Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

2.855

P-Index

This Author published in this journals

All Journal Jurnal Matematika International Journal of Science and Engineering (IJSE) Media Statistika SAINS DAN MATEMATIKA JURNAL SISTEM INFORMASI BISNIS Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Science and Technology E-Dimas: Jurnal Pengabdian kepada Masyarakat Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BAREKENG: Jurnal Ilmu Matematika dan Terapan J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Jurnal Riset Teknologi Pencegahan Pencemaran Industri STATISTIKA

Hasbi Yasin

Department Of Statistics, Faculty Of Sciences And Mathematics, Diponegoro University

Author-ID : 422426

Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

Published : 89 Documents Claim Missing Document

Claim Missing Document

Articles

5 6 7 8 9

PREDIKSI CURAH HUJAN EKSTREM DI KOTA SEMARANG MENGGUNAKAN SPATIAL EXTREME VALUE DENGAN PENDEKATAN MAX STABLE PROCESS (MSP) Hasbi Yasin; Budi Warsito; Arief Rachman Hakim
MEDIA STATISTIKA Vol 12, No 1 (2019): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

This research covers Spatial Extreme Value method application with Max-Stable Process (MSP) approach that will be used to analysis Extreme Rainfall in Semarang city. Extreme value sample are selected by Block Maxima methods, it will be estimated into Spatial Extreme Value form by including location factors. Then it transform to Frechet distribution because it has a heavy tail pattern. Max Stable Process (MSP) is an extension of the multivariate extreme value distribution into infinite dimension of the Extreme Value Theory. After the best model of extreme rainfall data in Semarang is obtained, then calculated the prediction of extreme rainfall with a certain time period. Predictions are calculated using a return level, predictions of extreme rainfall using the return period of the next two years, at the Semarang City Climatology Station predicted to be a maximum of 100.7539 mm. At the Tanjung Mas Rain Monitoring Station it is predicted that a maximum of 100.1052 mm, Ahmad Yani Rain Monitoring Station is predicted to be a maximum of 109.9379 mm. Maximum prediction of extreme rainfall can also be calculated for future t (time) periods.

ANALISIS SENTIMEN DATA ULASAN APLIKASI RUANGGURU PADA SITUS GOOGLE PLAY MENGGUNAKAN ALGORITMA NAÏVE BAYES CLASSIFIER DENGAN NORMALISASI KATA LEVENSHTEIN DISTANCE Hindun Habibatul Mubaroroh; Hasbi Yasin; Agus Rusgiyono
Jurnal Gaussian Vol 11, No 2 (2022): 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.v11i2.35472

One form of technological development in education is the increasing number of online based learning. More than that, during this period of Covid-19 pandemic distance education was tried by the government that requires learning are done online. The online learning application that is the implementation of this technological development continues to show its existence. Many non-formal educational companies are available, one of which is the Ruangguru, getting a nickname as a number one learning application requires the Ruangguru to continue and improve the performance. Users of the Ruangguru application can communicate a response to Ruangguru through the review feature available on the google play site. The reviews that have been written can be analyzed how the user sentiment is whether positive or negative using Multinomial Naïve Bayes. This method is used because it is easy to use with simple structures and gives high accuracy values. The model will be selected using 10-fold cross validation method to get the model with the best accuracy. The normalization phase of words was also perfected using Levenshtein Distance method that was proven to add accuracy value. Performance result using Multinomial Naïve Bayes by adding Levenshtein Distance method to fix the words gives an average accuracy value of 88,20% with the 8th fold as the fold with the best accuracy value of 94%.

PEMODELAN JUMLAH WISATAWAN DI JAWA TENGAH MENGGUNAKAN METODE GENERALIZED SPACE TIME AUTOREGRESSIVE - SEEMINGLY UNRELATED REGRESSION (GSTAR-SUR) Innosensia Adella; Dwi Ispriyanti; Hasbi Yasin
Jurnal Gaussian Vol 11, No 2 (2022): 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.v11i2.35473

Space-time model is a model that can explain data with spatial and time characteristics. The Generalized Space Time Autoregressive (GSTAR) model is one of the generalized space-time models from the Space Time Autoregressive (STAR) model. The GSTAR model is more flexible when dealing with areas that have heterogeneous characteristics than the STAR model. The GSTAR model models time series data in multiple regions at once. This model can then be used to model data on the number of tourists in four regions in Central Java, namely Semarang, Jepara, Magelang and Semarang district for the 2014 to 2019 period. in Central Java. On the residual model, the Lagrange Multiplier Test is carried out and it is known that there is a correlation between the residuals. The modeling was continued by using the Generalized Space Time Autoregressive – Seemingly Unrelated Regression (GSTAR-SUR) model. GSTAR-SUR is one of the more efficient models used to model GSTAR with correlated residuals. Residual through the white-noise assumption test, it is found that the appropriate model is the GSTAR-SUR(2,1) model. This model can then be used in forecasting data on the number of tourists in Semarang, Jepara, Magelang and Semarang district in the next period

Hybrid Vector Autoregression Feedforward Neural Network with Genetic Algorithm Model for Forecasting Space-Time Pollution Data Rezzy Eko Caraka; Rung Ching Chen; Hasbi Yasin; Suhartono Suhartono; Youngjo Lee; Bens Pardamean
Indonesian Journal of Science and Technology Vol 6, No 1 (2021): IJOST: VOLUME 6, ISSUE 1, April 2021
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/ijost.v6i1.32732

The exposure rate to air pollution in most urban cities is really a major concern because it results to a life-threatening consequence for human health and wellbeing. Furthermore, the accurate estimation and continuous forecasting of pollution levels is a very complicated task. In this paper, one of the space-temporal models, a vector autoregressive (VAR) with neural network (NN) and genetic algorithm (GA) was proposed and enhanced. The VAR could tackle the issue of multivariate time series, NN for nonlinearity, and GA for parameter estimation determination. Therefore, the model could be used to make predictions, such as the information of series and location data. The applied methods were on the pollution data, including NOX, PM2.5, PM10, and SO2 in Taipei, Hsinchu, Taichung, and Kaohsiung. The metaheuristics genetic algorithm was used to enhance the proposed methods during the experiments. In conclusion, the VAR-NN-GA gives a good accuracy when metric evaluation is used. Furthermore, the methods can be used to determine the phenomena of 10 years air pollution in Taiwan.

Classification of Public Opinion on Social Media Twitter concerning the Education in Indonesia Using the K-Nearest Neighbors (K-NN) Algorithm and K-Fold Cross Validation Intan Monica Hanmastiana; Budi Warsito; Rita Rahmawati; Hasbi Yasin; Puspita Kartikasari
Statistika Vol. 21 No. 2 (2021): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v21i2.297

Developing country is a country that has perspective and idea which reflect its awareness of the importance of advancing the education sector. Assessment of the quality of education in Indonesia from the perspective of the community gets different responses. Therefore, it makes people respond differently. The community response is often found on social media, one of which is Twitter. Twitter is one of the application service that is popular due to its uses to interact and communicate with people in daily life. The sentiment analysis on Twitter can be a choice to see the community’s responses to the condition of education in Indonesia. The responses are classified into positive sentiments and negative sentiments using the K-Nearest Neighbors (K-NN) algorithm with a 10-fold cross validation model evaluation. K-NN has several advantages, they are fast training, simple, easy to learn, resistance toward training data which has noise, and effective if the training data is large. In this study, the sentiment classification uses Cosine Similarity distance measurement and four k value parameters which are 3, 5, 7, and 9. Data labelling is done manually and done by scoring sentiment. Visualization of positive and negative sentiments use Word Cloud. The test results show that public sentiment about education tends to be positive on Twitter and the parameter k = 7 obtained the highest accuracy value in data labelling that was done manually and done by scoring sentiment. In labelling data manually, it obtained an accuracy of 76.93% whereas, in labelling the data with scoring sentiment, it obtained an accuracy of 77.87%. Sentiment analysis is made using the RStudio programming language as the support software.

PEMODELAN PERTUMBUHAN EKONOMI DI PROVINSI BANTEN MENGGUNAKAN MIXED GEOGRAPHICALLY WEIGHTED REGRESSION Hasbi Yasin; Budi Warsito; Arief Rachman Hakim
MEDIA STATISTIKA Vol 11, No 1 (2018): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Economic growth can be measured by amount of Gross Regional Domestic Product (GRDP). Based on official news of statistics BPS, Economic growth in Banten region has increase up to 5.59%. It supported by several sector, there are agriculture, business, industry and from various fields. Mixed Geographically Weighted Regression (MGWR) methods have been developed based on linear regression by giving spatial effect or location (longitude and latitude), the resulting model from Economic growth in Banten will be local or different based on each location. MGWR mixed method between linear regression and GWR, parameters in linear regression are global and GWR parameters are local. The results more specific because economic growth in Banten region assessed by location.Keywords: Banten, Economic growth, MGWR.

Examining Social Support and Trust Transfer Theory in Online Health Community Adoption Saputra, Ragil; Dharmawan, Bagus Dwiky; Adhy, Satriyo; Mutiara, Dinar; Yasin, Hasbi
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp277-284

Online Health Communities (OHCs) have become a key source of social support for individuals with health concerns. OHC members engage in communication and information exchange, with trust among members playing a crucial role in the acceptance of these platforms. This research aims to examine the determinants affecting OHC acceptance by employing trust transfer theory, social support, and self-efficacy as core variables. The proposed model was empirically tested using data from 100 members of the Indonesian Diabetes Forum on Facebook. This quantitative study employed a 5-point Likert scale to evaluate user perceptions. The findings indicate that OHC acceptance is significantly supported by both information support and emotional support, which foster trust among community members. Trust in members subsequently leads to trust in the broader community, culminating in the sustained use of the OHC. Furthermore, emotional support positively influences self-efficacy, encouraging users to join and actively participate in OHCs. However, information support does not have a significant effect on self-efficacy. This research offers significant understanding of the relationships among social support, self-efficacy, and trust in promoting the continued use of OHCs. The research model offers a framework that can be applied in other contexts with similar technological and community-based perspectives.

3-PARAMETER GAMMA REGRESSION MODEL FOR ANALYZING HUMAN DEVELOPMENT INDEX OF CENTRAL JAVA PROVINCE Yasin, Hasbi; Inayati, Syarifah; Setiawan, Setiawan
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 1 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

The number and quality of the population are one of the determining factors for the success of national development. The quality of the population of a region can be seen from Human Development Index (HDI) achieved by a region. The HDI is based on three basic dimensions: a long and healthy life, knowledge, and a decent standard of living. This study aimed to determine the factors influencing HDI in Central Java Province in 2018-2020. The data used tend to follow the 3-Parameter Gamma distribution, which implies the HDI is modeled with 3-Parameter Gamma regression. 3-Parameter Gamma Regression is a regression that explains the relationship among one or more predictor variables with response variables that follow the 3-Parameter Gamma distribution. This research also includes the preparation of algorithms and computations in modeling 3-parameter Gamma regression. The estimation of model parameters was carried out using Maximum Likelihood Estimation (MLE) and Berndt Hall Hausman (BHHH) methods. HDI modeling with 3-Parameter Gamma regression produces a coefficient of determination of 61.58%. The results show that increasing HDI can be done by increasing the Pure Participation Rate (APM) for SMP/MTs, the ratio of SMP/MTs students, population density, Labor Force Participation Rate (TPAK), the percentage of households (RT) with access to water, drinking water, and the percentage of households (RT) that have their toilet facilities, as well as by reducing the student-teacher ratio of Junior High School(SMP)/Islamic Junior High School (MTs) and the Open Unemployment Rate (TPT).

Efektivitas Permainan Kartu sebagai Media Pembelajaran Matematika Wulandari, Isna; Hendrian, Jody; Sari, Indri Puspita; Arumningtyas, Felinda; Siahaan, Rina Br; Yasin, Hasbi
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 11, No 2 (2020): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v11i2.2513

Belajar matematika menjadi momok tersendiri bagi siswa. Untuk itu diperlukan suatu metode supaya pembelajaran matematika menjadi sesuatu yang menyenangkan bagi siswa sehingga kedepannya kesan sulit pada pelajaran matematika dapat dihapus. Salah satu cara yang dapat dilakukan adalah dengan mengajak mereka belajar matematika sambil bermain. KARTIKA (Kartu Matematika) dirancang sebagai salah satu media pembelajaran matematika yang dikemas melalui permainan edukatif. Sasaran dari KARTIKA adalah siswa sekolah dasar kelas 4 dan 5. Permainan ini diterapkan pada siswa SD Islam Pangeran Diponegoro. KARTIKA adalah mainan kartu layaknya kartu bridge (kartu remi), perbedaan KARTIKA dengan kartu bridge adalah cara penomoran kartunya. Dalam KARTIKA setiap kartu berisikan operasi hitung yang disesuaikan dengan materi pembelajaran siswa sekolah dasar. Dimana jawaban dari operasi hitung itu adalah angka 1 sampai dengan 13. Sehingga untuk bisa bermain, siswa dituntut untuk bisa menyelesaikan operasi hitung yang ada di dalam kartu. Metode ini cukup efektif untuk mengajak anak belajar matematika. Karena pada pembelajaran matematika dengan media KARTIKA, anak menganggap dirinya sedang bermain, namun pikiran mereka tetap dijalankan untuk memecahkan operasi hitung yang ada pada kartu.

Co-Authors Abdul Hoyyi Achmad Choiruddin Adi Waridi Basyiruddin Adi Waridi Basyirudin Arifin Agus Rusgiyono Ajeng Arum Sari Alan Prahutama Alvita Rachma Devi Amanda Lucky Berlian Andreanto Andreanto Anggun Perdana Aji Pangesti Arief Rachman Hakim Arief Rachman Hakim Arumningtyas, Felinda Baluk, Andreas Pedo Bens Pardamean Budi Warsito Budi Warsito Danang Chandra Pradana, Danang Chandra Dani Al Mahkya Darwanto Darwanto Devi Wijayanti Dewi Setya Kusumawardani Dharmawan, Bagus Dwiky Dhea Kurnia Mubyarjati Di Asih I Maruddani Di Asih I Maruddani Di Asih I Maruddani Diah Safitri Dwi Hasti Ratnasari Dwi Ispriyanti Eko Siswanto Fadhilla Atansa Tamardina Fiqria Devi Ariyani Gera Rozalia Hanien Nia H Shega Hari Susanta Nugraha Hendrian, Jody Hidayatul Musyarofah Hindun Habibatul Mubaroroh Ika Chandra Nurhayati Inas Hasimah Inayati, Syarifah Indah Suryani Innosensia Adella Intan Monica Hanmastiana Isna Wulandari Ispriyansti, Dwi Johanes Roisa Prabowo Kadi Mey Ismail Kurniawan, Isma Dwi Lutfia Septiningrum Maghfiroh Hadadiah Mukrom Maria Odelia Mas'ad, Mas'ad Maulana Taufan Permana Mega Fitria Andriyani Meilia Kusumawardani, Meilia Moch. Abdul Mukid Mochammad Iffan Zulfiandri MUHAMMAD HARIS Muhammad Mujahid Muhammad Tahmid Muryanto Muryanto Muryanto, Muryanto Mustafid Mustafid Mutiara, Dinar Nova Delvia Nur Azizah Nur Indah Yuli Astuti, Nur Indah Yuli Pandu Anggara Purhadi Purhadi Puspita Kartikasari Ragil Saputra Rahmasari Nur Azizah Reza Dwi Fitriani Rezzy Eko Caraka Riama Oktaviani Samosir, Riama Oktaviani Rifki Adi Pamungkas, Rifki Adi Rita Rahmawati Rita Rahmawati Riza Fahlevi Rizki Brendita Br Tarigan Rose Debora Julianisa, Rose Debora Rukun Santoso Rung Ching Chen Saepudin, Yunus Sakhinah Abu Bakar Salma Farah Aliyah Sari, Ajeng Arum Sari, Indri Puspita Satriyo Adhy Setiawan Setiawan Setyoko Prismanu Ramadhan Siahaan, Rina Br Siska Alvitiani Siti Maulina Meutuah Sri Endah Moelya Artha Sudarno Sudarno Sudarno Sudarno Sugito Sugito - Sugito Sugito Suhartono Suhartono Suparti Suparti Tarno Tarno Tarno Tarno Tatik Widiharih Tiani Wahyu Utami Tsania Faizia Ubudia Hiliaily Chairunnnisa Via Risqiyanti Wahyu Sabtika Wawan Sugiarto, Wawan Wulandari, Heni Dwi Wulandari, Isna Youngjo Lee Yuciana Wilandari Yudha Subakti, Yudha Zulfa Wahyu Mardika, Zulfa Wahyu

Title

Found 89 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 89 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 89 Documents
Search