Nailah Rustam Sudarmin Sudarmin Yunus, Asmar Zakiyah Mar'ah Zakiyah Mar'ah Zakiyah Mar'ah Zakiyah Mar’ah Zulkifli Rais