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All Journal Jurnal Gaussian Jurnal Sains Matematika dan Statistika Jurnal DIDIKA: Wahana Ilmiah Pendidikan Dasar SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan EDUMATIC: Jurnal Pendidikan Informatika Variance : Journal of Statistics and Its Applications Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi
Siti Hariati Hastuti
Universitas Hamzanwadi
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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PENERAPAN METODE CLUSTERING SELF ORGANIZING MAPS (SOM) DAN K-AFFINITY PROPAGATION (K-AP) DALAM MENGELOMPOKKAN NILAI TUKAR PETANI DI INDONESIA 2022 Siti Hariati Hastuti; Wiwit Pura Nurmayanti; Apriska Ayu Saputri
VARIANCE: Journal of Statistics and Its Applications Vol 5 No 1 (2023): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol5iss1page79-88

Abstract

Sektor pertanian masih menjadi sorotan utama di Indonesia, hal ini dikarenakan kontribusi sektor pertanian terhadap perekonomian nasional cukup besar dan penyerapan tenaga kerja pada sektor pertanian terbilang cukup tinggi. Keberhasilan pembangunan di sektor pertanian dapat dilihat pada tingkat kesejahteraan petani dengan indikator Nilai Tukar Petani (NTP). Dalam rangka meningkatkan kesejahteraan petani di Indonesia dibutuhkan suatu analisis pengelompokan wilayah yang berguna untuk memetakan persebaran tingkat kesejahteraan petani. Analisis yang dapat digunakan adalah analisis clustering dengan algoritma Self Organizing Maps (SOM) dan K-Affinity Propagation (K-AP). Kedua metode cluster tersebut dapat diterapkan hampir disemua sektor, salah satunya sektor pertanian. Penelitian bertujuan untuk menguraikan hasil clustering metode SOM dengan K-AP dan untuk mengetahui hasil pengelompokan NTP terbaik antara metode SOM dengan K-AP. Hasil penelitian dengan metode SOM dan K-AP cluster terbaik yang terbentuk sebanyak 3 cluster. Pada metode SOM cluster 1 terdapat 14 provinsi, cluster 2 terdapat 19 provinsi dan cluster 3 terdapat 1 porvinsi. Sedangkan untuk metode K-AP, terdapat 11 provinsi pada cluster 1, 22 provinsi pada cluster 2 dan 1 provinsi cluster 3. Metode SOM memiliki nilai rasio sebesar 18,59997 dan pada metode K-AP memiliki nilai rasio sebesar 38,04833. Dari nilai rasio yang didapatkan pada kedua metode tersebut, dapat disimpulkan bahwa nilai rasio metode SOM lebih kecil dibandingkan K-AP, sehingga analisis cluster data NTP berdasarkan subsektor pertanian di Indonesia tahun 2022 lebih baik jika menggunakan metode SOM dengan 3 cluster.
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI ANGKA PUTUS SEKOLAH DI NUSA TENGARA BARAT MENGUNAKAN GENERALIZED POISSON REGRESION Ristu Haiban Hirzi; Ayu Septiani; Siti Hariati Hastuti; Jatiatul Muhsinah; Rodi Satriawan; Abdullah Abdullah
Jurnal DIDIKA: Wahana Ilmiah Pendidikan Dasar Vol. 9 No. 2 (2023): JURNAL DIDIKA : WAHANA ILMIAH PENDIDIKAN DASAR
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/didika.v9i2.22701

Abstract

Pendidikan adalah suatu modal dasar kemajuan suatu bangsa. Indonesia mengalami krisis pendidikan dengan hasil yang konsisten berada di peringkat bawah dalam beberapa riset internasional. Salah satu permasalahan dalam bidang pendidikan yang dihadapi bangsa Indonesia saat ini adalah keberadaan anak putus sekolah. Salah satu provinsi yang ada di Indonesia yang memiliki permasalahan tingginya angaka putus sekolah adalah Provinsi Nusa Tengara Barat. Berdasarkan data Dinas Pendidikan dan Kebudayaan dalam NTB Satu Data (2022), angka putus sekolah jenjang SD, SMP, SMA/SMK pada tahun ajaran 2021/2022 memang masih cukup besar. Untuk jenjang SD, jumlah siswa yang putus sekolah sebanyak 344 orang atau 0,07 persen. Sedangkan untuk jenjang pendidikan SMP, jumlah siswa yang putus sekolah di NTB sebanyak 43 orang. Sementara, angka putus sekolah untuk jenjang SMA sebanyak 47 orang. Jenjang pendidikan berikutnya yang banyak siswa putus sekolah adalah SMK, sebanyak 249 orang atau 0,34 persen. Angka putus sekolah disebabkan karena faktor ekonomi seperti persentase penduduk miskin, jumlah pengangguran, pendapatan/PDRB perkapita, indeks pembangunan manusia serta faktor lain yang diduga mempengaruhi angka putus sekolah. Hal tersebut dapat diatasi menggunakan metode Generalized Poisson Regression (GPR). Tujuan penelitian ini adalah untuk mengetahui faktor-faktor yang mempengaruhi angka putus sekolah di Provinsi Nusa Tenggara Barat. Hasil penelitian menunjukkan bahwa faktor-faktor yang berpegaruh signifikan terhadap jumlah anak putus sekolah tingkat SMK di Provinsi Nusa Tenggara Barat tahun 2023 adalah kepadatan penduduk, IPM, APM dan angka buta huruf.Kata Kunci: Angka Putus Sekolah, Regresi, Generalized Poisson Regression (GPR)
KAJIAN SIMULASI PERBANDINGAN METODE RIDGE REGRESSION DAN ADJUSTED RIDGE REGRESSION UNTUK PENANGANAN MULTIKOLINEARITAS Nisa, Choirun; Hastuti, Siti Hariati
Jurnal Gaussian Vol 12, No 3 (2023): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.12.3.330-339

Abstract

Regression analysis is widely used in research. However, often in using this analysis the assumption of non-multicollinearity is not fulfilled. Handling of these problems can be done using Ridge Regression (RR) and Adjusted Ridge Regression (AR) methods. This study aims to compare the performance of RR and AR in handling multicollinearity among explanatory variables in multiple regression analysis using data simulation. The simulated data contain various multicollinearity level (ρ = 0.6, 0.8, 0.9) with of each different sample size (n = 20, 50, 100). The performance of the two methods are compared using Mean Square Errors (MSE). The result shows that the AR method and the RR method produce a smaller MSE value when the sample size used is larger. The MSE value generated by the AR method tends to be smaller than the RR method which can be seen from each data repetition used. It shows that the AR method is relatively more effective than the RR method for dealing with multicollinearity problems.
Penerapan Metode OPTICS dan ST-DBSCAN untuk Klasterisasi Data Kesehatan Hastuti, Siti Hariati; Septiani, Ayu; Hendrayani, Hendrayani; Nurmayanti, Wiwit Pura
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.25765

Abstract

One way to extract valuable insights from large datasets is through cluster analysis. This statistical technique involves grouping data objects based on their similarities, aiming to create distinct groups where objects within each group share high similarities but differ significantly from objects in other groups. Cluster analysis, such as the OPTICS and ST-DBSCAN methods, can be utilized in various domains, including healthcare workforce and demographic data. In a case study focusing on health workers in East Lombok, these clustering methods were employed. The study aimed to present the outcomes of clustering health workers using OPTICS and ST-DBSCAN and determine the superior method through internal validation. The results from OPTICS revealed the formation of 5 clusters: cluster-1 with two sub-district members, cluster-2 with three members, cluster-3 with two members, cluster-4 with three members, and cluster-5 with seven members. Conversely, ST-DBSCAN produced only 2 clusters: cluster-1 with six members and cluster-2 with four members. Based on the internal validation findings, OPTICS emerged as the more effective method for categorizing health workers in East Lombok.
SPATIAL AUTOREGRESSIVE (SAR) POISSON MODELING IN DENGUE FEVER CASES ON LOMBOK ISLAND IN 2021 Husnaeni, Ririn Robiatul; Hauliati, Siti; Sholihah, Imroatun; Lasmiani, Bq Tia Ayu; Hastuti, Siti Hariati; Gazali, Muhammad
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 2 (2024): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol6iss2page143-154

Abstract

Indonesia, the fourth most populous country in the world with 275.5 million people, faces increasing human activity that can lead to negative impacts such as the spread of infectious diseases. One of these diseases is Dengue Hemorrhagic Fever (DHF), which is particularly susceptible in residential areas with poor environmental hygiene. The rising number of DHF cases on Lombok Island is a significant concern. This study employs a spatial analysis modeling approach, specifically the Spatial Autoregressive Poisson (SAR Poisson) model, which considers the spatial dependence of dengue cases assumed to follow a Poisson distribution. The objective is to model and map the potential distribution of DHF cases on Lombok Island in 2021. The analysis reveals spatial autocorrelation in the data based on Moran's I. Significant variables affecting DHF cases include the number of permanent sanitation facilities (X2) and the number of drinking water facilities (X3). Mapping results based on the SAR Poisson model indicate that the distribution of DHF cases is relatively uniform across most sub-districts, with the highest incidence suspected in Tanjung Sub-district
ANALISIS SPASIAL BERBASIS PEMETAAN MENGGUNAKAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) PADA SEBARAN JUMLAH WISMA DI KABUPATEN LOMBOK BARAT Deviani, Deviani; Wulandari, Baiq Yuliandita; Askariyah, Askariyah; Fitri, Ika Julia; Hastuti, Siti Hariati
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 5 No. 2 (2024): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v5i2.545

Abstract

This research aims to analyze the effect of population density, number of food stalls, and population on the number of homesteads using the Geographically Weighted Regression (GWR) model. GWR modeling is carried out based on spatial data using secondary data sourced from the Central Statistics Agency (BPS). First, multiple linear regression analysis was carried out to evaluate the relationship between variables. The results of multiple linear regression show that only the variable number of food stalls has a significant effect on the number of homesteads. Next, spatial aspects were tested, including spatial autocorrelation tests and spatial heterogeneity tests. Testing spatial aspects shows the existence of spatial autocorrelation and spatial heterogeneity in the data. Therefore, we continued with GWR modeling to obtain a more in-depth picture of the distribution of the number of homesteads in West Lombok Regency. The results of modeling with GWR show that the variables used have a spatially varying influence throughout the West Lombok Regency area. Mapping GWR results produces better modeling of the factors that influence the number of homesteads in each village. A comparison between the multiple linear regression model and the GWR shows that the GWR model is able to explain variations in the number of homesteads with a higher R-square and a smaller AIC value
Pemetaan Kasus DBD di Pulau Lombok menggunakan Regresi Binomial Negatif berbasis Geografis Ayundasari, Dita Septiana; Hastuti, Siti Hariati; Kertanah, Kertanah
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 2 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i2.27460

Abstract

According to the Indonesia Health Profile Report 2022, NTB Province is among the 11 provinces with the highest incidence rate of dengue hemorrhagic fever (DHF). On Lombok Island, there were 2,074 cases with 4 deaths in 2022. DHF remains a serious threat in Lombok, so this study aims to map sub-districts based on significant factors for the spread of DHF in 54 sub-districts throughout Lombok Island. This study used quantitative analysis with one response variable, the number of DHF cases, and three predictor variables: the ratio of medical personnel (nurses) (X1), the percentage of proper sanitation facilities (healthy latrines) (X2) and the percentage of standard drinking water facilities (X3) in 54 sub-districts. Data were obtained from the Health Office throughout Lombok Island. Analysis techniques include descriptive analysis, GWNBR modeling, and significant variable mapping. The mapping results showed six groups of sub-districts with a combination of significant variables, which included variables X1, X2, and X3. The findings suggest the need for additional studies or prevention policies that are more focused on hygiene to reduce the risk of DHF spread. Related parties also need to be informed to take strategic steps based on these findings.
Pendampingan pemanfaatan limbah rumah tangga menjadi pupuk organik dengan komposter bahan bekas Basirun, Basirun; Kartanah, Kartanah; Hidayaturrohman, Umam; Hastuti, Siti Hariati
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 2 (2025): March
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i2.29775

Abstract

Abstrak Limbah rumah tanpa disadari terus diproduksi pada setiap aktivitas yang dilakukan terutama dilingkungan dapur sehingga volume sampah pada TPA terus meningkat. Permasalahan ini dapat teratasi dengan adanya pengetahuan dan keterampilan serta kesadaran setiap rumah tangga untuk melakukan pengolahan sederhana dengan mengolahnya menjadi pupuk organik. Tujuan dilakukan kegiatan pendampingan ini adalah meningkatkan kesadaran, pengetahuan, dan keterampilan masyarakat dalam pengolahan sampah menjadi pupuk organik sehingga sampah yang dihasilkan tidak lagi ditimbun untuk disalurkan ke tempat pembuangan akhir. Metode pendampingan ada tiga yaitu sosialisasi, praktik dan evaluasi. Kegiatan diawali dengan sosialisasi kemudian praktik dan evaluasi kegiatan. Mitra  saasaran adalah pengelola HIFARM dan masyarakat sekitar dengan peserta yang hadir sebanyak 23 orang. Hasil pendampingan menunjukkan bahwa tumbuhnya kesadaran, meningkatnya pengetahuan dan keterampilan masyarakat dalam mengolah limbah dapur yang dihasilkan menjadi pupuk organik dengan menggunakan komposter yang terbuat dari ember bekas. Bukti peningkatan dilihat dari hasil evaluasi bahwa setelah pendampingan didapatkan sebesar 75% peningkatan baik itu pengetahuan maupun keterampilan sehingga secara perlahan dan menjadi kebiasaan yang terus dilakukan  untuk mengurangi volume sampah. Kata kunci: limbah rumah tangga; komposter; pupuk organik Abstract Unconsciously, household waste continues to be produced in every activity carried out, especially in the kitchen environment, so that the volume of waste in the landfill continues to increase. This problem can be resolved with the knowledge, skills and awareness of every household to carry out simple processing by processing it into organic fertilizer. The aim of this mentoring activity is to increase community awareness, knowledge and skills in processing waste into organic fertilizer so that the waste produced is no longer landfilled to be distributed to final disposal sites. There are three mentoring methods, namely socialization, practice and evaluation. The activity begins with socialization then practice and evaluation of the activity. The target partners are HIFARM managers and the surrounding community with 23 participants attending. The results of the assistance show that there is growing awareness, increased knowledge and skills of the community in processing the resulting kitchen waste into organic fertilizer using a composter made from used buckets. Evidence of improvement can be seen from the evaluation results that after mentoring, there was a 75% increase in both knowledge and skills so that it slowly and became a continuous habit to reduce the volume of waste. Keywords: household waste; composter; organic fertilizer
Analisis Faktor-Faktor yang Mempengaruhi Jumlah Kasus Tuberculosis di Kabupaten Lombok Timur menggunakan Model Spatial Autoregressive Poisson Adini, Ertina Septia; Azizah, Efida; Hastuti, Siti Hariati; Ghazali, Muhammad
Jambura Journal of Probability and Statistics Vol 6, No 1 (2025): Jambura Journal of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v6i1.30913

Abstract

Tuberculosis (TB) is a deadly infectious disease caused by the bacteria Mycobacterium tuberculosis. According to the NTB Provincial Health Office, the number of TB cases in NTB Province was reported as many as 7,305 cases in 2019. East Lombok Regency in that year recorded 1,521 TB cases. The high number of TB cases in East Lombok Regency is an interesting reason to use statistical analysis techniques in modeling variables that influence the number of TB cases in East Lombok Regency. This study uses Spatial Autoregressive Poisson (SAR Poisson) analysis. This method is a development of the classical regression method by considering spatial dependence on the dependent variable, namely count data that follows the Poisson distribution. According to the results of the study, there is significant spatial dependence on the data based on the results of the Moran's I test. The results of the SAR Poisson modeling show that only the Population Density variable (X_4) has a significant effect on the number of TB cases in East Lombok Regency with a parameter value of -1.24 x 10^{-21}. The corrected determination coefficient showed quite high results with a value of 71.8\%, which means that the model can explain most of the variability in the data, which is an indication that the model has a good fit and high relevance to the data. The results of the mapping of the comparison of actual data and the estimated value of TB cases from the SAR Poisson model showed similar results. 
Analisis Geographically Weighted Regression (GWR) Berbasis Pemetaan pada Jumlah Menara Telepon Seluler di Kabupaten Lombok Tengah Tahun 2021 Wati, Rana Ambarwati; Febiana, Izu Izatul; Hastuti, Siti Hariati
Jambura Journal of Probability and Statistics Vol 6, No 1 (2025): Jambura Journal of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v6i1.24770

Abstract

Cell towers are tall structures where telecommunications equipment and antennas are installed to support cellular networks. This research aims to analyze the influence of Population Size (X1) and the Number of Service Operators (X2) on the Number of Cellular Phone Towers (Y ) in 139 villages in Central Lombok Regency in 2021. The Geographically Weighted Regression (GWR) method is used to understand spatial variability in the relationship between variables (X1) and (X2) with respect to variable Y . This method is an advancement of the OLS regression analysis method, taking spatial variability into account. By using this method, it is hoped that more accurate spatial distribution patterns can be identified, along with solutions that can assist in the planning of telecommunications infrastructure development in this area. The analysis results indicate that there is significant spatial variability in the distribution of the number of cellular towers based on the Breusch-Pagan test. The significance test results for the parameters show that only the Population Size variable (X1) has a significant effect on the Number of Cellular Towers (Y ) across all observation units (villages) in Central Lombok Regency. The comparison of models shows that the GWR model for the Number of Cellular Towers is better than the OLS Regression, with lower AIC and SSE values and a higher coefficient of determination (R2). 
Co-Authors Abdullah, Abdullah Adini, Ertina Septia Amli, Istia Datul Apriska Ayu Saputri Askariyah, Askariyah Ayu Septiani Ayu Septiani, Ayu Ayundasari, Dita Septiana Azizah, Efida Basirun, Basirun Chintyana, Alissa CHOIRUN NISA Deviani Deviani Febiana, Izu Izatul Fitri, Ika Julia Ghazali, Muhammad Hardani, Bq Ika Hariani, Fitri Hauliati, Siti Hendrayani, Hendrayani Herniyati Herniyati, Herniyati Husnaeni, Ririn Robiatul Husnul Khotimah Jatiatul Muhsinah Kartanah, Kartanah Kertanah, Kertanah Lasmiani, Bq Tia Ayu Muhammad Gazali Nurmayanti, Wiwit Pura Ristu Haiban Hirzi, Ristu Rodi Satriawan Sastriana, Hanipar Mahyulis Sholihah, Imroatun Umam Hidayaturrohman Wati, Rana Ambarwati Wiwit Pura Nurmayanti Wulandari, Baiq Yuliandita