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All Journal The Journal of Experimental Life Sciences (JELS) Jurnal EECCIS SIGMA: Jurnal Pendidikan Matematika PYTHAGORAS: Jurnal Program Studi Pendidikan Matematika Jurnal Matematika Sains dan Teknologi Jurnal Saintek Lahan Kering Variance : Journal of Statistics and Its Applications Publik: Jurnal Manajemen Sumber Daya Manusia, Administrasi dan Pelayanan Publik Jurnal Statistika dan Aplikasinya Jurnal Sibermas (Sinergi Pemberdayaan Masyarakat) JAMBURA JOURNAL OF PROBABILITY AND STATISTICS International Journal of Health, Economics, and Social Sciences (IJHESS) Griya Journal of Mathematics Education and Application Parameter: Journal of Statistics Jurnal Info Sains : Informatika dan Sains Jurnal Kolaboratif Sains Jurnal Pijar MIPA Research in the Mathematical and Natural Sciences Research Review: Jurnal Ilmiah Multidisiplin Jurnal Riset Mahasiswa Matematika Journal of Artificial Intelligence and Digital Business Jurnal Ilmiah Ekonomi dan Manajemen Sciencestatistics: Journal of Statistics, Probability, and Its Application Journal of Mathematics, Computation and Statistics (JMATHCOS)
Siti Nurmardia Abdussamad
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Pemodelan Matematis Besaran Pengaruh pada Kasus Keputusan Pembelian Konsumen Gerai Rumah Karawo Abdussamad, Siti Nurmardia
Saintek Lahan Kering Vol 7 No 1 (2024): JSLK JUNI 2024
Publisher : Fakultas Pertanian, Universitas Timor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/slk.v7i1.2551

Abstract

The development of the business world has advanced very rapidly in the current era of globalization, where there is a lot of competition between companies that have the same business. One of the businesses that developed from the creations of children from the Gorontalo area is Karawo. Karawo is a symbol of Gorontalo's cultural identity, to this day not only has consumers in its own area but consumers outside the Gorontalo area. So it is important for companies to pay attention to attractiveness in terms of consumer purchasing decisions. Several factors that influence purchasing decisions include buyer awareness of a brand, product price and perceived quality. By using a mathematical model using a quantitative approach with a regression analysis method, it can describe whether there is an influence of brand awareness, price and perceived quality on consumer purchasing decisions at Gerai Rumah Karawo and the magnitude of the influence. The data collection technique was by distributing questionnaires to 68 respondents. The research results show that brand awareness, price and perceived quality simultaneously influence consumer purchasing decisions at the Rumah Karawo Outlet by 69.5%.
Comparison Of Radial Basis Function Neural Networks (RBFNN) And Autoregressive Moving Average (ARMA) Algorithms On Inflation Rate Prediction Models In Batam City Widya Reza; Febrya Christin Handayani Buan; Siti Nurmardia Abdussamad
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 02 (2024): Informatika dan Sains , Edition, June 2024
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/infosains.v14i02.4713

Abstract

The inflation rate in the city of Batam from January 2023 to April 2024 continues to fluctuate, so an accurate prediction model is needed so that inflation control can be carried out optimally. In this study, we conducted a comparative analysis between the Radial Basis Function Neural Network (RBFNN) method and the Autoregressive Moving Average (ARMA) model in predicting the inflation rate. The data used is historical data on the inflation rate of Batam City from January 2009 to April 2024. The results of the analysis show that the RBFN method with an MSE value of 0.239 is able to provide a more accurate prediction compared to the ARMA model (2.3) with an MSE value of 0.246 in predicting the inflation rate in Batam City. This is due to the RBFN's ability to capture complex and non-linear patterns contained in inflation data. In addition, the performance of RBFNN is also affected by the number of neurons and the basis function used. Thus, the results of this study show that the RBFN method can be an effective and efficient alternative in predicting the inflation rate in Batam City.
ANALISIS KUANTITATIF IMPLEMENTASI KEBIJAKAN PROGRAM BPJS KESEHATAN DI RSUD PROF. DR. ALOEI SABOE KOTA GORONTALO Abdussamad, Siti Nurcahyati; Abdussamad, Siti Nurmardia
Publik: Jurnal Manajemen Sumber Daya Manusia, Administrasi dan Pelayanan Publik Vol. 12 No. 1 (2025): Publik: Jurnal Manajemen Sumber Daya Manusia, Administrasi, dan Pelayanan Publ
Publisher : Universitas Bina Taruna Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37606/publik.v12i1.1712

Abstract

This research aims to determine the extent to communication and resources have on the effectiveness of the implementation of the BPJS Health program, both simultaneously and partially. The background to the problem of implementing the BPJS Health program is that for approximately 5 years, the BPJS Health program has always experienced a budget deficit. The main cause is the categories of BPJS Health participants who tend not to pay premiums on time and participants who only pay contributions when he just wanted to go to the hospital for treatment. This research uses quantitative research methods. The data collection technique is by distributing questionnaires to 100 samples who are BPJS Health users at RSUD Prof. Dr. Aloei Saboe, Gorontalo City. The research results show that communication and resources have a partial positive and significant influence of 21.8% and 62% respectively on the effectiveness of the implementation of the BPJS Health program and simultaneously the influence of communication and resources on the effectiveness of implementing the BPJS Health program was 61.3%.
Comparison of Word2vec and CountVectorizer with Mutual Information in Support Vector Machine (SVM) for Public Sentiment Analysis Doholio, Nadya Pratiwi; Hasan, Isran K; Abdussamad, Siti Nurmardia
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.v8i1.6640

Abstract

Social media is widely used today. Along with the development of social media, it makes it not only a means of communication but also a means of exchanging opinions. One of the social media that is widely used to exchange opinions is X (Twitter). X is widely used to express opinions, particularly on controversial issues, such as the relocation of IKN. Therefore, sentiment analysis is needed to analyse public opinion regarding this national issue. SVM is widely used to classify sentiment based on several required categories, such as positive or negative. However, SVM will work even more effectively if the features used have good quality. Therefore, feature extraction and selection are necessary to enhance SVM classification accuracy. The selection of appropriate feature extraction is very important for classification. Therefore, this study aims to compare two feature extractions, namely Word2Vec and CountVectorizer by adding Mutual Information feature selection to SVM in classifying public sentiment from X. The results show that SVM with Word2Vec and CountVectorizer is more effective than SVM with Mutual Information feature selection. The results show that SVM with Word2Vec feature extraction and Mutual Information feature selection is more effective overall with 84% accuracy, 90% precision, 90% recall, and 90% f1-score, compared to SVM with CountVectorizer feature extraction and Mutual Information feature selection which has 80% accuracy, 83% precision, 92% recall, and 87% f1-score.
Evaluation of the Adaptive Fuzzy Neuro Inference System and Fuzzy Model Time Series Markov Chains in Forecasting Crude Oil Prices Hinelo, Ikrar Prasetyo; Nuha, Agusyarif Rezka; Hasan, Isran K; Nasib, Salmun K; Abdussamad, Siti Nurmardia
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.v8i1.6763

Abstract

The development of a country's economy is greatly influenced by global economic conditions, given the increasingly close links between countries through economic relations and international cooperation. One of the main factors in economic growth is international trade, particularly export and import activities. Crude oil is one of the most actively traded commodities. Given the highly volatile crude oil market, accurate price forecasts are crucial in economic and financial decision-making. This study compares the performance of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Fuzzy Time Series Markov Chain (FTSMC) in forecasting the price of West Texas Intermediate (WTI) crude oil using time series data from 2020 to 2024 with saturated sampling technique. The implementation of both methods is carried out through Matlab Online and R-Studio software, with results showing that ANFIS has higher accuracy than FTSMC, as evidenced by the Mean Absolute Percentage Error (MAPE) value of 1,8010% for ANFIS and 3,7567% for FTSMC. Further analysis shows that ANFIS with a triangular membership function as well as significant lags at lag 1, lag 3, lag 4, and lag 7 is able to produce more accurate predictions and match the trend of actual data. Therefore, ANFIS is recommended as a more effective method in forecasting WTI crude oil prices, which can provide valuable insights for policy makers and industry stakeholders.
CFGWC-PSO in Analyzing Factors Affecting the Spread of Dengue Fever in East Java Province Abdussamad, Siti Nurmardia; Astutik, Suci; Effendi, Achmad
The Journal of Experimental Life Science Vol. 9 No. 3 (2019)
Publisher : Graduate School, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1060.997 KB) | DOI: 10.21776/ub.jels.2019.009.03.10

Abstract

Fuzzy Geographically Weighted Clustering-Particle Swarm Optimization using Context Based Clustering (CFGWC-PSO) has been developed to clustering in factors influencing the spread of dengue fever in East Java Province. CFGWC-PSO method can overcome slow computing time problems in terms of iterations, and produce accurate data partition with stable. In this research, CFGWC-PSO applied to 11 variables from data on the causes of the spread of dengue fever in East Java Province in 2017. CFGWC-PSO using the FCM method to determine the context variable. Processing used the results of clustering with 2 clusters until 5 clusters. From the three validation index that used to find out the right number of clustering, two clusters gave better clustering results. CFGWC-PSO shows that all districts/cities in cluster 2 become dengue fever endemic areas that need to be considered by the East Java Provincial Government.Keywords: Context-Based Clustering, dengue hemorrhagic fever, Fuzzy Geographically Weighted Clustering-Particle Swarm Optimization.
Optimalisasi Tata Kelola Pelayanan Administrasi Desa Berbasis Digital di Desa Limbato Kecamatan Tilamuta Kabupaten Boalemo Abdussamad, Juriko; Abdussamad, Zuchri; Abdussamad, Siti Nurcahyati; Abdussamad, Siti Nurmardia
Jurnal Sibermas (Sinergi Pemberdayaan Masyarakat) Vol 14, No 1 (2025): Jurnal Sibermas (Sinergi Pemberdayaan Masyarakat)
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/sibermas.v14i1.29055

Abstract

Desa Limbato, Kecamatan Tilamuta, Kabupaten Boalemo, menghadapi tantangan dalam penyelenggaraan pelayanan administrasi desa, khususnya terkait keterbatasan sumber daya manusia, sarana, prasarana, dan rendahnya penerapan digitalisasi layanan. Padahal, desa ini memiliki potensi besar dengan mayoritas penduduk berpendidikan sarjana dan capaian nominasi nasional PHBS. Untuk mengatasi permasalahan tersebut, dilaksanakan program pengabdian masyarakat melalui KKN-MBKM Terintegrasi dengan fokus optimalisasi tata kelola pelayanan administrasi berbasis digital. Metode yang digunakan meliputi sosialisasi, pelatihan pembuatan dan penggunaan website desa, serta simulasi layanan administrasi digital bagi aparatur desa selama 4 bulan. Hasil kegiatan menunjukkan bahwa aparatur desa mampu mengelola layanan administrasi secara digital, meningkatkan efisiensi pelayanan, serta memperluas akses informasi publik melalui website desa. Keberhasilan program ini diharapkan dapat mempercepat transformasi digital pemerintahan desa dan menjadi inspirasi bagi desa-desa lain di Kabupaten Boalemo dalam mewujudkan pelayanan publik yang efektif, efisien, dan transparan.
FORECASTING STOCK PRICES OF PT. BANK RAKYAT INDONESIA USING THE HYBRID ARIMA-BACKPROPAGATION NEURAL NETWORK METHOD Alaina, Silvana Rahmayanti; Hasan, Isran K.; Abdussamad, Siti Nurmardia
VARIANCE: Journal of Statistics and Its Applications Vol 7 No 1 (2025): 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/variancevol7iss1page39-48

Abstract

PT. Bank Rakyat Indonesia (Persero) Tbk is classified as a blue-chip stock. Although investing in BRI shares has the potential to generate profits, stock price fluctuations can pose risks, making forecasting necessary. The ARIMA model is frequently used to predict such fluctuations, but struggles to capture non-linear patterns. ARIMA is combined with an Artificial Neural Network (ANN), specifically the Backpropagation Neural Network, to address this issue and improve forecasting accuracy. Although Backpropagation is weak in slow convergence, this can be overcome using the Conjugate Gradient Powell Beale (CGB) algorithm. The research results show that the closing stock price data of BRI from January 2023 to February 2024 produced an ARIMA (1,1,1)-Backpropagation [4-4-1] model with higher accuracy, achieving a MAPE of 2.516% and RMSE of 200.1592, Relative to the standalone ARIMA (1,1,1) model, which had a MAPE of 6.203% and RMSE of 421.5896.
Pemodelan Multiple Discriminant Analysis Pada Perilaku Impulsive Buying Pengguna Shopee Pada Tanggal Cantik Naue, Siti Nurmeylisya; Yahya, Lailany; Abdussamad, Siti Nurmardia; Payu, Muhammad Rezky Friesta; Nasib, Salmun K
Griya Journal of Mathematics Education and Application Vol. 5 No. 2 (2025): Juni 2025
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v5i2.632

Abstract

Impulsive buying is a consumer behavior that makes purchases without prior planning. Impulsive buying is one of the consumer behavior phenomena that is increasingly widespread, especially on e‑commerce platforms such as Shopee during massive promotions on beautiful dates. Multiple Discriminant Analysis (MDA) is a method that has the advantage of classifying individuals into groups based on several predictor variables. The purpose of this study is to classify consumers into groups or categories based on their tendency to make impulse purchases on beautiful dates by analyzing the factors that influence them. The results of this study indicate that the beautiful date can affect the behavior of impulsive buying. The discriminant function model formed is able to distinguish categories of impulsive buying behavior with a good classification accuracy rate of 86.25% and the model shows that price is the most dominant or influential factor in distinguishing the category of impulsive buying of Shopee users on beautiful dates. This means that MDA Modeling is very helpful in classifying respondents into groups or categories based on the factors that influence them.
Penerapan Ensemble K-modes Pada Pengelompokkan Kelurahan di Kota Gorontalo Berdasarkan Kecanduan Game Online Remaja Taufik, Mohamad Alfiransyah; Achmad, Novianita; Abdussamad, Siti Nurmardia; Wungguli, Djihad; Yahya, Nisky Imansyah
Griya Journal of Mathematics Education and Application Vol. 5 No. 2 (2025): Juni 2025
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v5i2.633

Abstract

The swift advancement of digital technology has resulted in a heightened frequency of online game usage among teenagers, raising concerns about potential addiction. This study aims to cluster urban villages in Gorontalo City based on the characteristics of online game addiction in adolescents, to support the formulation of more effective preventive policies. The method used is ensemble clustering with K-modes algorithm approach, which is effective for mixed numeric and categorical data. Data were obtained through a survey of adolescents aged 10-24 years in all urban villages, including indicators of lack of attention from close people, self-control, lack of activities, stress or depression, social environment, parenting, length of time playing online games, frequency of playing online games and many favorite online games. The clustering results obtained 3 optimum clusters, where cluster 1 consists of 7 neighborhoods, cluster 2 consists of 17 neighborhoods and cluster 3 consists of 26 neighborhoods. Cluster 1 is a group of neighborhoods with a low risk and addiction level, cluster 2 with a moderate tendency, and cluster 3 with a high tendency.
Co-Authors Abdussamad, Siti Nurcahyati Agustina, Melisa Agusyarif Rezka Nuha Alaina, Silvana Rahmayanti Amanda Adityaningrum Amanda Adityaningrum Amanda Adityaningrum Armayani Arsal Asriadi Asriadi Asriadi Desya Neydi Putri Pakaya Dewi Rahmawaty Isa Dina Zulfiana Matiyeni Djafar, Fikriyanto Djihad Wungguli Doholio, Nadya Pratiwi Dwi Putri Juniar Adam effendi, Achmad FAHREZAL ZUBEDI Fajar Putrawan Djabar Febrya Christin Handayani Buan Hanz Franklyn Bachruddin Wewengkang Hinelo, Ikrar Prasetyo Ikhlas Ul Aqmal Ilato, Mutiara Ismail Djakaria Ismail Djakaria Isran K Hasan Isran K Hasan Isran K. Hasan Juriko Abdussamad Karim, Finansiya S. Abd. La Ode Nashar Lailany Yahya Marukai, Nur Amalia Meitasya wolah Mohamad Iswanto Rahman Mohamad, Rini Wahyuni Muhammad Rezky F. Payu Muhammad Rezky Friesta Payu Nadia Kasmin Hasan Nadya Pratiwi Doholio Naue, Siti Nurmeylisya Ni Luh Diyani Swarningsih Ni Wayan Tiarawati Nikmatisni Arsad NISKY IMANSYAH YAHYA Nurwan Nurwan Nur’ain Manoppo Pakaya, Desya Neydi Putri Putri Ayuningtias Mahdang Putu Ayu Indah N. Usia Putu Ayu Indah Nazwa Usia Qamarani Zatil Isma Darise Rahmi, Emli Rifandi Pratama Putra Kasadi Rizal Usman Salmun K. Nasib Shafiah Poliyama Siti Nurmeylisya Naue Suci Astutik Sulista Kamah Syafri Yandi Kudo Taufik, Mohamad Alfiransyah Vidya Avianti Hadju Wahyu Pratama Lasaleng Wahyu Pratama Lasaleng Widya Reza Widya Reza Zuchri Abdussamad