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All Journal Publikasi Pendidikan Jurnal Daya Matematis Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) BAREKENG: Jurnal Ilmu Matematika dan Terapan MATAPPA: Jurnal Pengabdian Kepada Masyarakat EIGEN MATHEMATICS JOURNAL Jurnal Varian Inferensi Economics and Digital Business Review Mattawang: Jurnal Pengabdian Masyarakat Quantitative Economics and Management Studies Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Panrannuangku Jurnal Pengabdian Masyarakat ARRUS Journal of Mathematics and Applied Science Abdimas Langkanae Journal of Mathematics: Theory and Applications Seminar Nasional Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Bhinneka Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Ininnawa: Jurnal Pengabdian Masyarakat Jeinsa : Jurnal Ekonomi Ichsan Sidenreng Rappang ARRUS Jurnal Pengabdian Kepada Masyarakat Abdi Kimia : Jurnal Pengabdian Masyarakat Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat (JHP2M) SMART: Jurnal Pengabdian Kepada Masyarakat Journal of Mathematics, Computation and Statistics (JMATHCOS) Jurnal Akademik Pengabdian Masyarakat Ichsan Sidenreng Rappang
Muthahharah, Isma
Universitas Patompo Makassar
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Pengenalan Tables, AutoSum, & Charts Pada Microsoft Excel Untuk Siswa UPT SMAN 8 Takalar Fatwa, Inayanti; Muthahharah, Isma; Harjuna, Hariani; Syamsinar, Syamsinar; Amrullah, Nursinah
Panrannuangku Jurnal Pengabdian Masyarakat Vol. 3 No. 2 (2023)
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/panrannuangku1831

Abstract

Tables, Autosum, dan Charts merupakan suatu aplikasi yang dapat ditemukan pada aplikasi Microsoft Excel, pada menu Insert dan Formulas. Microsoft Excel sudah tidak asing lagi bagi siswa, namun dalam memahami penggunaan aplikasinya masih sangat kurang. Microsoft Excel merupakan sebuah program aplikasi lembar kerja yang dibuat dan didistribusikan oleh Microsoft Corporation. Penggunaan aplikasi ini dapat digunakan untuk mempermudah dalam pembuatan tables, diagram, dan menyelesaikan perhitungan matematika. Adapun dari 25 siswa kelas X UPT SMAN 8 Takalar, terdapat 20% peserta yang tidak paham akan praktikum yang dilakukan dan terdapat 80% mampu mengikuti setiap arahan yang diberikan selama praktikum. Metode yang digunakan adalah pembimbingan pelatihan dan pendampingan. Luaran yang hendak diupayakan dan dicapai yakni: (1)Meningkatnya pengetahuan dan keterampilan para siswa di sekolah mitra mengenai tables, autosum, dan charts pada Microsoft Excel.(2)Terciptanya produk berupa pengenalan table, autosum, dan chart pada microsoft excel yang dapat diterapkan dalam pembelajaran di sekolah mitra.(3)Publikasi ilmiah di jurnal nasional.
Pelatihan Pembuatan Komposter Alat Pengolah Limbah Organik di Kampung Bersih Nusantara Kota Makassar Meliyana, Sitti Masyitah; Rustam, Sitti Nail; Rahman, Abdul; Muthahharah, Isma; Hafid, Hardianti
Panrannuangku Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2024)
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/panrannuangku2616

Abstract

Sampah yang tidak dikelolah dengan baik dapat mencemari lingkungan, mengganggu ekosistem, dan mengancam kesehatan manusia. Di Kampung Bersih Nusantara telah tersedia Bank Sampah sehingga masyarakat dapat menyetorkan sampah anorganic mereka ke Bank Sampah tersebut. Namun belum ada solusi untuk sampah organik seperti sisa-sisa tanaman, sampah rumah tangga dan lain-lain. Sehingga tujuan kegiatan ini adalah memberikan pelatihan pembuatan komposter pengolah sampah limbah organik dan memudahkan daur ulang limbah organik. Dengan adanya pelatihan pembuatan komposter sederhana masyarakat dapat membuat sendiri alat komposter dan masyarakat mampu mengolah sampah rumah tangga secara mandiri.
Classification Poverty Levels in Indonesia Using Discriminant Analysis Muthahharah, Isma; Hafid, Hardianti
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.6816

Abstract

Poverty is a complex global challenge affecting countries like Indonesia that seek to improve the welfare of their citizens. Although the number of Indonesia's poor has fluctuated over the past few years, the study shows a decline in 2022. Using Multivariate Discriminant Analysis, this study aims to classify poverty levels in Indonesian provinces. Previous findings highlighted the relationship between the poverty depth index and average and duration of schooling. Through the development of classification models, this research seeks to provide a better understanding of poverty factors and support more effective policymaking in combating poverty in various regions. Using secondary data from the Central Bureau of Statistics in 2022, this research is quantitative research that produces important insights for the formulation of poverty eradication policies and programs in Indonesia. The result is the low provincial group of 20 provinces only 10 provinces are correctly predicted, the remaining 10 are predicted in the high province group. The same thing happened in the high province group of 13 provinces, only 9 provinces were correctly predicted, while the remaining 4 were predicted in the low group.
Pendampingan Pengisian Kuesioner Penelitian Bagi Guru SDN 30 Panaikang Kabupaten Pangkep Muthahharah, Isma; Juhari, Agusalim; Bungatang, Bungatang; St. Habibah, St. Habibah; Asmayani, Asmayani
Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat Vol. 4 No. 1 (2025): Volume 04 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jhp2m.v4i1.8491

Abstract

Kuesioner atau angket adalah metode pengumpulan data yang dilakukan dengan menyajikan serangkaian pertanyaan terkait masalah penelitian. Kegiatan pendampingan pengisian instrumen penelitian bagi guru SDN 30 Panaikang Kabupaten Pangkep dengan jumlah peserta sebanyak 10 orang yang di laksanakan pada bulan awal bulan Januari 2025. Kuesioner atau angket adalah metode pengumpulan data yang dilakukan dengan menyajikan serangkaian pertanyaan terkait masalah penelitian. Tujuan kegiatan pendampingan ini adalah untuk memastikan bahwa mereka memahami isi kuesioner, mengisi dengan benar, dan memberikan jawaban yang sesuai dengan kondisi sebenarnya. Hal ini dapat dibuktikan dari antusiasme guru dalam melakukan pengisian, dimana karakteristik jawaban 10 guru beragam, dimana variabel Kualitas Kerja Guru di semua respon memliki jawaban yang baik pada setiap item pertanyaan artimya banyak yang menjawab “Sangat Setuju”, sedangkan Interpersonal Skill dan Gaya Kepemimpinan Kepala Sekolah memiliki jawaban yang bervariasi pada setiap pertanyan, atau dengan kata lain respon menjawab “Setuju” dan “Tidak Setuju” dan hanya sedikit yang menjawab “Sangat Setuju” pada setiap item pertanyaan pada kuesioner penelitian.
Membangun Budaya Literasi Akademik: Sosialisasi Penulisan Karya Tulis Ilmiah bagi Siswa SMA Negeri 5 Bantaeng Meliyana R, S.Pd, M.Si, Sitti Masyitah; Isma Muthahharah; Zakiyah Mar’ah; Muh. Isbar Pratama; Hardianti Hafid
Ininnawa : Jurnal Pengabdian Masyarakat Vol. 3 No. 1 (2025): Vol. 3 No. 1 (2025): Volume 03 Nomor 01 (April 2025)
Publisher : Program Studi Manajemen FEB UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/ininnawa.v3i1.8207

Abstract

Scientific writing skills are essential competencies that high school students must acquire as part of strengthening academic literacy. However, observations at SMA Negeri 5 Bantaeng revealed that most students lack a solid understanding of scientific writing concepts and techniques. This community service program aimed to provide socialization and training on scientific writing to improve students’ academic literacy. The program involved several stages: pretest, material delivery, workshops, group discussions, writing assistance, result presentations, and posttest. The results showed a significant improvement in students' understanding, evidenced by a 30-point increase in posttest scores. Additionally, participants' enthusiasm and positive feedback from both students and teachers indicated that the activity was relevant and beneficial. This program is expected to contribute to fostering a scientific writing culture among high school students.
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.
Kernel-Truncated Spline: Estimator Fleksibel untuk Regresi Nonparametrik Hidayat, Rahmat; Muthahharah, Isma; Resmawan, Resmawan
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 13 Issue 2 August 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v13i2.33062

Abstract

This study aims to develop a multivariable nonparametric regression model using a hybrid approach that combines Spline and kernel estimators. This method is proposed to address the limitations of conventional nonparametric models that typically apply a single type of estimator across all predictor variables, regardless of their individual patterns. In this approach, predictors with oscillatory patterns are modeled using truncated Spline regression, while variables exhibiting complex nonlinear behavior are modeled using a Gaussian kernel estimator. The combined model is constructed and estimated using the Ordinary Least Square (OLS) method and applied to data on the average years of schooling in South Sulawesi Province, Indonesia. Results indicate that the model using two Spline knots and an optimal bandwidth for the kernel component yields the lowest Generalized Cross Validation (GCV) value of 0.142, outperforming models with one or three knots. The best-fitting model achieves a coefficient of determination (R²) of 91.214% and a Mean Squared Error (MSE) of 0.0461. These findings suggest that the hybrid regression approach offers greater flexibility and accuracy in modeling multivariable social data.
Co-Authors Abdul Rahman Agusalim Juhari Aidid, Muhammad Kasim Alfiah Nurfadhilah AM Hindi Amran Amrullah, Nursinah Andi Syukriani Aslindawati, Nur Asmayani Asmayani Asmirani, Sri BT Samsuddin, Yati Bungatang Bungatang Bungatang Bungatang Hamzah, Qardawi Hapsan, Amran Hardianti Hafid Hariani Harjuna Hariani Harjuna Harjuna, Hariani Inayanti Fatwa Indradewa, Rhian Islamiah, Farida Khadijah Khaidarsyah Khaidarsyah Mar'ah, Zakiyah Mar’ah, Zakiyah Masyitah Meliyana, Sitti Meliyana R, S.Pd, M.Si, Sitti Masyitah Muhammad Isbar Pratama Nur Aslindawati Pratiwi, Kartika Septiary Rahmat Hidayat Resmawan Resmawan Rusdianto Rusdianto Rusdianto Rusdi Rustam, Sitti Nail S. Sugianty Sapinah Sapinah Septiary Pratiwi, Kartika Sitti Masyitah Meliyana R. St. Habibah, St. Habibah Sutamrin Syahrul Syahrul Syalsabila, Annisa Syamsinar Yati BT Samsuddin Zakiyah Mar'ah Zakiyah Mar’ah