Implementation of singular spectrum analysis in the forecasting of seawater wave height

Indonesia is renowned as a maritime nation, positioned amidst the Pacific Ocean and the Indian Ocean. This strategic location grants Indonesia the distinct advantage of serving as a global crossroads for maritime traffic, particularly with regards to trade and waterborne transportation. Among Indonesia's bustling ports, Tanjung Priok Port stands out as one of the busiest. In this context, the measurement of seawater wave height assumes a pivotal role in shaping the dynamics of transportation and commercial activities at Tanjung Priok Port. Hence, the availability of predictive insights into forthcoming seawater wave height assumes paramount significance in proactively addressing potential calamities and orchestrating maritime endeavors more efficaciously. This study aims to apply the Singular Spectrum Analysis (SSA) technique to forecast the wave height of seawater at Tanjung Priok Port. The dataset employed encompasses the daily seawater wave height observations recorded at Tanjung Priok Harbor during the timeframe from January 2022 to May 2023. The findings of this research unveil a parameter value of L = 98, a Grouping Effect (r) of 13, and a Mean Absolute Percentage Error (MAPE) value of 10.01%. This MAPE value signifies that the forecasting yielded by the Singular Spectrum Analysis (SSA) methodology exhibits a satisfactory level of accuracy in prognosticating future seawater wave heights at Tanjung Priok Port

Peramalan Jumlah Investasi Usaha Mikro Dan Kecil (UMK) dengan Menggunakan Metode Double Exponential Smoothing (Studi Kasus di Kabupaten Sidoarjo)

Industry is the activity of processing raw materials into finished goods which have the added value of their purpose, which is to get more profits. Micro and Small Enterprises (MSEs) are very efficient in the economic development of the people of Sidoarjo, based on data obtained from the Disperindag of Sidoarjo Regency, the amount of investment in the micro and small industries has increased the most compared to medium and large industries from year to year. To find out the amount of investment in 2018, a double exponential smoothing method is calculated so that the forecasting result id Rp. 76.124.607.773 with an error value of 6.639%

Prediksi Jumlah Gempa Tektonik di Wilayah Jawa Timur dengan Menggunakan Metode ARIMA Box Jenkins dan Kalman Filter

Indonesia merupakan negara yang tercangkup dalam wilayah cincin api pasifik aktif (Ring of Fire). Dengan demikian, gempa bumi menjadi fenomena alam yang sudah tidak asing lagi terjadi di Indonesia. Gempa dengan kekuatan magnitudo yang cukup besar akan beresiko merusak sumber daya alam, manusia, dan infastruktur bangunan. Dalam hal ini, sangat perlu dilakukan studi penelitian untuk memprediksi gempa bumi sebagai upaya mitigasi bencana. Metode prediksi yang diterapkan pada studi ini adalah metode ARIMA yang akan diperbaharui dengan estimasi Kalman Filter. Pada perhitungan ARIMA didapatkan model terbaik yaitu ARIMA(0,1,1) dengan perolehan MAPE yang cukup besar yakni 50.5788 sedangkan hasil pembaharuan model ARIMA-KF(0,1,1) memperoleh MAPE yang sangat baik yakni 0.0071. Oleh karena itu, etimasi Kalman Filter dapat dikatakan cukup mumpuni dalam pembaharuan model prediksi ARIMA. Prediksi jumlah gempa tektonik di wilayah Provinsi Jawa Timur pada tahun 2018 paling banyak terjadi pada bulan Juli yakni sebanyak 114 kejadian sedangkan paling sedikit pada bulan Januari yakni 13 kejadian

Application Random Forest Method for Sentiment Analysis in Jamsostek Mobile Review

Purpose: This study aims to monitor the service quality of JMO applications from time to time by classifying JMO user reviews into the class of positive, neutral, and negative sentiments.Design/methodology/approach : The method used in this study is the random forest classification method. Data processing in this study uses feature extraction, TF-IDF and labeling with the lexicon-based method.Findings/result: Based on the research results, it was found that the highest frequency of classification was the positive class with 17571 reviews compared to the neutral class with 8701 reviews and the negative class with 3876 reviews with an accuracy evaluation value of 93%, precision 88%, recall 93%, and f1-score 90%.Originality/value/state of the art:This study uses 150737 reviews that have been pre-processed using the random forest method and TF-IDF and lexicon-based feature extraction

Analisis Pengendalian Persediaan Batu Bara Menggunakan Metode Economic Order Quantity

Inventory is an important factor in making a production. Many companies experience problems in terms of inventory control, one example of which is scarity of inventory. The purpose of tis study is to optimize the needs of goods so that the company will not experience problems with lack of inventory or stockpiling. This research uses the Economic Order Quantity, Safety Stock, Reorder Point, and Maximum Inventory methods by collecting data in the form of inventory of goods needs, ordering costs, and inventory costs. The results of this research are found to have an economic inventory requirement of 19.716.262 kg. Inventory costs generated through the calculation of the EOQ method are Rp. 90.750.967. The safety stock value of 855.580 kg is useful to protect and anticipate the occurrence of inventory shortages, so the company must be on guard when it is at that value. Then, the Reorder Point value is obtained at 907.210 kg. Furthermore, the value of the Maximum Inventory is 20.571.842 kg so the company is not recommended to have inventory more than that value

COMPARISON OF FORECASTING VIOLENCE CASES NUMBER AGAINST WOMEN AND CHILDREN USING DOUBLE EXPONENTIAL SMOOTHING (DES) AND AUTO REGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) METHODS

Violence is something that is being widely discussed. It is due to the increasing number of victims of violence in a scope where victims should feel safe. Therefore, the researchers took this case intending to predict the number of violence cases against women and children in Jakarta so that the government can anticipate the spike in cases and evaluate the policies that will be issued in this case. The data used was from the Office for the Empowerment of Child Protection and Population Control (DPPAPP) of DKI Jakarta Province from January 2018 to October 2021 to predict the number of cases in 2022. Based on the analysis results, it is known that the number of cases of violence against women and children has decreased throughout 2022. In addition, the accuracy of the model using the Double Exponential Smoothing (DES) method is 44.91%, and the Auto-Regressive Integrated Moving Average (ARIMA) is 39.03%

Optimalisasi Traffic Light Berdasarkan Kepadatan Kendaraan dengan Teknik Edge Detection Operator Sobel dan Metode Fuzzy Logic Sugeno (Studi Kasus: Jalan Margorejo Indah)

Traffic jam is one of the many problems of major cities in Indonesia that need to be solved. One form of traffic jam is long queues at traffic light. Therefore, an effort that can be used to reduce traffic jam is to build a better or efficient traffic light control system to manage traffic at a crossroads. A traffic light system that is needed is one that can adjust the time and duration of the traffic lights that are adjusted to the density of road conditions that are not dense, normal, congested, and very dense. Margorejo Indah street at Surabaya is a district that has traffic jam or long queues at certain hours. Optimization of the duration of the green light can be applied by using image data that is simulated with the edge detection method of the Sobel operator resulting in boundary values ​​to then be processed with Sugeno fuzzy logic. The results obtained for a long duration of green light obtained were 37 seconds with regard to road condition

ARIMA MODEL OF OUTLIER DETECTION FOR FORECASTING CONSUMER PRICE INDEX (CPI)

The Consumer Price Index (CPI) is a indicator used by Badan Pusat Statistik (BPS) which describes the average change in the prices paid by urban consumers for a market basket of consumer goods and services in a certain period. The case on Consumer Price Index (CPI) of Probolinggo City, if the Consumer Price Index (CPI) increase then describe inflation occurs and conversely. The Consumer Price Index (CPI) of Probolinggo City increase is not fixed. This study is to forecast the Consumer Price Index (CPI) that the results can be used as one of the considerations in carrying out economic development in the future. Research focused on the data of Consumer Price Index (CPI) of Probolinggo City from January 2014 to April 2022. Methodology implemented in this study is Autoregressive Integrated Moving Average (ARIMA). Result show that ARIMA  without an outlier was the best model for predicting Consumer Price Index (CPI) of Probolinggo City for the next 8 months. This model shows the value of MAPE is . The value of forecasting results in each month has decreased and increased not so significantly where in May 2022 the forecasting value was 108,391 then in June 2022 the forecasting value became 108,411 and so on until December 2022 the forecasting results using ARIMA model   of 107,845

ANALISIS PREDIKSI JUMLAH PENDUDUK DI KOTA PASURUAN MENGGUNAKAN METODE ARIMA

Laju pertumbuhan penduduk di Kota Pasuruan pada tahun 2019 sebesar 0.68% dengan jumlah penduduk 200.422 jiwa. Tingginya pertumbuhan penduduk dapat mempengaruhi kepadatan penduduk. Penelitian ini bertujuan untuk memprediksi pertumbuhan penduduk Kota Pasuruan menggunakan metode ARIMA (Autoregressive Integrated Moving Average). Metode ARIMA adalah cara prediksi data deret waktu yang memiliki tiga model, yaitu AR (Autoregressive), MA (Moving Average), ARMA (Autoregressive Moving Average). Metode ini memiliki parameter (p,d,q) dapat diketahuidari plot ACF dan PACF untuk memastikan model yang akan digunakan untuk prediksi. Dalam penelitian ini data yang digunakan merupakan data penduduk Kota Pasuruan tahun 1983 sampai tahun 2019 sejumlah 37 data. Dari data tersebut didapatkan ARIMA model (1,1,1) dengan jumlah penduduk Kota Pasuruan pada tahun 2020 adalah 203.221 jiwa, didapatkan nilai MSE 10542507.06 dan MAPE 1.52%

Breast Cancer Survival Analysis Using Cox Proportional Hazard Regression and Kaplan Meier Method

Breast cancer is one of the malignant tumors that begins in the breast cells that develop and attack the surrounding tissues; according to World Health Organization (WHO), breast cancer is globally declared the top five killer cancers. In Indonesia, breast cancer becomes the number one killer cancer.  One of the successes in breast cancer treatment is if the cure obtained by cancer patients can be proven to have the same life expectancy as those who do not have breast cancer.This study aims to know the probability of survival of breast cancer patients and know the factors that affect breast cancer patients' survival. The data were consist of 394 medical records of breast cancer patients at Dr. Soetomo Hospital Surabaya in the period January 2018 – December 2019, with variables used, i.e., initial age of infection, clinical stage, tumor size, metastatic to other organs, type of treatment, and patient status (life or death). This study using Kaplan Meier and Cox Proportional Hazard regression methods, and the result showed that the probability of survival of breast cancer patients (with data samples) was 0.737 or 73.7%. The variables that significantly affect breast cancer patients' survival are the initial age of infection, the clinic stage, and the tumor's size. This research provides information and motivation to the community related to life expectancy, especially in breast cancer patients, to stay motivated in the healing process. In addition, this research is also used to add insight to academics, especially the department of statistics, regarding the regression of Cox Proportional Hazard in analyzing the survival of breast cancer patients