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Sigit Nugroho
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Agglomerative Nesting (AGNES) Method and Divisive Analysis (DIANA) Method For Hierarchical Clustering On Some Distance Measurement Concepts Wijuniamurti, Susi; Nugroho, Sigit; Rachmawati, Ramya
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v1i1.21009

Abstract

Clustering data through hierarchical approach could be performed by Agglomerative Nesting (AGNES) Method and Divisive Analysis (DIANA) Method. The objective of this research is to compare both the methods based on Euclid and Manhattan distance measurements. Of this research the clustering procedures of agglomerative method are conducted by exploring all techniques including single linkage, complete linkage, average linkage, and Ward. The data used are the National Socio-Economic Survey (SUSENAS) data which are selected specifically for the percentage of over 5 year old residents in each province, for both living in urban or rural, who access the internet in the last 3 months in 2017 but classified according purpose of accessing. By applying Mean Square Error (MSE) for 2 and 3 clusters, it can be concluded that the single linkage technique is the best performance of clustering procedure for both Euclidean and Manhattan distances.
Partitioned Design Matrix Method for Two Factors Multivariate Design Alvionita, Renny; Nugroho, Sigit; Chozin, Mohammad
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v1i1.21010

Abstract

Factorial experiment often involves large data sets and the use of generalized inverse for the data analysis. It becomes less manageable as the data increased. The objective of this study is to evaluate the accuracy of partitioned design matrix method for two factors multivariate design. The design matrix is partitioned into several sub-matrices based on their source of variation. The partitioned design matrix method in two factors multivariate is much simpler than usual sigma summation method in calculating the sum of product matrix and the degrees of freedom. This method could also be used in explaining the derivation of the statistics for testing the hypothesis of the equality of the means which corresponds to the source of variation.
A Comparison of Weighted Least Square and Quantile Regression for Solving Heteroscedasticity in Simple Linear Regression Fransiska, Welly; Nugroho, Sigit; Rachmawati, Ramya
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v1i1.21011

Abstract

Regression analysis is the study of the relationship between dependent variable and one or more independent variables. One of the important assumption that must be fulfilled to get the regression coefficient estimator Best Linear Unbiased Estimator (BLUE) is homoscedasticity. If the homoscedasticity assumption is violated then it is called heteroscedasticity. The consequences of heteroscedasticity are the estimator remain linear and unbiased, but it can cause estimator haven‘t a minimum variance so the estimator is no longer BLUE. The purpose of this study is to analyze and resolve the violation of heteroscedasticity assumption with Weighted Least Square(WLS) and Quantile Regression. Based on the results of the comparison between WLS and Quantile Regression obtained the most precise method used to overcome heteroscedasticity in this research is the WLS method because it produces that is greater (98%).
Simulation of Sample Determination Quick Count Legislative Elections In Bengkulu City Gumilar, Andri Tresna; Nugroho, Sigit; Keraman, Buyung
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v1i1.21012

Abstract

In this research illustrates the simulation of quick count of sampling for the year 2014 Legislative Election in Bengkulu City, which has a data acquisition result for 589 TPS. The problem in this research is how to know the sample size and the right sampling method for Legislative Election in Bengkulu City on Year 2014. The purpose of this research is to know the sample size and the quick count calculation sampling method that can predict the actual vote result for Legislative Election. The method used in the calculation of fast calculation consists of three methods, simple random sampling, cluster random sampling and multistage random sampling. From the population data of 589 polling stations (TPS) into the population, the sample size was taken as much as 120 TPS or about 20% of the population, based on the results of calculations for sample sizes in a limited population. After the sample was selected, a sample simulation of 100 times for each method and simulation results was tested for compatibility with the chi-squared test. Based on the test results, it can be concluded that for sample size 120 TPS taken by simple random sampling method, cluster random sampling or multistage random sampling can predict the actual vote result in Legislative Election Year 2014 in Bengkulu with margin of error 5%. For efficiency consideration simple random sampling method can be selected.
Sentiment Analysis of Twitter User’s Perceptions of the Campus Merdeka Using Naïve Bayes Classifier and Support Vector Machine Methods Salsabilla, Intan; Alwansyah, Muhammad Arib; Nugroho, Sigit; Agwil, Winalia
Journal of Statistics and Data Science Vol. 2 No. 2 (2023)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v2i2.30577

Abstract

The Campus Merdeka program is being implemented by the government to realize autonomous and flexible learning in tertiary institutions to create a learning culture that is innovative, not restrictive, and the needs of students. The Campus Merdeka provides added value and is attractive and provides various responses from the public both directly and on different social media platforms. One of the social media platforms is Twitter. Therefore, research was conducted on the community's response to the Campus Merdeka program on Twitter social media. Twitter documents in the form of community response tweets to the Campus Merdeka program are classified into two categories, namely positive responses and negative responses. The method used in this study is the Naïve Bayes Classifier (NBC) and Support Vector Machine (SVM) with a Polynomial Degree 2 kernel. The highest level of accuracy resulting from this research is 73.5% with a parameter value of  of 0.5, a constant value  is 0.5, with training data of 309 documents for training data and 132 documents for test data. The accuracy results obtained for the Naïve Bayes Classifier method are 65.9% and for the Support Vector Machine method, an accuracy is 73.5%.
Enhancing Data Visualization Competencies Through Power BI Training Agwil, Winalia; Sunandi, Etis; Rizal, Jose; Faisal, Fachri; Nugroho, Sigit; Syahada, Sri; Hermalia, Hermalia
International Journal of Research in Community Services Vol 6, No 2 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijrcs.v6i2.901

Abstract

Vocational High School (SMK) aims to prepare students with the skills and knowledge required to meet industry demands. Recognizing the importance of data analysis and visualization in the workforce, this community service focuses on enhancing these competencies among SMKN 04 Kota Bengkulu students, particularly those in the Software Engineering program. A community service program was conducted to train students in utilizing Power BI for real-time and interactive data visualization. The training program included preparatory surveys, module development, and practical workshops. Students actively participated, demonstrating a greater interest and understanding of data visualization concepts. Evaluation results showed that 89% of participants found the training beneficial, and 84% mastered Power BI’s visualization techniques. The outcomes highlight the program's effectiveness in equipping students with industry-relevant skills, emphasizing the need for similar initiatives targeting broader student groups. This project bridges the gap between vocational education and the digital economy's demands.
Forestry Spatial Planning Policy Direction: Concerning the Long-Term National Development Plan 2025-2045 Margono, Belinda Arunarwati; Purwanto, Judin; Nugroho, Sigit; Widiyatno, Widiyatno
Jurnal Ilmu Kehutanan Vol 19 No 1 (2025): March
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jik.v19i1.18426

Abstract

The role of forests is related to the challenges of balancing food, water, and energy, which are likely to increase significantly in the near future. A science-based conception is needed to support the correct application of forest adequacy in terms of forestland and forest cover over a watershed or island to address these challenges and to strengthen the role of forests in performing economic, social, and ecological functions, mainly in the context of water, food, and energy security. However, the minimum extent of forest over land is still debatable. The determination of what is named forest adequacy, in terms of both forestland (kawasan hutan) and forest cover (penutupan hutan), needs to consider roles of biogeophysical factors, environmental carrying capacity, watershed characteristics, along with flora and fauna diversity. Spatial planning plays a crucial role in implementing the concept of determining the forest's adequacy based on spatial considerations to support the Forestry Spatial Planning Policy in the 2025-2045 National Development Plan to ensure the future security of water, food, and energy supply.
Pengabdian Kepada Masyarakat FMIPA 2024: Desa Cantik, Desa Cinta Statistik: Visualisasi Data dengan Statistik Deskriptif di Desa Panca Mukti Kabupaten Bengkulu Tengah Susi Wijuniamurti; Nugroho, Sigit; Novianti, Pepi; Sriliana, Idhia; Dyah Pangesti, Riwi
Jurnal Pengabdian Masyarakat Bumi Rafflesia Vol. 8 No. 1 (2025): APRIL: Jurnal Pengabdian Kepada Masyarakat Bumi Raflesia
Publisher : Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jpmbr.v8i1.8195

Abstract

Pembangunan desa dikatakan berhasil dan dapat terwujud jika masing-masing desa dapat mengenali potensi yang dimiliki. Menggali potensi desa memiliki hubungan yang erat dengan memberikan data yang akurat sehingga tugas pemerintah dalam perancangan pembangunan dapat tepat sasaran. Peran data sangat penting untuk menentukan bagaimana strategi dalam pembangunan desa. Bagi perangkat desa, meningkatkan kemampuan manajemen pengolahan data dan penggunaan data serta literasi statistik menjadi hal yang sangat penting. Penerapan teknologi akan mempermudah aparat desa dalam memahami pengolahan dan penyajian data statistik sehingga desa dapat secara mandiri mengidentifikasi potensi daerahnya. Prodi S1 Statistika, Prodi S2 Statistika dan pojok statistik Universitas Bengkulu bekerjasama dengan BPS dan mitra BPS Kabupaten Bengkulu tengah melalui program pengabdian kepada masyarakat melaksanakan kegiatan pelatihan dan pendampingan terhadap perangkat desa untuk meningkatkan kemampuan pengolahan, penganalisaan dan penyajian data statistik di bidang sektoral serta memaksimalkan penggunaan data dalam bentuk visualisasi data dengan statistik deskriptif  di Desa Panca Mukti. Kegiatan pelatihan visualisasi data dengan statistik deskriptif di Desa Panca Mukti memberikan hasil yang positif bagi masyarakat Desa Panca Mukti. Masyarakat Desa Panca Mukti, khususnya agen statistik dan perangkat desa dapat menampilkan data-data hasil survei ataupun sensus dalam bentuk diagram atau grafik yang mudah dipahami oleh semua orang. Data yang ada di Desa Panca Mukti ditampilkan di website resmi Desa Panca Mukti.
Forecasting A Weekly Red Chilli Price in Bengkulu City Using Autoregressive Integrated Moving Average (ARIMA) and Singular Spectrum Analysis (SSA) Methods Putriasari, Novi; Nugroho, Sigit; Rachmawati, Ramya; Agwil, Winalia; Sitohang, Yosep O
Journal of Statistics and Data Science Vol. 1 No. 1 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Red chili occupies a strategic position in the Indonesian economic structure because its use applies to almost all Indonesian dishes. Therefore, controlling the price of red chili is a necessity to maintain national economic stability. The purpose of this research is to forecast a red chili weekly price using ARIMA and SSA based on the weekly data of chili prices from January 2016 - December 2019 sourced from Statistics Indonseia (BPS) Branch Office of Bengkulu Province. The data have been analyzed using software R. Based on MAPE, ARIMA K (2,1,2) provides the best forecasting with value 0.49% while SSA 10.64%.
The Disparity of Maternal and Neonatal Death Modeling in Sumatra Region Using Geographically Weighted Bivariate Negative Binomial Regression Bayubuana, Muhammad Gabdika Bayubuana; Nugroho, Sigit; Rini, Dyah Setyo; Alwansyah, Muhammad Arib
Journal of Statistics and Data Science Vol. 3 No. 2 (2024)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v3i2.41285

Abstract

The Sumatra region occupies the second highest rank in terms of Maternal Mortality Rate (MMR) and Neonatal Mortality Rate (NMR) in Indonesia in 2020. Many factors are thought to have influenced these two cases, both directly and indirectly. So it is necessary to do an analysis to find out what factors influence MMR and NMR. The methods that can be used to determine these factors are Bivariate Negative Binomial Regression (BNBR) and Geographically Weighted Bivariate Negative Binomial Regression (GWBNBR). The results of the analysis show that the Deviance Information Criterion (DIC) in GWBNBR is smaller than BNBR, so GWBNBR is better than BNBR in modeling MMR and NMR in the Sumatra Region in 2020.
Co-Authors Achmad Binadja Achmad Djunaedi Adesi, Putri Adi Indrayanto Adriani, Desi Agi Ginanjar Agung Juliarto Agung Tri Prasetya Agwil, Winalia Ahmad Nasrulloh Alvionita, Renny Alwansyah, Muhammad Arib Ari Agung Nugroho, Ari Agung Arief, Yanwar Arief, Yanwar Aristya, Irma Sendy Arono Arono Azhar Abdul Rahman, Azhar Abdul Bahri, Syuhada Bayubuana, Muhammad Gabdika Bayubuana Betarina , Nurmalia Buyung Keraman Cerika Rismayanthi Ciptadi, Zaniar Dwi Prihatin Crisdianto, Riki Dewantara, Julian Dina Agustina, Dina Doni Pranata Duwi Kurnianto Pambudi Dyah Pangesti, Riwi Eka Swasta Budayati Eka Wahyudhi, Andi Sultan Brilin Susandi Eken, Özgür Fachri Faisal Fadhlia, Tengku Nila Fairuzindah, Athaya Feriza, Firman Firdaus Firdaus Firmansyah, Didi Fransiska, Welly Gumilar, Andri Tresna Haidar, Muhammad Daffa Hardiansyah Hardiansyah Haryanti, Wenny Herawati, Icha Herlin Fransiska Hermalia, Hermalia Hidayat, Bahril Idhia Sriliana Iskandar, Doddy Aditya Istislami, Yosuja Jomecho, Tommy Jose Rizal Jose Rizal Judin Purwanto, Judin Juliati, Kurnia Karuna, Elisabeth Evelin Kurniawan, Fuji Kurniawan, Yohan Lestari, Reza Lestari, Wina Ayu Leybina, Anna V Listyani, Nilla Lubis, Layla Takhfa Mahira, Rina Margono, Belinda Arunarwati Mariati, Dian Sri Marwan Maulana, Rifqi Adrian Mohammad Chozin, Mohammad Muhammad Salman Muliadi, Rahmad Mulyawan , Rizki Murgolo, Michael Nanang Wahyudin Napitupulu, Lisfarika Nasrullah, Ahmad Nasution, Silvia Fauziah Neni Lismareni, Neni Novi Susanti Nur Afandi Nurul Hidayati Okka Adittio Putra Oktarina, Cinta Rizky Panganiban, Teejay D. Pepi Novianti Perdana, Satya Pongsiri, Tatpicha Praningrum Pratiwi, Stevy Cahya Pusparani, Annisa Marchelyn Putriasari, Novi Qorifah, Nasha Nuryati rachmawati, Ramya Rahayu, Sundari Putri Razak, Ateerah Abdul Resi Vusvitasari Rifky Riyandi Prastyawan Riky Dwihandaka Rina Yuniana Rini, Dyah Setyo Rohani, Tri Salsabilla, Intan Sarumpaet, Mey Yanti Sebastian, Leonard Sihombing, Esther Damayanti Singh, Laishram Thambal Sitohang, Yosep O Slamet Widodo Solly Aryza Sri Wahyuni SRI WARDANI Stojanović, Stefan Sujadmi, Sujadmi Sulistiyono Sulistiyono Sumaryanti Sumaryanti Sunandi, Etis Suparyono, Sita Wardhani Suryadi Suryadi Susi Wijuniamurti Syahada, Sri Syahrul Akbar Talib, Kamal bin Tri Hadi Karyono Umi Kalsum Vira Dila, Sondang Wali, Carles Nyoman Wang, Ziyu Wati, Dewi Rohma Wawan Sundawan Suherman Wenni Anggita, Wenni Widiyatno Widodo, Fanani Haryo Widodo Widodo, Haryo Wijuniamurti, Susi Yassin, Abdulnassir Yoga Pratama YULIANA RAHMAWATI, YULIANA