COVID-19 pandemic has brought great changes to the stability of the Indonesian state. The disease not only has an impact on public health but also has the effect of weakening the economic sector. One indicator is the weakening of the rupiah exchange rate against the USD. When the pandemic emerged, the rupiah exchange rate started to weaken, which may encourage investors to reduce investment in Indonesia. Therefore, it is necessary to predict the rupiah exchange rate during the COVID-19 pandemic for the coming period. This study applies the Double Exponential Smoothing forecasting method by adding a damped trend factor. The calculation of the parameters of the method becomes the research optimization problem. This optimization problem is then solved using metaheuristic methods, namely Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The performance of the forecasting model is measured based on the magnitude of the forecast error. This study shows that the PSO algorithm is better at obtaining the optimal parameters for predicting the rupiah exchange rate in the coming period compared to GA. The integration error rate of Double Exponential Smoothing damped trend with PSO is 0.70%, while the error rate for the same method with GA is 0.72%. Thus, the integrated performance of double exponential smoothing with metaheuristic optimization is a more excellent method in predicting the rupiah exchange rate against the USD during the period of the Coronavirus outbreak. Furthermore, the addition of a trend dampening factor to the DES method also significantly increases the forecast accuracy.
{"title":"Integration of Double Exponential Smoothing Damped Trend with Metaheuristic Methods to Optimize Forecasting Rupiah Exchange Rate against USD during COVID-19 Pandemic","authors":"Maftahatul Hakimah, M. Kurniawan","doi":"10.23917/khif.v6i2.9887","DOIUrl":"https://doi.org/10.23917/khif.v6i2.9887","url":null,"abstract":"COVID-19 pandemic has brought great changes to the stability of the Indonesian state. The disease not only has an impact on public health but also has the effect of weakening the economic sector. One indicator is the weakening of the rupiah exchange rate against the USD. When the pandemic emerged, the rupiah exchange rate started to weaken, which may encourage investors to reduce investment in Indonesia. Therefore, it is necessary to predict the rupiah exchange rate during the COVID-19 pandemic for the coming period. This study applies the Double Exponential Smoothing forecasting method by adding a damped trend factor. The calculation of the parameters of the method becomes the research optimization problem. This optimization problem is then solved using metaheuristic methods, namely Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The performance of the forecasting model is measured based on the magnitude of the forecast error. This study shows that the PSO algorithm is better at obtaining the optimal parameters for predicting the rupiah exchange rate in the coming period compared to GA. The integration error rate of Double Exponential Smoothing damped trend with PSO is 0.70%, while the error rate for the same method with GA is 0.72%. Thus, the integrated performance of double exponential smoothing with metaheuristic optimization is a more excellent method in predicting the rupiah exchange rate against the USD during the period of the Coronavirus outbreak. Furthermore, the addition of a trend dampening factor to the DES method also significantly increases the forecast accuracy.","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122431726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-24DOI: 10.23917/khif.v6i2.10468
Puteri Anidya Maulan, D. Manongga, I. Sembiring
Tambaksari is a village in Kendal Regency that has home industries ( Industri Rumahan , IR). The local government classifies these industrial activities of BUMDes (Village-Owned Enterprises) into three groups, namely IR-1, IR-2, and IR-3. Each group or class has its specific criteria. The significant local potentials in Tambaksari include fish farming and processing. The advantage of the local potential in Tambaksari is inseparable from the synergy between the local government and the people of Tambaksari. This study observed the patterns of actor interactions in 64 IRs in Tambak Sari. Data were collected from questionnaires and analyzed using the Social Network Analysis (SNA) method. The results showed that Tambaksari IRs have a network density of 5.5%, which suggests that the relationship was weak. Network analysis using UCINET illustrates the separation of the IR group, which further reinforces the existence of competition in the network. The study reveals the dominant actor in the network interaction based on the measure of degree centrality, closeness centrality, and betweenness centrality. He is the actor with id # 29 who is the Chairman of IR-2, 54 years old, who has a Pindang Fish Processing.
{"title":"Analysis of Communication Network Patterns of Home Industries (A Case Study in Tambaksari, Rowosari, Kendal)","authors":"Puteri Anidya Maulan, D. Manongga, I. Sembiring","doi":"10.23917/khif.v6i2.10468","DOIUrl":"https://doi.org/10.23917/khif.v6i2.10468","url":null,"abstract":"Tambaksari is a village in Kendal Regency that has home industries ( Industri Rumahan , IR). The local government classifies these industrial activities of BUMDes (Village-Owned Enterprises) into three groups, namely IR-1, IR-2, and IR-3. Each group or class has its specific criteria. The significant local potentials in Tambaksari include fish farming and processing. The advantage of the local potential in Tambaksari is inseparable from the synergy between the local government and the people of Tambaksari. This study observed the patterns of actor interactions in 64 IRs in Tambak Sari. Data were collected from questionnaires and analyzed using the Social Network Analysis (SNA) method. The results showed that Tambaksari IRs have a network density of 5.5%, which suggests that the relationship was weak. Network analysis using UCINET illustrates the separation of the IR group, which further reinforces the existence of competition in the network. The study reveals the dominant actor in the network interaction based on the measure of degree centrality, closeness centrality, and betweenness centrality. He is the actor with id # 29 who is the Chairman of IR-2, 54 years old, who has a Pindang Fish Processing.","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114691145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-22DOI: 10.23917/khif.v6i2.11281
Muhamad Ali Kasri, H. Jati
Every year UNIMUDA Sorong welcomes new students and keeps promoting to attract more. The process generates a growing number of student data. On the other hand, the promotional strategy to attract new students faces obstacles such as generalization among locations, ineffective time, limited personnel to carry out promotions, and cost inefficiency. This study examines the new student data and university marketing strategies to optimize time, effort, and cost. It uses the K-Means method for data grouping and the Simple Additive Weighting (SAW) for ranking the results of data grouping. The result of this research suggests that the location of promotion may be determined from the clustering process using the K-Means method. The silhouette coefficient test invalidates the data clustering, and the SAW method helps the ranking process to obtain a sequence of promotion locations. The ranking results reflect the predetermined decision table that directs promotion location selection according to the promotion strategy. The combination of the two methods helps to decide the location and marketing strategy to optimize time, effort, and cost. The results of this study may be used as a comparative reference for the management to decide the right promotion strategy based on the locations and student background.
{"title":"Combination of K-Means and Simple Additive Weighting in Deciding Locations and Strategies of University Marketing","authors":"Muhamad Ali Kasri, H. Jati","doi":"10.23917/khif.v6i2.11281","DOIUrl":"https://doi.org/10.23917/khif.v6i2.11281","url":null,"abstract":"Every year UNIMUDA Sorong welcomes new students and keeps promoting to attract more. The process generates a growing number of student data. On the other hand, the promotional strategy to attract new students faces obstacles such as generalization among locations, ineffective time, limited personnel to carry out promotions, and cost inefficiency. This study examines the new student data and university marketing strategies to optimize time, effort, and cost. It uses the K-Means method for data grouping and the Simple Additive Weighting (SAW) for ranking the results of data grouping. The result of this research suggests that the location of promotion may be determined from the clustering process using the K-Means method. The silhouette coefficient test invalidates the data clustering, and the SAW method helps the ranking process to obtain a sequence of promotion locations. The ranking results reflect the predetermined decision table that directs promotion location selection according to the promotion strategy. The combination of the two methods helps to decide the location and marketing strategy to optimize time, effort, and cost. The results of this study may be used as a comparative reference for the management to decide the right promotion strategy based on the locations and student background.","PeriodicalId":326094,"journal":{"name":"Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125071633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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