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All Journal Jurnal Statistika Universitas Muhammadiyah Semarang BAREKENG: Jurnal Ilmu Matematika dan Terapan Variance : Journal of Statistics and Its Applications Tensor: Pure and Applied Mathematics Journal Parameter: Jurnal Matematika, Statistika dan Terapannya PENGAMATAN: Jurnal Pengabdian Masyarakat untuk Ilmu MIPA dan Terapannya
Ronald John Djami
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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Journal : Tensor: Pure and Applied Mathematics Journal

 1 
Forecasting the Ambon City Consumer Price Index Using Arima Box-Jenkins Jefry Esna T. Radjabaycole; Ronald John Djami; Gabriella Haumahu
Tensor: Pure and Applied Mathematics Journal Vol 2 No 2 (2021): Tensor : Pure and Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol2iss2pp87-96

Abstract

The Consumer Price Index is an index number that measures the average price of goods and services consumed by households. The index number is the price comparison in a certain month against the previous month, in which case the price in the previous month is the price in the base year in the CPI calculation. CPI is time series data, so CPI data in the next period can be known by forecasting through time series analysis. Arima is a technique for finding the most suitable pattern from a group of data (curve fitting). Based on the results of the analysis, the best ARIMA model used in forecasting CPI in Ambon city for the period January 2007 to December 2020 is the ARIMA model (1,1,1), namely 1 = 0.9000 and 1 = 0.9933.
Application of the Spatial Regression Model to Analyze Factors that Influence the Human Development Index (HDI) in West Papua Province Gainau, Intan Friska; Djami, Ronald John; Sinay, Lexy Jansen; Beay, Lazarus Kalvein
Tensor: Pure and Applied Mathematics Journal Vol 4 No 2 (2023): Tensor: Pure and Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol4iss2pp83-92

Abstract

Indeks Pembangunan Manusia merupakan suatu angka yang bertujuan untuk melihat kinerja pembangunan wilayah dengan dimensi yang luas. Provinsi Papua Barat merupakan salah satu provinsi yang IPM terus meningkat setiap tahunnya, meskipun terus mengalami peningkatan, Provinsi Papua Barat tetap menduduki peringkat ke-2 indeks pembangunan manusia terendah di Indonesia. Untuk terus meningkatkan indeks pembangunan manusia di Provinsi Papua Barat perlu diketahui faktor-faktor mengetahui yang mempengaruhinya, salah satu cara yang digunakan untuk menentukannya yaitu dengan pemodelan regresi. Pada penelitian ini dilakukan analisis regresi untuk mendapatkan informasi pengamatan yang dipengaruhi efek lokasi. Hasil penelitian ini menunjukan bahwa pemodelan menggunakan SAR lebih baik dibandingkan menggunkan OLS. Model SAR menghasilkan nilai koefisien determinasi sebesar 0.987126 lebih besar dari model OLS yaitu 0.982664 dan nilai AIC dari model SAR sebesar 40.3641 lebih kecil dibandingkan model OLS yaitu 44.1147.
Application of the Seasonal Autoregressive Integrated Moving Average (SARIMA) Method to Forecast the Number of Vessel Passenger Departures tt Yos Soedarso Ambon Port Butarbutar, Winda; Van Delsen, Marlon Stivo Noya; Djami, Ronald John
Tensor: Pure and Applied Mathematics Journal Vol 4 No 2 (2023): Tensor: Pure and Applied Mathematics Journal
Publisher : Department of Mathematics, Faculty of Mathematics and Natural Sciences, Pattimura University, Ambon, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/tensorvol4iss2pp105-118

Abstract

Maluku Province is a fairly large archipelago in Indonesia. The large number of islands which are the administrative areas of Maluku Province, encourages the creation of a supporting transportation system. Yos Soedarso Ambon Port is the largest port in Ambon. Based on the statistics of Indonesia, the number of ship passengers at Yos Soedarso Port in Ambon during the April 2023 period experienced an increase of 44.97 percent, while in the March 2023 period, it only experienced an increase of 42.94 percent. Because the data used is time series data and has a seasonal pattern, the most appropriate method for predicting the number of passengers is the Seasonal Autoregressive Moving Average (SARIMA) method. The SARIMA method is an approach model developed from the Autoregressive Moving Average (ARIMA) model used on time series or data with a seasonal pattern. This research produced the best model for forecasting the number of departures of ship passengers at Yos Soedarso Port, Ambon. With an MSE value of 26.44. with the shape of the model with MAPE 10.23%.
Co-Authors Beay, Lazarus Kalvein Butarbutar, Winda Candio, Syaifullah Adam Gabriella Haumahu Gainau, Intan Friska H. W. M. Patty Hayoto, Sasmita Hiariey, Arlene H Jefry Esna T. Radjabaycole Laamena, Novita Serly Lexy Janzen Sinay, Lexy Janzen Noya Van Delsen, M.S. Salhuteru, R. Sampulawa, Zulfikar Ilham Sinay, Lexy Jansen Sony Sunaryo Van Delsen, Marlon Stivo Noya Wattimanela, H. J. Yonlib Weldri Arnold Nanlohy Yopi Andry Lesnussa