Indonesian Journal on Computing (Indo-JC)
Indonesian Journal on Computing (Indo-JC) is an open access scientific journal intended to bring together researchers and practitioners dealing with the general field of computing. Indo-JC is published by School of Computing, Telkom University (Indonesia).
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<![CDATA[Classification Model of Consumer Question about Motorbike Problems by Using Naïve Bayes and Support Vector Machine ]]>
<![CDATA[Ekky Wicaksana]]>;
<![CDATA[Danang Triantoro Murdiansyah]]>;
<![CDATA[Isman Kurniawan]]>
<![CDATA[ Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 2 (2021): September, 2021 ]]>
Publisher : <![CDATA[School of Computing, Telkom University ]]>
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DOI: 10.34818/INDOJC.2021.6.2.561
<![CDATA[The motorbike plays an important role in supporting daily activity. The motorbike is known as one of the transportation modes that is frequently used in Indonesia. The number of motorbikes used in Indonesia is continuously increasing time by time. Hence, the occurrence of motorbike problems can affect community activity and disturb the economic condition in society. Since the problem of the motorbike can occur at any time, a prevention action is required by providing an online consultation platform. However, a classification model is required to handle a wide range of questions about the motorbike problem. By classifying those questions into a specific class of problems, the solution can be delivered to the consumer faster. In this study, we developed prediction models to classify consumer questions. The data set was collected from consumer questions regarding motorbike problems that are commonly occurring. The model was developed using two machine learning algorithms, i.e., Naïve Bayes and Support Vector Machine (SVM). Text vectorization was performed by using the n-gram and term frequency-inverse document frequency (TF-IDF) method. The results show that the SVM model with the uni-trigram model performs better with the value of accuracy and F-measure, which are 0.910 and 0.910, respectively.]]>
<![CDATA[Information Technology Governance Audit Using the COBIT 5 Framework (Case Study of PDAM Tirta Patriot Kota Bekasi) ]]>
<![CDATA[Lisda Awalia Aprilianti]]>;
<![CDATA[Eko Darwiyanto]]>;
<![CDATA[Yanuar Firdaus Arie]]>
<![CDATA[ Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 2 (2021): September, 2021 ]]>
Publisher : <![CDATA[School of Computing, Telkom University ]]>
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DOI: 10.34818/INDOJC.2021.6.2.563
<![CDATA[PDAM Tirta Patriot has implemented information systems for its business process but still has deficiencies, including some business processes that do not have documented guidelines and procedures. Furthermore, the human resources in PDAM Tirta Patriot are insufficient for improving IT governance due to the lack of reliable personnel in the IT unit. Given the importance of IT for PDAM, an audit is needed to evaluate the capability of the IT unit in managing IT. COBIT 5 provides a goals cascade to align the company with its business goals. However, the goals cascade does not provide priority to IT-related goals. Therefore, for prioritizing IT-related goals, this research uses Analytical Hierarchy Process (AHP). From the AHP result, the selected domains are APO01, MEA01, and APO07. This research aims to determine the current capability level and analyze the gap between it and the chosen target capability level, precisely level 2. The current capability level of PDAM Tirta Patriot from domain APO01 is 1, MEA01 is 0, and APO07 is 0, which means none of those have reached the target capability level. Recommendations are given based on the unfulfilled work product for domains that do not reach the target capability level.]]>
<![CDATA[Forecasting Number of New Cases Daily COVID-19 in Central Java Province Using Exponential Smoothing Holt-Winters ]]>
<![CDATA[Dinda Fitri Irandi]]>;
<![CDATA[Aniq Atiqi Rohmawati]]>;
<![CDATA[Putu Harry Gunawan]]>
<![CDATA[ Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 2 (2021): September, 2021 ]]>
Publisher : <![CDATA[School of Computing, Telkom University ]]>
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DOI: 10.34818/INDOJC.2021.6.2.565
<![CDATA[There is hard to mention how long the COVID-19 pandemic will discontinue. There are some factors, including the public’s efforts to slow spread and researchers’ work to observe more about this outbreak. From the beginning of the health crisis, particularly following the announcement of the first positive case In Indonesia due to the COVID-19 on March 2, 2020. Afterwards, the number of daily cases increase simultaneously in other regions in Indonesia until today. Due to the fact that the significant mobility of the people, Central Java has contributed the 3rd rank of potential number of COVID-19 positive cases in Indonesia. This study aims to forecast the number of COVID-19 daily new cases in Central Java to assist the government in preparing the necessary resources and controlling the spread of the COVID-19 virus in Central Java Province. We proposed Exponential Smoothing Holt-Winters with the Additive model with seasonal addition considering trend and seasonal factors. The dataset during March 14 to April 17, 2021, revealed fluctuation of trend and seasonal patterns. Our simulation studies indicate that Exponential Smoothing Holt-Winters provides sharp and well performance for forecasting daily new cases of COVID-19 in Central Java province with MAPE less than 10%.]]>
<![CDATA[Multi Criteria Recommender System for Music using K-Nearest Neighbors and Weighted Product Method ]]>
<![CDATA[Muhamad Hafidh Nofal]]>;
<![CDATA[zk abdurahman baizal]]>;
<![CDATA[Ramanti Dharayani]]>
<![CDATA[ Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 2 (2021): September, 2021 ]]>
Publisher : <![CDATA[School of Computing, Telkom University ]]>
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DOI: 10.34818/INDOJC.2021.6.2.575
<![CDATA[Currently, the music industry has grown rapidly which has led to an information overload that hinders users from finding the music they want, because everyone has their own unique characteristics. In a previous study, the Recommender System converted music lyrics into digital values using Lexicon's Non-Commercial Research (NRC) and K Nearest Neighbors (KNN) to look for similarities between music. However, this system only uses lyrics to recommend music, so it doesn't pay more attention to user preferences. Therefore, in this study adds criteria from users using the Weighted Product Method (WPM) to weight the music criteria with the input criteria from users. In this study uses a music dataset from 2000 to 2019 taken from the Kaggle website. The purpose of this study was to measure user satisfaction using the System Usability Scale (SUS). In this case, the user is free to answer 10 questions regarding the results of the recommendations provided by the system. Based on the results of the questionnaire, the SUS score was 83.65. This score is included in the EXCELLENT category with grade A scale]]>
<![CDATA[An Exponential Smoothing Holt-Winters Based-Approach for Estimating Extreme Values of Covid-19 Cases ]]>
<![CDATA[Abi Rafdhi Hernandy]]>;
<![CDATA[Aniq Atiqi Rohmawati]]>;
<![CDATA[Putu Harry Gunawan]]>
<![CDATA[ Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 2 (2021): September, 2021 ]]>
Publisher : <![CDATA[School of Computing, Telkom University ]]>
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DOI: 10.34818/INDOJC.2021.6.2.576
<![CDATA[Covid-19 is an ongoing outbreak across the world infecting millions, having significant fatality rate, and triggering economic disruption on a large scale. The demand of healthcare facility has been significantly affected by the increased Covid-19 cases. Many countries have been forced to do lockdown and physical distancing to avoid a crucial peak of novel Covid-19 pandemic that potentially overwhelms healthcare services. Central Java is the province with the third highest population density in Indonesia and predicted to be affected significantly over a particular period of this outbreak. Our paper aims to provide a modelling to estimate extreme values of daily Covid-19 cases in Central Java, between March and April 2021. We particularly capture seasonality during this period using Exponential Smoothing Holt-Winters. We employ that Value at Risk and mean excess function based-approaches for extreme value estimation. Our simulation studies indicate that Exponential Smoothing Holt-Winters and Value at Risk provide sharp and well prediction for extreme value with zero violation. Since a number of positive cases has resulted unprecedented volatility, estimating the extreme value of daily Covid-19 cases become a crucial matter to support maintain essential health services.]]>
<![CDATA[Tourism Recommender System using Weighted Parallel Hybrid Method with Singular Value Decomposition ]]>
<![CDATA[Yoan Amri Akbar]]>;
<![CDATA[zk abdurahman baizal]]>;
<![CDATA[Agung Toto Wibowo]]>
<![CDATA[ Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 2 (2021): September, 2021 ]]>
Publisher : <![CDATA[School of Computing, Telkom University ]]>
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DOI: 10.34818/INDOJC.2021.6.2.579
<![CDATA[Presently, we often get suggestions for recommendations for tourist attractions from various sources such as the internet, magazines, newspapers, or travel agencies. Because there is numerous information, tourists become difficult to determine the tourism destination that suits their wishes. We created a tourism recommender system that can provide information in the form of recommendations for tourist attractions by the preference of tourists. The method used is a hybrid method that combines several recommendation methods, which are Content-Based Filtering (CB) and Collaborative Filtering (CF). We use tourism data of Lombok Island, West Nusa Tenggara, which will be taken from the TripAdvisor site. We apply the Singular Value Decomposition algorithm on CF and CB. The Hybrid Weighted Parallel Technique is used for Hybrid Method. The results of the experiment show that the weighting technique hybrid method provides higher prediction accuracy than when undergoing the recommender system method separately. The average results of Mean Square Error were obtained 0.7275 (CF), 0 .4583 (CB), and 0.2548 (Hybrid Method). The result indicates that the Hybrid Method with the Weighting Technique has the highest accuracy of another method.]]>
<![CDATA[Classification Model of Consumer Question about Motorbike Problems by Using Naïve Bayes and Support Vector Machine ]]>
<![CDATA[Wicaksana, Ekky]]>;
<![CDATA[Murdiansyah, Danang Triantoro]]>;
<![CDATA[Kurniawan, Isman]]>
<![CDATA[ Indonesian Journal on Computing (Indo-JC) Vol. 6 No. 2 (2021): September, 2021 ]]>
Publisher : <![CDATA[School of Computing, Telkom University ]]>
Show Abstract
|
Download Original
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Original Source
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Check in Google Scholar
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DOI: 10.34818/INDOJC.2021.6.2.561
<![CDATA[The motorbike plays an important role in supporting daily activity. The motorbike is known as one of the transportation modes that is frequently used in Indonesia. The number of motorbikes used in Indonesia is continuously increasing time by time. Hence, the occurrence of motorbike problems can affect community activity and disturb the economic condition in society. Since the problem of the motorbike can occur at any time, a prevention action is required by providing an online consultation platform. However, a classification model is required to handle a wide range of questions about the motorbike problem. By classifying those questions into a specific class of problems, the solution can be delivered to the consumer faster. In this study, we developed prediction models to classify consumer questions. The data set was collected from consumer questions regarding motorbike problems that are commonly occurring. The model was developed using two machine learning algorithms, i.e., Naïve Bayes and Support Vector Machine (SVM). Text vectorization was performed by using the n-gram and term frequency-inverse document frequency (TF-IDF) method. The results show that the SVM model with the uni-trigram model performs better with the value of accuracy and F-measure, which are 0.910 and 0.910, respectively.]]>
<![CDATA[Information Technology Governance Audit Using the COBIT 5 Framework (Case Study of PDAM Tirta Patriot Kota Bekasi) ]]>
<![CDATA[Lisda Awalia Aprilianti]]>;
<![CDATA[Darwiyanto, Eko]]>;
<![CDATA[Arie, Yanuar Firdaus]]>
<![CDATA[ Indonesian Journal on Computing (Indo-JC) Vol. 6 No. 2 (2021): September, 2021 ]]>
Publisher : <![CDATA[School of Computing, Telkom University ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.34818/INDOJC.2021.6.2.563
<![CDATA[PDAM Tirta Patriot has implemented information systems for its business process but still has deficiencies, including some business processes that do not have documented guidelines and procedures. Furthermore, the human resources in PDAM Tirta Patriot are insufficient for improving IT governance due to the lack of reliable personnel in the IT unit. Given the importance of IT for PDAM, an audit is needed to evaluate the capability of the IT unit in managing IT. COBIT 5 provides a goals cascade to align the company with its business goals. However, the goals cascade does not provide priority to IT-related goals. Therefore, for prioritizing IT-related goals, this research uses Analytical Hierarchy Process (AHP). From the AHP result, the selected domains are APO01, MEA01, and APO07. This research aims to determine the current capability level and analyze the gap between it and the chosen target capability level, precisely level 2. The current capability level of PDAM Tirta Patriot from domain APO01 is 1, MEA01 is 0, and APO07 is 0, which means none of those have reached the target capability level. Recommendations are given based on the unfulfilled work product for domains that do not reach the target capability level.]]>
<![CDATA[Forecasting Number of New Cases Daily COVID-19 in Central Java Province Using Exponential Smoothing Holt-Winters ]]>
<![CDATA[Irandi, Dinda Fitri]]>;
<![CDATA[Rohmawati, Aniq Atiqi]]>;
<![CDATA[Gunawan, Putu Harry]]>
<![CDATA[ Indonesian Journal on Computing (Indo-JC) Vol. 6 No. 2 (2021): September, 2021 ]]>
Publisher : <![CDATA[School of Computing, Telkom University ]]>
Show Abstract
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Download Original
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DOI: 10.34818/INDOJC.2021.6.2.565
<![CDATA[There is hard to mention how long the COVID-19 pandemic will discontinue. There are some factors, including the public’s efforts to slow spread and researchers’ work to observe more about this outbreak. From the beginning of the health crisis, particularly following the announcement of the first positive case In Indonesia due to the COVID-19 on March 2, 2020. Afterwards, the number of daily cases increase simultaneously in other regions in Indonesia until today. Due to the fact that the significant mobility of the people, Central Java has contributed the 3rd rank of potential number of COVID-19 positive cases in Indonesia. This study aims to forecast the number of COVID-19 daily new cases in Central Java to assist the government in preparing the necessary resources and controlling the spread of the COVID-19 virus in Central Java Province. We proposed Exponential Smoothing Holt-Winters with the Additive model with seasonal addition considering trend and seasonal factors. The dataset during March 14 to April 17, 2021, revealed fluctuation of trend and seasonal patterns. Our simulation studies indicate that Exponential Smoothing Holt-Winters provides sharp and well performance for forecasting daily new cases of COVID-19 in Central Java province with MAPE less than 10%.]]>
<![CDATA[Multi Criteria Recommender System for Music using K-Nearest Neighbors and Weighted Product Method ]]>
<![CDATA[Nofal, Muhamad Hafidh]]>;
<![CDATA[baizal, zk abdurahman]]>;
<![CDATA[Dharayani, Ramanti]]>
<![CDATA[ Indonesian Journal on Computing (Indo-JC) Vol. 6 No. 2 (2021): September, 2021 ]]>
Publisher : <![CDATA[School of Computing, Telkom University ]]>
Show Abstract
|
Download Original
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Original Source
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Check in Google Scholar
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DOI: 10.34818/INDOJC.2021.6.2.575
<![CDATA[Currently, the music industry has grown rapidly which has led to an information overload that hinders users from finding the music they want, because everyone has their own unique characteristics. In a previous study, the Recommender System converted music lyrics into digital values using Lexicon's Non-Commercial Research (NRC) and K Nearest Neighbors (KNN) to look for similarities between music. However, this system only uses lyrics to recommend music, so it doesn't pay more attention to user preferences. Therefore, in this study adds criteria from users using the Weighted Product Method (WPM) to weight the music criteria with the input criteria from users. In this study uses a music dataset from 2000 to 2019 taken from the Kaggle website. The purpose of this study was to measure user satisfaction using the System Usability Scale (SUS). In this case, the user is free to answer 10 questions regarding the results of the recommendations provided by the system. Based on the results of the questionnaire, the SUS score was 83.65. This score is included in the EXCELLENT category with grade A scale]]>
