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All Journal Jurnal Matematika BIMASTER Proceedings of Annual International Conference Syiah Kuala University - Life Sciences & Engineering Chapter Jurnal Statistika Universitas Muhammadiyah Semarang Agrointek BAREKENG: Jurnal Ilmu Matematika dan Terapan Jambura Journal of Mathematics GERVASI: Jurnal Pengabdian kepada Masyarakat Sarwahita : Jurnal Pengabdian Kepada Masyarakat M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Variance : Journal of Statistics and Its Applications Abdimas Galuh : Jurnal Pengabdian Kepada Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian kepada Masyarakat Nusantara Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Jurnal Forum Analisis Statistik Pattimura International Journal of Mathematics (PIJMath) Jurnal Pelayanan dan Pemberdayaan Masyarakat STATISTIKA Equiva
Hendra Perdana
Universitas Tanjungpura
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Metode Holt-Winter Exponential Smoothing untuk Memprediksi Nilai Tukar Petani di Provinsi Kalimantan Barat: Holt-Winter Exponential Smoothing Method to Predict Farmer Exchange Rates in West Kalimantan Province Fidianty, Fadilla; Perdana, Hendra; Rofatunnisa, Sifa
Jurnal Forum Analisis Statistik Vol. 5 No. 1 (2025): Jurnal Forum Analisis Statistik (FORMASI)
Publisher : Badan Pusat Statistik Provinsi Kalimantan Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57059/formasi.v5i1.95

Abstract

Kegiatan bertani yang dilakukan manusia adalah untuk memenuhi kebutuhan pangan. Tidak hanya berkontribusi untuk memenuhi kebutuhan pangan, tetapi juga menjadi pendorong untuk membangun suatu pedesaan. Sektor pertanian adalah sektor perekonomian yang memiliki peran besar terhadap pembangunan negara berkembang. Salah satu indikator yang berperan dalam evaluasi pembangunan pertanian adalah Nilai Tukar Petani (NTP). Besarnya kontribusi sektor pertanian sehingga diperlukan penentuan kebijakan yang tepat, salah satunya menggunakan metode peramalan. Metode peramalan yang digunakan pada penelitian ini adalah Holt-Winter Exponential Smoothing. Tujuan dilakukannya penelitian ini adalah untuk meramalkan NTP pada Januari 2024 sampai dengan desember 2024, dan melihat apakah metode ini tepat dalam meramalkan NTP. Ketepatan peramalan dilihat dari nilai Mean Absolute Percentage Error (MAPE) terkecil yang sesuai dengan klasifikasi nilai MAPE. Hasil analisis yang didapatkan dengan parameter optimal yang digunakan adalah alfa = 0,953014, beta = 0,08162, dan gamma = 0,99 , parameter tersebut didapatkan setelah dilakukan solver data. Nilai MAPE yang didapatkan dengan parameter tersebut sebesar 1,12%. Metode ini bisa menjadi rujukan untuk meramalkan NTP ke depannya. Untuk penelitian selanjutnya, disarankan menggunakan metode peramalan yang lain, agar dapat diketahui metode mana yang mendapatkan hasil terbaik.
MULTI-STATE MODEL FOR CALCULATION OF LONG-TERM CARE INSURANCE PRODUCT PREMIUM IN INDONESIA Perdana, Hendra; Satyahadewi, Neva; Kusnandar, Dadan; Tamtama, Ray
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (487.771 KB) | DOI: 10.30598/barekengvol16iss4pp1293-1302

Abstract

Long Term Care (LTC) insurance is a type of health insurance. One of the LTC products is Annuity as A Rider Benefit. This insurance provides benefits for medical care costs during the term and death benefits if the insured dies. This insurance product can be modeled with a multi-state model. The multi-state model is a stochastic process in which the subject can switch states at a specified number of states. This paper discusses the calculation of LTC insurance premiums with the Annuity as A Rider Benefit product using a multi-state model for critically ill patients in Indonesia. The state used consisted of eight states, namely healthy, cancer, heart disease, stroke, died from the illness from each disease, and died from others. The premium calculation also utilized Markov chain transition probabilities. The data used were data on Indonesia's population in 2018, data on the prevalence of cancer, heart disease, stroke, and Indonesia's 2019 mortality table. The stages of this study were calculating the net single premium value, benefit annuity value, and insurance premium value. The case study was conducted on a 25 years old male in good health following LTC insurance with a coverage period of 5 years. It was known that the compensation value for someone who dies was IDR 100,000,000 and the interest rate used was 5%. The calculation results obtained an annual premium of IDR 5,308,915 which was then varied based on gender and varied interest. Insurance premiums for men were more expensive than for women since men had a greater chance of dying. Then, the higher the interest rate taken; the lower premium paid. This was because the interest rate is a discount variable.
PREMIUMS CALCULATION OF TERMINAL ILLNESS INSURANCE Satyahadewi, Neva; Retnani, Hani Dwi; Perdana, Hendra; Tamtama, Ray; Aprizkiyandari, Siti
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0913-0918

Abstract

One related type of critical illness insurance is Long Term Care (LTC) Insurance. This study discusses the calculation of LTC insurance premiums with an annuity as a rider benefit. The benefit is included the cost of insurance care when diagnosed with a critical illness with a terminal condition or death because of any reason. The types of critical illnesses used in this study are cancer, heart disease, stroke, and diabetes mellitus. The data used are in the form of Indonesia's mortality table, and data on the prevalence of critical illness patients with terminal illness conditions. The net annual premium value in this study was obtained through the results of the multiple-state model determination of the transition probabilities of 10 states. The transition probability of an insured candidate is obtained from the prevalence of critical illness patients and the prevalence of mortality. Based on the case study, the amount of net annual premium that must be paid by an insured female aged years in good health is for the protection period and the payment period is years. The cost of insurance premiums for the male insured is greater than for the female insured. The higher the interest rate used, the smaller the net single premium that must be paid. The younger the age when registering the policy, the smaller the premium that must be paid. The longer the coverage period, the greater the premium that must be paid. This result is expected to be a recommendation for the prospective insured to adjust the suitable premium.
NET SINGLE PREMIUM ON CRITICAL ILLNESS INSURANCE WITH MULTI-STATE MODEL Taraly, Inggriani Millennia; Satyahadewi, Neva; Perdana, Hendra; Tamtama, Ray; Aprizkiyandari, Siti
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0989-0994

Abstract

The chances of someone getting a disease or suffering from a critical illness are very large, especially when they get older, the chances of getting a critical illness will be higher. A guarantee of the future is indispensable if a person suffers from a critical illness at any time and requires considerable costs to undergo treatment. Insurance is one of the right choices and is beneficial for people with critical illnesses. In this study, the calculation of Critical Illness insurance premiums was carried out to determine the value of premiums that must be paid by a person when suffering from a critical illness. The types of critical illnesses used include cancer, heart disease, stroke, kidney failure, diabetes mellitus, and hypertension. Health insurance that protects insureds suffering from critical illnesses is Long Term Care insurance with the Annuity as A Rider Benefit product. The multi-state model is used to determine the probability of a person suffering from a critical illness. The benefits obtained are in the form of death compensation, and treatment costs when the insured is diagnosed with a critical illness. The data used are data on the prevalence of critical illnesses and the percentage of deaths due to critical illnesses. In this study, we will compare the amount of premium that must be paid by the insured with different interest rates, gender, coverage period, and age. The higher the age at the beginning of following the insurance, the higher the premium. The higher the interest rate during the payer's period, the lower the premium.
HIERARCHICAL CLUSTER ANALYSIS OF DISTRICTS/CITIES IN NORTH SUMATRA PROVINCE BASED ON HUMAN DEVELOPMENT INDEX INDICATORS USING PSEUDO-F Satyahadewi, Neva; Sinaga, Steven Jansen; Perdana, Hendra
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1429-1438

Abstract

Human development is needed to create prosperity and assist development in a country. In realising this, it is necessary to first look at the quality of human resources in the country, so that its use is more targeted. The measure used as a standard for the success of human development in a country is the Human Development Index (HDI). HDI figure are calculated from the aggregation of three dimensions, namely longevity and healthy living, knowledge, and decent standard of living. The longevity and healthy living dimension is represented by the Life Expectancy. Average Years of Schooling (AYS) and Expected Years of Schooling (EYS) are indicators representing the knowledge dimension. Meanwhile, the decent standard of living dimension is represented by the Expenditure per Capita indicator. The purpose of this study is to explain the characteristics of each cluster obtained from Hierarchical Cluster Analysis of districts/cities in North Sumatra Province based on HDI indicators in 2022 using Pseudo-F. The methods used are Hierarchical Cluster Analysis and Calinski-Harabasz Pseudo-F Statistic. The main concept of this method is to determine the optimum number of groups. This research uses secondary data obtained from BPS. The sample size in this study are 33 districts/cities and the number of variables are 4 variables. The results of the analysis of this study are the formation of 4 clusters with the best method is Ward. Cluster 1 consists of four members, namely Medan City, Pematang Siantar City, Binjai City, and Padang Sidempuan City, where this cluster has a very high HDI level. Meanwhile, Cluster 4 is a cluster that has a very low HDI level with four cluster members, namely Nias District, South Nias District, North Nias District, and West Nias District. Thus, it can be seen that there is a gap between regions in North Sumatra Province.
APPLICATION OF BAGGING CART IN THE CLASSIFICATION OF ON-TIME GRADUATION OF STUDENTS IN THE STATISTICS STUDY PROGRAM OF TANJUNGPURA UNIVERSITY Imtiyaz, Widad; Satyahadewi, Neva; Perdana, Hendra
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp2243-2252

Abstract

The timeliness of graduation is used as the success of students in pursuing education which can be seen from the time taken and measured by the predicate of graduation obtained. The characteristics of students who tend to graduate not or on time can be analyzed using classification techniques. Classification and Regression Tree (CART) is one of the classification tree methods. There is a weakness in CART, which is less stable in predicting a single classification tree. The weaknesses in CART can be improved by using Ensemble methods, one of which is Bootstrap Aggregating (Bagging) which can reduce classification errors and increase accuracy in a single classification model. This study aims to classify and determine the accuracy of Bagging CART in the case of the accuracy of student graduation classification. The number of samples used is 140 data on the graduation status of Untan Statistics Study Program students from Period I of the 2017/2018 academic year to Period II of the 2022/2023 academic year. The variables used are the timeliness of graduation which is categorized into two namely Not and On Time, Gender, Semester 1 GPA, Semester 2 GPA, Semester 3 GPA, Semester 4 GPA, Region of Origin Domicile, High School Accreditation, Entry Path, Scholarship, and first TUTEP. A good classification can be seen from the accuracy value. The CART method obtained an accuracy value of 70%. While using the CART Bagging method obtained an accuracy value of 85.71%. Based on the accuracy value obtained, the application of the CART Bagging method can increase accuracy and correct classification errors on a single CART classification tree by 15.71% by resampling 25 times.
APPLICATION OF FUZZY ANALYTICAL NETWORK PROCESS IN DETERMINING THE CHOICE OF AREAS OF INTEREST Tiara, Dinda; Sulistianingsih, Evy; Perdana, Hendra; Satyahadewi, Neva; Tamtama, Ray
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp2253-2262

Abstract

The Untan Statistics Study Program offers students a choice of areas of interest to develop competencies, attitudes, and skills. This study aims to analyze the decision to determine the choice of field of interest according to lecturers and students using the Fuzzy Analytical Network Process (FANP) method. A combination of ANP methods and Fuzzy logic, FANP is used to model and analyze complex networks of several factors determining the choice of areas of interest. The step in this study begins with the determination of the criteria and sub-criteria used for tissue formation. Then a comparison was carried out in pairs using the Fuzzy scale, so that the calculation of the global weight value of each criterion and sub-criteria was obtained. The resulting weight can be used for decision making. Data in research affects the opinions of lecturers and students. The decision obtained using the FANP method in this study is in the opinion of lecturers and students that the fields of business and finance are priority alternatives with the highest weight of 44.5%. The second priority with a weight of 37.5%, namely social and industrial interests, and the environmental and disaster sector occupies the last priority with a weight of 18%.
VECTOR AUTOREGRESSIVE WITH OUTLIER DETECTION ON RAINFALL AND WIND SPEED DATA Lestari, Lisa; Sulistianingsih, Evy; Perdana, Hendra
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0117-0128

Abstract

Vector Autoregressive (VAR) is a multivariate time series model that analyzes more than one variable where each variable in the model is endogenous. VAR is one of the models used in forecasting rainfall and wind speed. In observations of rainfall and wind speed, there are usually a series of events whose values are far from other observations or can be said to be outliers. The purpose of this study is to compare the VAR model on rainfall and wind speed data before and after outlier detection. This study uses secondary data, namely monthly data on rainfall and wind speed from 2019 to 2021. From the analysis results, the smallest AIC value obtained in the VAR model before outlier detection was 4.94, then the smallest AIC value in the VAR model after outlier detection was 0.25. Thus, it can be concluded that the best model is obtained in the VAR model after outlier detection seen from the smallest AIC value of the two VAR models.
DETERMINING STUDENT GRADUATION BASED ON SCHOOL LOCATION USING GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION Perdana, Hendra; Satyahadewi, Neva; Arsyi, Fritzgerald Muhammad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp2273-2280

Abstract

Faculty of Mathematics and Natural Sciences (FMIPA) is one of the Faculties in Tanjungpura University with 9 Undergraduate Programs (S1). Based on the graduation data of the 2014 batch of FMIPA students, the number of students who did not complete their studies was 131 students or 29% of the total 445 students and 187 schools in Indonesia. If the study period of students can be predicted early, the study program can provide advice or recommendations so that students can complete their studies in/exactly 8 semesters. This study aims to determine the model for analyzing the factors that influence the graduation of FMIPA students using GWLR. Geographically Weighted Logistic Regression (GWLR) is a developing logistic regression model applied to spatial data. This model is used to predict data with binary dependent variables that consider the location characteristics of each observation. The units of observation in this study are the school location of 455 students spread across Indonesia. The variables used in this study were sourced from the Academic and Student Affairs Bureau UNTAN and divided into dependent variables (Y) and independent variables (X), i.e. Gender, college selection, Accreditation, School Type, School Location, and Name of Study Program. The dependent variable analyzed is the graduated status of FMIPA UNTAN students, i.e. completed and not completed their studies. The results showed that gender and the name of the study program are factors that affect the graduation of FMIPA UNTAN 2014 students with a classification accuracy of 72.6%.
Effect of aromatic herbs and roasted coconut flesh on acceptability and perception of mixed porridge (bubur paddas) Nofiani, Risa; Ardiningsih, Puji; Perdana, Hendra; Alatin, Isam; Hasanah, Kutsiatul; Roeswandi, Irine Fajrin; Juniarti, Leni; Huda, Nurul
AGROINTEK Vol 19, No 4 (2025)
Publisher : Agroindustrial Technology, University of Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/agrointek.v19i4.22979

Abstract

Bubur pedas or bubor paddas (BP) is porridge from roasted rice granules (R) rich in vegetables with a specific aroma that probably contributed to producing the aroma were roasted coconut flesh granules (C ), fresh kesum (Polygonum minus Huds) leaves (K), fresh buas-buas (Premna cordifolia ROXB) leaves (B), and fresh young tumeric (Curcuma longa) leaves (T). This study aimed to find out the effect of aroma-contributing ingredients (B, C, K, and T) and their role in developing specific aromas based on sensory panelists' acceptability and perception. Each aromatic ingredient was prepared in four serial formulations, namely C, K, B, and T, and a sensory test was then conducted using a hedonic rating method with a 9-point hedonic scale by a panel of 100-200 semi-trained panelists. The data were analyzed using a hierarchical analytical process (AHP), principle component analysis (PCA) biplot, multidimensional scaling (MDS) with alternating least squares scaling (ALSCAL) model, and Spearman's correlation. The highest acceptability for each aromatic ingredient's formula was 25 g of the C formula, 16 g of the K formula, 12 g of the B formula, and 12 g of the T formula, respectively. Almost the best formula for each aromatic ingredient's formula showed no correlation or dissimilarity. Among the aromatic ingredients, K and T played a pivotal role in developing the aroma, but only K enhanced the savory. Therefore, K and T were considered compulsory ingredients in generating a unique characteristic for BP in the panellists's perception
Co-Authors Aditya Handayani Al Amin Alatin, Isam Aldien, Royan Gustio Alex Sander Almazmar, Giatul Khodijah Hodijah Andani, Wirda Andi Hairil Alimuddin Anggi Putri Dewi Anggi, Muhamad Anis Fakhrunnisa Annisa Fitri Apriliyani, Techa Aprizkiyandari, Siti Ariady Zulkarnain Arsyi, Fritzgerald Muhammad Assa Trissia Rizal Atikasari, Awang Aulia Puteri Amari Cesoria, Yola Zerlinda Dadan Kusnandar Dadan Kusnandar Dadan Kusnandar Dadan Zaliluddin Debataraja, Naomi Nessyana Dedi Rosadi Deni Wardani Dinda Lestari Dwi Nining Indrasari Dzakirah, Nasya Rabbi Eka Rizki Wahyuni Elga Fitaloka Endah Saraswi Ersawahyuni, Aisna Evi Noviani Evy Sulistianingsih Faizah, Putri Alya Nur Fajar, Arif Nur Febriani, Nindy Febriani, Rani Febriyanto, Ferdy Fery Prastio Fidianty, Fadilla Firhan Januardi Firman Saputra Fortuna, Nia Fitriana Frans Xavier Natalius Antoni Gilang Habibie Gunawan, Sucipto Hapipah, Liza Darojatul Hariadi, Wahyudio Shaney Fikri Harnanta, Nabila Izza Hasanah, Kutsiatul Hasanuddin Hasanuddin Helmi Helmi Hidayat, Rani Lestari Huda, Nur’ainul Miftahul Huriyah, Syifa Khansa Iman Sanjaya Imanni, Rahmania Andarini Hatti Imro'ah, Nurfitri Imro’ah, Nurfitri Imtiyaz, Widad Indriani, Maria Meilinda Ira Mona Irwanto, Dicky Ismi Adam Jajad Sudrajat Jawani Jawani Juniarti, Leni Khabib Mustofa Laksono Trisnantoro Lilit Tamara Dinta Lisa Lestari M. Deny Hafizzul Muttaqin Maisarah Maisarah Margaretha, Ledy Claudia Mariana Yopi Mariatul Kiftiah Martha, Shantika Marwalida Rachmadiar Maulida Amanasari Mega Tri Junika Mida Mida Millennia Taraly Misrawi Misrawi Muhamad Ikbal Muhammad Ahyar Muhammad fauzan Muhardi Muhtadi, Radhi Mursyidah, Lailatul Mutiara Nurisma Rahmadhani Nabilah, Niken Aushaf Nanda Ayuni Nanda Shalsadilla Naomi Nessyana Debataraja Naomi Nessyana Debataraja Neva Satyahadewi Novita, Irene Nugrahaeni, Indah Nur Asiska Nur Azmi Nurfitri Imro'ah Nurfitri Imro’ah Nurhanifa, Nurhanifa Nurin Hafizah Nurmaulia Ningsih Nurul Huda Padilah, Ariski Paisal Paisal Pinasari, Repi Pitriani Pitriani Pranata Anggi Puji Ardiningsih Putri, Vinna Septyara Qalbi Aliklas Rafika Aufa Hasibuan Rahman, Tri Wanda Rahmania Andarini Hatti Imanni Rahmasari, Yulia Ramadhan, Nanda Ratna Nursariyani Ratna Sari Dewi Reni Unaeni Retnani, Hani Dwi Ria Fuji Astuti Rina Rina Risa Nofiani Risko, Risko Rivaldo, Rendi Roeswandi, Irine Fajrin Rofatunnisa, Sifa Salsabila, Hana Samson Samson Santika Santika Sasqia Aklysta Antaristi Setyo Wir Rizki Setyo Wira Rizki Setyo Wira Rizki Setyo Wira Rizki Shantika Martha Shantika Martha Shantika Martha Silvia Andriany Sinaga, Steven Jansen Sindia, Eri Sintia Margun Siti Julaeha, Siti Siti Septiani Rahayu Putri Solly Aryza Steven Jansen Sinaga Suci Angriani Suhardi Suprianto, Okto Syuradi syuradi Tamtama, Ray Taraly, Inggriani Millennia Thariq Thariq Tiara, Dinda Titania Aurellia Vinsensius Yogi Virginnia Atlantic Wafiq Nurhaliza Wahyu Diyan Ramadana Wilda Ariani Wira Fujiyanto Enizar Wirda Andani Wirdha Eryani Yohane, Novi Yonatan, Yulianus Yopi Saputra Yudhi Yumna Siska Fitriyani Yundari, Yundari Yundari, Yundari Yustosio, Darwis Yuveinsiana Crismayella Zahidah, Zahra