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All Journal Journal of the Indonesian Mathematical Society Jurnal Minds: Manajemen Ide dan Inspirasi BAREKENG: Jurnal Ilmu Matematika dan Terapan JEMMA | Journal of Economic, Management and Accounting Variance : Journal of Statistics and Its Applications Indonesian Actuarial Journal
Zainuddin, Ahmad Fuad
School Of STEM, Universitas Prasetiya Mulya, Tangerang, Indonesia
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation

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ANALISIS PERSEPSI DAN POLA PERILAKU MASYARAKAT HULU DAS LATUPPA DALAM MELAKUKAN KONSERVASI LAHAN DAN AIR UNTUK INISIASI KONSEP PEMBAYARAN JASA LINGKUNGAN DI KOTA PALOPO Jibria Ratna Yasir; Wahida Wahida; Ahmad Fuad Zainuddin
JEMMA (Journal of Economic, Management and Accounting) Vol 1, No 1 (2018): Maret 2018
Publisher : Universitas Andi Djemma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35914/jemma.v1i1.79

Abstract

Meningkatnya jumlah penduduk, pertumbuhan dan pembangunan ekonomi menyebabkan ketersediaan dan pemanfaatan air bersih (fresh water) untuk memenuhi kebutuhan hidup manusia dan peningkatan kinerja ekonomi mengalami perubahan dan cenderung menimbulkan kelangkaan akan air bersih. Salah satu ekosistem tempat air mengalir yang mengalami degradasi fungsi akibat pola perilaku manusia yang tidak memperhatikan aspek kelestarian lingkungan adalah Daerah Aliran Sungai (DAS). Adanya peningkatan degradasi fungsi DAS mendorong tumbuhnya kesadaran untuk mengenali kegiatan pelayanan lingkungan yang dapat dilakukan untuk menjaga fungsi DAS tersebut. Masifnya tingkat kerusakan DAS, umumnya dipicu oleh kerusakan hutan yang relatif tinggi, sebagai turunan dari perilaku menyimpang masyarakat seperti: illegal logging dan alih fungsi lahan hutan menjadi areal pertanian tanaman semusim. Kondisi tersebut telah menimbulkan kekhawatiran dan permasalahannya menuntut adanya pola pengelolaan DAS yang baik dan tepat. Siklus saling ketergantungan antara pemanfaat air bersih di hilir dengan penyedia jasa lingkungan air bersih di hulu menciptakan adanya suatu ide reward atau penghargaan yang diberikan kepada masyarakat hulu untuk berbagai kegiatan yang dilakukan dalam rangka merehabilitasi kawasan yang diwujudkan dalam kerangka mekanisme pembayaran jasa lingkungan. Tujuan umum penelitian ini adalah mengestimasi besaran nilai kompensasi untuk masyarakat hulu. Penelitian ini dilakukan di dua Kecamatan yaitu Kecamatan Mungkajang dan Kecamatan Sendana yang merupakan kecamatan yang berada di Hulu DAS Latuppa Kota Palopo. Data yang digunakan dalam penelitian ini adalah data primer dan sekunder. Penelitian ini menggunakan analisis Spearman (skala likert) dengan rataan skor untuk mengetahui persepsi dan pola perilaku masyarakat dalam melakukan rehabilitasi di hulu DAS Latuppa. Hasil dari rataan skor menunjukkan masyarakat hulu DAS Latuppa di Kecamatan Mungkajang dan Sendana yang merupakan penyedia jasa lingkungan khususnya kelompok tani To’buangin dan kelompok tani Se’pon bersedia merehabilitasi lahan dan air di hulu DAS Latuppa dengan mekanisme pembayaran jasa lingkungan.
WORKFORCE GROUPING IN COMPLETING PROJECTS WITH INTERN WORK ACTIVITY LOG DATA Brandon Anggawidjaja; Faizah Sari; Ahmad Fuad Zainuddin
VARIANCE: Journal of Statistics and Its Applications Vol 5 No 2 (2023): 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/variancevol5iss2page131-138

Abstract

This study consists of an attempt to optimize the K-Means Clustering Algorithm and calculating the Full Time Equivalent (FTE) of each cluster based on intern's daily work log data. The optimization will be done by using some of K-Means Clustering’s validation method to estimate the best K clusters of the data. The validation methods that will be used to optimize the algorithm are Elbow Criterion Method and Silhouette Score Index. The initial k cluster will be formed and evaluated using Davies Bouldin Index analysis. The divided clusters are supposed to be classified by the rate of complexity of each project. The calculated FTE will be used to estimate the workload for the current workforce. This estimation is hoped to help companies decide in their hiring decision.
Joint-Life Insurance Premium Model Using Archimedean Copula: The Study of Mortality in Indonesia Ramadhan, Muhammad Akhirul; Zainuddin, Ahmad Fuad; Pasaribu, Udjianna Sekteria; Sari, RR Kurnia Novita
Journal of the Indonesian Mathematical Society Vol. 31 No. 1 (2025): MARCH
Publisher : IndoMS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22342/jims.v31i1.1783

Abstract

Joint-life insurance pays a sum insured when the first death occurs. This insurance has a case based on the order of exit from the cohort, namely joint life and last survivor. The former means that one of the insured leaves the cohort, while the latter means the last member of the insured has left his or her cohort. For some reasons of simplicity, the insurance premium is usually calculated with the assumption that the husband and wife are mutually independent. However, this assumption is considered unrealistic. Couples are open to the same risks, hence explaining joint survival model should involve dependence structures between the distribution of spouse mortality. In line with this, to understand the dependence structure of multiple random variables, the approach used is Copula. In this context, Copula relates the marginal distribution function of these variables to the joint life distribution. One of the advantages from Copula is that the random variables do not have to come from the same distribution, hence Copula is considered good enough to explain the dependence of the mortality rate between husband and wife. This study aimed to develop a joint survival model for calculating joint life insurance premiums using the concept of Archimedean Copula to discover the minimum premium value by conducting the following steps: first, identifying the marginal distributions of mortality for genders using Indonesian Mortality Table IV (TMI/Tabel Mortalitas Indonesia IV); second, Archimedean copula function-based constructing survival models that captures the relationship between these variables; third, setting dependency parameter θ; fourth, calculating the joint life premium using Archimedean copula based survival modeled for each correlation dependency level; and carrying out optimization to find the minimum premium value. This can be achieved by formulating the problem as an optimization problem, considering an objective function that yields the lowest premium till satisfying the financial requirements of the insurance company.
LOSS MODEL OF CLIMATE INSURANCE BASED ON EFFECT OF GROWING DEGREE DAYS INDEX Anggasari, I Gusti Ayu Wulan; Zainuddin, Ahmad Fuad; Indratno, Sapto Wahyu; Yunus, Muhammad Haekal
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp0893-0902

Abstract

Climate change is a threat to agriculture, especially food crops such as rice. Climate index insurance is an alternative to cover the risk of agricultural losses due to crop failure due to climate change factors. The observed climate index is the effect of growing degree days which measures the impact of temperature on plant growth and development. The data used in this study is daily temperature data at Climatology Station Class 1 Darmaga, Bogor and Meteorological Station Class 3 Citeko, West Java, during the gadu (rice that is planted in the Gadu/Dry season) planting period. In determining the amount of loss, the average daily temperature on growing degree days is calculated using a combination of a time series model and a deterministic model. The deterministic model describes the trend and seasonality of the time series at each station. The parameters contained in the model will be estimated using least-square. To see the dependence of temperature at different stations using a normal bivariate distribution. The result show that the amount of loss based on the index of growing degree days per unit rupiah per degree Celsius (℃) for Meteorological Station Class 3 Citeko only occurs for certain percentages, namely 80%, 90%, and 95%, while for Climatology Station Class 1 Darmaga Bogor it can occur for each percentage. This indicates that the amount of losses obtained will depend on determining the strike level by using the mean and standard deviation of the growing degree days index distribution. Furthermore, these findings suggest that Climatology Station Class 1 Darmaga Bogor have higher risk of crop failure due to climate change than Meteorological Station Class 3 Citeko.
PREDIKSI NILAI KURS MATA UANG DOLLAR AMERIKA (USD) DAN YUAN CHINA (CNY) DENGAN RUPIAH (IDR) MENGGUNAKAN METODE ARIMA Teja, Satya Dhira Alfa; Derick, Luigi; Tauryawati, Mey Lista; Zainuddin, Ahmad Fuad
VARIANCE: Journal of Statistics and Its Applications Vol 6 No 1 (2024): 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/variancevol6iss1page99-112

Abstract

Bonus demografi yang sedang terjadi di Indonesia tidak sebanding dengan lapangan pekerjaan yang tersedia. Hal ini menyebabkan banyak dari mereka untuk mencari sumber pendapatan dari berbagai tempat, salah satunya dengan berinvestasi atau trading. Trading forex juga merupakan sumber pendapatan yang potensial jika dilakukan dengan benar. Analisa dengan menggunakan metode yang benar dapat membantu untuk sukses dalam dunia trading forex. Dalam dunia forex, mata uang Dollar Amerika (USD) dan Yuan China (CNY) merupakan mata uang yang sering dipilih karena paling berpotensi menghasilkan keuntungan. Penelitian ini bertujuan untuk melakukan prediksi harga kurs Dollar Amerika (USD) dan Yuan China (CNY) terhadap Rupiah (IDR) menggunakan metode Autoregressive Integrated Moving Average (ARIMA). Data kurs mata uang USD dan CNY akan dibagi menjadi data train dan test untuk memprediksi secara long term (10 hari), dan short term (5 hari). Dari hasil analisa tersebut, diperoleh bahwa model ARIMA (2,0,2) adalah model terbaik untuk memprediksi kurs USD terhadap IDR, sedangkan model ARIMA (3,0,2) adalah model terbaik untuk prediksi kurs CNY terhadap IDR. Model terbaik diperoleh berdasarkan nilai AIC terendah dan signifikansi parameter. Setelah mendapatkan model terbaik untuk nilai tukar kurs mata uang USD dan CNY terhadap IDR, selanjutnya dilakukan prediksi untuk jangka waktu short term dan long term. Hasil menunjukkan bahwa untuk meramalkan secara short term, model ARIMA yang telah diperoleh, cocok untuk digunakan. Namun, untuk meramalkan secara long term, model ARIMA tersebut masih kurang akurat untuk digunakan, karena keterbatasan data train.
Understanding Generation X’s Adoption of Digital Payment Systems: An Integrated Utaut–ToE Perspective Yunus, Muhammad Haekal; Nurjannah, Nurjannah; Zainuddin, Ahmad Fuad; Erwina, Erwina
Jurnal Minds: Manajemen Ide dan Inspirasi Vol 12 No 2 (2025): December
Publisher : Management Department, Universitas Islam Negeri Alauddin Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/minds.v12i2.56396

Abstract

This study examines Generation X’s intention to adopt digital payment systems by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Technology–Organization–Environment (ToE) framework. It contributes to the fintech adoption literature by explicitly disentangling individual-level behavioral drivers from organizational and environmental constraints, thereby clarifying why adoption among Generation X remains uneven despite widespread technological diffusion. Using survey data from 200 Generation X respondents and analyzing the model with PLS-SEM, we find that UTAUT constructs, including performance expectancy, effort expectancy, social influence, facilitating conditions, and trust, significantly predict adoption intention. In contrast, ToE-related factors exhibit weaker explanatory power, suggesting limited salience of organizational and environmental conditions for this cohort. These findings imply that policies and managerial strategies aimed at accelerating fintech adoption among Generation X should prioritize behavioral alignment and digital confidence rather than structural or institutional interventions.
Robust E-Bayesian Estimation and Prediction of Esscher Premium for Car Insurance Claim Frequencies Under a Negative Binomial Model Eli Zulkatri; Muhammad Azka; Ahmad Fuad Zainuddin
Indonesian Actuarial Journal Vol. 2 No. 1 (2026)
Publisher : Persatuan Aktuaris Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65689/iajvol2no1pp069-080

Abstract

Car insurance claim frequencies often exhibit overdispersion, making the Poisson model too restrictive for premium estimation. This study develops a Negative Binomial-based Bayesian and E-Bayesian framework for estimating and predicting Esscher premiums using aggregated car insurance claim-frequency data. The novelty of this study lies in combining a closed-form Esscher premium under the Negative Binomial model with Bayesian conjugate updating and E-Bayesian hyperparameter averaging to reduce sensitivity to prior specification. A simulated aggregated claim-frequency table with 1,200 exposure units was used to illustrate the proposed framework. The data contained 642 total claims, with an empirical mean of 0.5350 and a sample variance of 0.8378. The variance-to-mean ratio of 1.5660 confirmed overdispersion and supported the use of the Negative Binomial model over the Poisson model. The method-of-moments estimates were  for the dispersion parameter and  for the success probability. At the representative tilt parameter , the Esscher premiums obtained from the method-of-moments, Bayesian, and E-Bayesian approaches ranged from 0.9004869 to 0.9059240, indicating stable premium estimates across alternative estimation methods. The sensitivity analysis showed that the Esscher premium increases nonlinearly with the tilt parameter, confirming its role as a risk-loading control. The prequential illustration further showed that the framework can support one-step-ahead prediction for aggregated claim totals. Overall, the proposed approach provides a robust and analytically tractable premium estimation framework for overdispersed car insurance claim-frequency data when prior information is uncertain and only aggregated data are available.
MAPPING DISASTER-PRONE AREAS ON JAVA ISLAND USING THE K-PROTOTYPES ALGORITHM Mey Lista Tauryawati; Ahmad Fuad Zainuddin
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0179-0196

Abstract

Clustering in disaster areas is often implemented as a disaster mitigation effort with the aim of minimizing risk. Determining the appropriate clustering method based on the data set will influence the clustering results. K-Prototypes is a clustering method that is capable of handling mixed data, numerical and categorical data, so this method is suitable to clustering disaster prone area with mixed data of disaster factors such as incident intensity, type of disaster, population density, and level of infrastructure vulnerability. This research focuses on disaster prone areas on Java Island and clustering using K-Prototypes to group and map areas that have the highest to lowest levels of disaster vulnerability based on the number of incidents, number of victims, and the amount of damage to facilities and the type of disaster. The clustering results obtained mapping of cities in the province into cluster groups based on the level of vulnerability and calculated potential losses based on disasters in each province. Afterward, the clustering results are used to determine priority areas for disaster mitigation to minimize losses.
Co-Authors Anggasari, I Gusti Ayu Wulan Brandon Anggawidjaja Derick, Luigi Eli Zulkatri Erwina Erwina, Erwina Faizah Sari Indratno, Sapto Wahyu Jibria Ratna Yasir Mey Lista Tauryawati Muhammad Azka Muhammad Haekal Yunus Nurjannah Nurjannah Pasaribu, Udjianna Sekteria Ramadhan, Muhammad Akhirul Sari, RR Kurnia Novita Teja, Satya Dhira Alfa Wahida Wahida