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All Journal Natural Science: Journal of Science and Technology JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) JOIN (Jurnal Online Informatika) JURNAL ILMIAH MATEMATIKA DAN TERAPAN BAREKENG: Jurnal Ilmu Matematika dan Terapan Kompartemen : Jurnal Ilmiah Akuntansi Jurnal Aplikasi Statistika & Komputasi Statistik Jurnal Varian Majalah Ilmiah Matematika dan Statistika (MIMS) JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Parameter: Journal of Statistics Jurnal Pengabdian Farmasi dan Sains

Fadjryani, Fadjryani

Department Statistics, Faculty Of Mathematics And Natural Sciences, Tadulako University, Indonesia

Author-ID : 718081

Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Environmental Science Immunology & microbiology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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The Motivation of Criminality During the Covid-19 Pandemic in Central Sulawesi Fadjryani; Saputra, Wawan
Parameter: Journal of Statistics Vol. 2 No. 2 (2022)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2022.v2.i2.15680

With the news of the crime were often pushed in a variety of digital platforms and non- digital and criminal acts that are still happening in the community, make this topic endlessly to be discussed. Moreover, during the current pandemic, so many demands for life are not in line with the situation as a result of the implementation of the lockdown policy and the implementation of restrictions on community activities (IRCA) from the government which requires some people to be willing to lose their livelihood. Meanwhile, out of 100,000 people in Indonesia, 140 of them are at risk of being exposed to crime. The high crime rate is influenced by several factors such as education, less strict laws, high unemployment and inadequate wages. The purpose of this study was to determine the characteristics of crime and determine the factors that influence the occurrence of criminal acts in Central Sulawesi during the Covid-19 pandemic. This type of research is a type of descriptive qualitative research and descriptive quantitative. The data used in this study is secondary data from the Central Statistics Agency and the Central Sulawesi Regional Police. The research method used is multiple linear regression. The results of this study show that the characteristics of crime in Central Sulawesi during the pandemic, namely ordinary theft cases became the highest indicator in criminal cases, while theft in the family became the lowest indicator in criminal cases. In addition, it is known that the dominant criminal acts are carried out by men with self-employed and unemployed jobs, with the last education being high school or equivalent. Partially, the variable Number of Poor People has a significant effect on crime that occurs in Central Sulawesi and simultaneously or together the four variables, namely education, unemployment, Gross Regional Domestic Product (GRDP) and Number of Poor Population have an effect on the occurrence of crime in Central Sulawesi. The result of the coefficient of determination in this study was 79.99% it means that the four independent variables are able to explain the dependent variable of 79.99% and the remaining 20.01% are other variables that have not been used as variables in this study.

ANALYZING THE QUALITY OF MEASUREMENT INSTRUMENTS OF MULTIPLE CHOICE QUESTIONS ON CLASS XI ECONOMICS MATERIAL IN PUBLIC HIGH SCHOOL 3 GORONTALO THROUGH CLASSICAL TEST THEORY AND RASCH MODELS Yulisharyasti, Luthfiah; Nurdin, Ansor; Aulia, Nanda; Arfa, Fhahnul Aiman H; Fadjryani
Parameter: Journal of Statistics Vol. 3 No. 1 (2023)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2023.v3.i1.16417

One form of evaluation of student learning outcomes is the Final Semester Examination. This exam is designed to measure the extent of achievement of educational objectives. A good evaluation must meet several criteria, including good item validity and reliability, a variety of difficulty levels, and the power of differentiation. This study aims to describe the results of a comparative analysis of the quality of measurement instruments in the form of multiple-choice questions using the classical test theory approach and the Rasch model in terms of validity, reliability, difficulty level, and question differentiation. Data were obtained through a website that presents multiple choice exam results of grade XI students at SMA Negeri 3 Gorontalo, consisting of 26 female students and 10 male students. The results showed that in the instrument validity analysis, the Rasch model showed more valid items with a determination category of 0.4 < pt measure corr < 0.8. This means that the Rasch model provides a better analysis compared to the classical test theory analysis. In the reliability analysis, the reliability value of items in the Rasch model is higher but in almost the same category. In analyzing the difficulty level of the instrument, the classical test theory approach shows that the items are in the easy, medium, and difficult categories, so they are still considered capable of measuring students' abilities. However, in the Rasch model, items are only in the very easy, difficult, and extremely difficult categories. In analyzing the power of differentiation, the classical test theory method and the Rasch model have not provided good enough results to identify respondents in several groups based on their level of understanding

PENGARUH INTERAKSI GENOTIP DAN LINGKUNGAN TERHADAP PENINGKATAN PRODUKTIVITAS TANAMAN BAWANG MERAH MENGGUNAKAN METODE SEM-AMMI Raihanah, Ghina Rizqa; Junaidi, Junaidi; Fadjryani, Fadjryani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 15 No 1 (2021): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Stable and adaptive superior varieties play an important role in increasing plant productivity. The technological innovation was carried out by studying the yield GEI. However, if only paying attention to yield GEI would not be enough in selecting stable and adaptive varieties, so this research used a combination of AMMI and SEM methods. Through the SEM-AMMI, GEI modeling was carried out by taking into account the physiological processes of growth and genotype development which explained the relationship between yield GEI components and how it affected yield GEI. The results of the AMMI biplot showed that genotypes were adaptable and relatively stable were planted in five planting locations, namely Biru Lancor and Tinombo. SEM test results showed that the yield component has an effect on production yield, where the tuber weight above the average will give relatively more onion yields and genotypes planted in relatively low locations, soil pH above 6 and dusty clay soil conditions will produce relatively more red onions and quality.

ANALYSIS OF SPATIAL EFFECTS ON FACTORS AFFECTING RICE PRODUCTION IN CENTRAL SULAWESI USING GEOGRAPHICALLY WEIGHTED PANEL REGRESSION Gamayanti, Nurul Fiskia; Junaidi, Junaidi; Fadjryani, Fadjryani; Nur'eni, Nur'eni
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Fulfillment of rice stock in Indonesia to always be distributed based on demand in the community is certainly closely related to the results of rice production. The results of rice production in various regions of Indonesia are very different. This difference can of course be influenced by geographic location or spatial effects between regions. Central Sulawesi, which is one of the provinces with a large population compared to other provinces on the island of sulwesi, has a responsibility to meet the needs of its community, so it is necessary to take into account and increase the production of rice by relying on production in the province.Modeling of rice production that has spatial effects or heterogeneity between regions is needed as an analytical tool because if the modeling ignores spatial effects and generalizes the model, the modeling predictions will be biased. So we need an analytical model that can accommodate the problem of spatial effects using Geographically Weighted Panel Regression. The purpose of this study was to determine the factors that can affect rice production in central sulawesi. The data used comes from BPS Central Sulawesi province from 2014-2020. This study focus to the spatial effect factors that are considered to be able to affect the rice production production in Central Sulawesi. Tthe results of the study there area 8 districts/cities which are affected by land area, and 4 districts/cities are affected by land area and harvested are.

EXPERT SYSTEM DESIGN TO DIAGNOSE PESTS AND DISEASES ON LOCAL RED ONION PALU USING BAYESIAN METHOD Junaidi, Junaidi; Fadjryani, Fadjryani; Setiawan, Iman; Batara, Mohammad; Hendra, Syaiful; Ismail, Nurmasita
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 1 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Bayesian is a method that can be used to overcome the uncertainty of a situation or data. The information obtained must be continuously updated so that it can foster trust as a result of the uncertainty of those conditions. In this study, the application of the Bayesian method to detect early symptoms of diseases on local red onion Palu plants based on the symptoms that appear will be carried out. Information about pests and diseases that attack local red onion Palu is needed to help farmers. As a result, they can deal with attacked diseases quickly and precisely. This is crucial conducted by considering that this plant is one of the mainstay commodities for farmers in Central Sulawesi Province whose production must continue to be increased. Pests and diseases can be diagnosed through visible symptoms.The sample is local red onion Palu that affected by pests and disesases which planted in the AIAT of Central Sulawesi by experiment. As a result, through these symptoms an expert system can then be created to do a diagnosis. An expert system is a system that seeks to adopt human knowledge to a computer that is built to solve problems like an expert. The created expert system to diagnose diseases uses the Bayesian method to calculate the probability of an event occurring based on the obtained results from observations and experts. An expert system for diagnosis of pests and diseases is built on a web-based basis. This expert system has features and functions including the diagnosis of pests and diseases of the observed plants, viewing the results of the diagnosis and printing the results of the diagnosis. In addition, users can view information on pests and other diseases that attack plants. From the results of system testing that conducted by experts, this shows that the expert system is feasible to use to diagnose local red onion Palu plants which affected by pests and diseases with an accuracy point that has the largest percentage value.

Exploring Diabetes Mellitus Risk Patterns with Multiple Correspondence Analysis at Torabelo Hospital, Central Sulawesi Asfar; Fadjryani; Ambarwati B. Sarabi , Valina; Jannah , Miftahul; Sartika, Dewi; Setiawan, Aldi; Nurfadilah, Khalilah
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.59040

This study aims to explore the pattern of diabetes mellitus risk factors among patients at Torabelo Regional Hospital in Sigi using Multiple Correspondence Analysis (MCA). A total of 465 patients were analyzed based on eight categorical variables, including age, gender, blood glucose levels, and lipid profiles. MCA was applied to identify inter-category relationships and visualize them in a low-dimensional space. The results show that most diabetes patients were female, aged 46 years and above, and had high fasting glucose, low HDL, and high LDL levels. The analysis identified two main patterns: a group with a low-risk metabolic profile who were not diagnosed with diabetes, and a group with a combination of high-risk metabolic categories who were more likely to already have diabetes. A distinct subgroup with extremely high triglyceride levels was also identified, indicating a rare but significant metabolic pattern. The first two dimensions of the MCA explained more than 40% of the data variation, providing sufficient support for meaningful visual interpretation. These findings demonstrate that MCA is effective in simplifying complex categorical data and supports risk-based segmentation strategies for early intervention planning in primary healthcare services, particularly in regions with high diabetes prevalence.

Automatic Plant Watering System for Local Red Onion Palu using Arduino Setiawan, Iman; Junaidi, Junaidi; Fadjryani, Fadjryani; Amaliah, Fika Reski
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.813

Central Sulawesi Province in Indonesia has great potential for horticultural commodities, namely local red onion Palu. In the current climate change, local farmers are still watering plants in the conventional way. The automatic watering system simplifies the work of local farmers. This device uses a soil moisture sensor as a soil moisture detector and Arduino as a program brain. This study aims to determine the position of soil moisture sensor, the optimal length of watering time and analyze the quality of data stored. The experiment was carried out using a Completely Randomized Design (CRD). The position of the soil moisture sensor was analyzed by Profile Analysis. The optimal length of watering time was determined by Analysis of Variance (ANOVA) and Least Significant Difference (LSD). The quality of data stored was determined by a number of missing values and frequency of watering. The results showed that in soil planting media the position of soil moisture sensor had no significant effect, while in others planting media (water and combination of water and soil) the position of the sensor had a significant effect. The optimal watering time was 3 seconds. The stored data has low quality in terms of missing values and lack of consistency.

Internet of Things (IoT) for Soil Moisture Detection Using Time Series Model Setiawan, Iman; Junaidi, Junaidi; Fadjryani, Fadjryani; Amaliah, Fika Reski
JOIN (Jurnal Online Informatika) Vol 7 No 2 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i2.951

Technology in agriculture has been widely and massively applied. One of them is automation technology and the use of big data through the Internet of Things (IoT). The use of IoT allows a process to run automatically without human intervention. Extreme weather changes and narrow land use are one of the main problems in agriculture. The development of IoT devices has been widely developed regarding this subject. One of them is a soil moisture detection system. This study aims to build an IoT soil moisture detection system. The system will use a sensor as input which is then processed in a microcontroller device and the prediction results are sent to the IoT cloud platform. Prediction results are obtained using a time series model and then its performance is evaluated using RMSE. This model was chosen because the structure of the observed soil moisture data is based on time. The results of this study indicate that the soil moisture IoT system can work well. This is supported by the results of the prediction evaluation value of the RMSE = 1.175682x10-5 model which is very small.

PENERAPAN PETA KENDALI T^2 HOTELLING ALGORITMA FAST MINIMUM COVARIANCE DETERMINANT PADA PENGENDALIAN KUALITAS BAWANG MERAH VARIETAS LEMBAH PALU Marulu, Puja Lestari; Junaidi, Junaidi; Fadjryani, Fadjryani
Jambura Journal of Probability and Statistics Vol 3, No 2 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i2.15522

The physical condition of the Palu Valley shallots variety greatly affects the quality of the fried onions that are obtained. The poor quality of shallots will affect the product that will sale by the farmers. Therefore, it is necessary to monitor by conducting the quality control analysis of the physical condition of shallots. In this study we use the quality control method of the Hotelling control map with the fast-MCD algorithm. This method is used because the outlier in the data to be analyzed. The purpose of this study is to produce average vector estimates and variance-covariance matrix estimates in the formation of the Hotelling control map. From the calculation by using the mean vector and the variant-covariant matrix with fast-MCD estimation, 93 data were obtained that experienced out of control on the Hotelling control map with the fast-MCD algorithm where the observations that experienced out of control were more than the usual of Hotelling control map. This shows that the Hotelling control map with the fast-MCD algorithm is more effective in detecting observations which contain outliers. The value of the multivariate process capability analysis is less than one showing the process is uncapable.

Pemodelan Jumlah Siswa Putus Sekolah Tingkat SMA di Indonesia Menggunakan Geographically Weighted Generalized Poisson Regression Azizah, Nur; Gamayanti, Nurul Fiskia; Junaidi, Junaidi; Sain, Hartayuni; Fadjriyani, Fadjryani
Jurnal Varian Vol. 8 No. 1 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/varian.v8i1.4248

In 2022, the high school dropout rate is the highest compared to other levels of education in Indonesia.Seeing the urgency of the 12-year Compulsory Education program, completing education up to the highschool level is an important thing that needs to be considered. Thus, it is necessary to know the factorsthat influence the dropout rate in the hope that this problem can be reduced. This study aims to modelthe high school dropout rate using geographically weighted generalized poisson regression (GWGPR)based on the factors that influence it. GWGPR is used if the response variable is overdispersed anddepends on the location observed. The results of this study indicate that each province has a different regression model. The GWGPR model with the adaptive tricube kernel weighting function is thebest model because it has the smallest AIC value compared to other weighting functions. In CentralSulawesi Province, the GWGPR model with the adaptive tricube kernel weighting function formed isÂµË†26 = exp (8, 1267 âˆ’ 0, 1267X4 + 0, 0344X5 + 0, 0957X6 + 0, 1173X7). With the significant variables are the average length of schooling, the percentage of the population aged 7-17 years who receivePIP, the open unemployment rate, and the percentage of children who do not live with parents.

Co-Authors Aan Bin Mardi Abdul Mahatir Najar Afriza, D A Afriza, Dini Aprilia Agus Indra Jaya Ainanur Aisya, Cici Aldi Setiawan, Aldi Amaliah, Fika Reski Ambarwati B. Sarabi , Valina Annisa, N Arfa, Fhahnul Aiman H Asfar Asrima Aulia, Nanda Batara, Mohammad Chalfin Lieputera Kaliongga Damayanti, Virga Dewi Puji Astuti, Dewi Puji DEWI SARTIKA Diah Daniaty Difa Shalsabila Eka Rizky Wulansari Eliani Eliani Fika Reski Amaliah Fitri, Yuhelni Gamayanti, Nurul Fiskia Harmila, D Hartayuni Sain Iman Setiawan Ismail, Nurmasita Iut Tri Utami Jannah , Miftahul Junaidi Junaidi Junaidi Junaidi Juni Wijayanti Puspita Marulu, Puja Lestari Maulidyani Abu Mohammad Fajri Mu'arif, Z Mujahida, A S Mukarrama, F.A. Musyarofah, U Nur Azizah Nur'Eni Nur?Eni, Nur?Eni Nurdin, Ansor Nureni, Nureni Nurfadilah, Khalilah Nursanti, M Radi, Aryani Raihanah, Ghina Rizqa Rais Rais Resnawati Salsabila, P Setiawan, Iman Siti Helmyati Suaib, Tri Putri Andayani Syaiful Hendra Wawan Saputra Yulisharyasti, Luthfiah

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