1 10 26 https://repository.horizon.ac.id/files/original/ef0c6e96f064817ef6890919e96ec2b7.pdf 5edc41c0cad5ef3e8b92af2949fc9873 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 6 NO 6 (2022) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Heart Attack Notification and Monitoring System Using Internet of Things Subject The topic of the resource heart attack, notification system, monitoring system, IoT, internet of things Description An account of the resource People are frequently shocked when someone passes away suddenly without any prior symptoms. One of the contributing factors is a heart attack. This condition might occur anywhere and at any time. A sudden heart attack can be highly perilous for a person who is alone, without family members or friends because the family cannot be informed of the victim's condition or their location. Therefore, it is vital to raise awareness of heart attacks. With the support of the Internet of Things, this study aims to develop a wearable device that people may use to monitor their heart health and connect with hospitals to get alerts in case of a heart attack. This system also provides family members with access to a web-based patient monitoring tool. The heart beat is considered as the parameter in developing this system. There are three types of evaluation which are conducted in this study, namely: 1) Sub-system evaluation; 2) Black-box testing; and 3) Integrating system testing. The three evaluation results show that all assembled hardware components are work properly and the system effectively satisfies the objectives of monitoring, buzzer activation, hospital and patient family notification, and so forth, with 1.96% average sensor error, which is still considerably acceptable. Creator An entity primarily responsible for making the resource 1*Maya Fitria, 2Ramzi Adriman, 3 Irham Muhammaddin Batubara, 4Akhyar Bintang Publisher An entity responsible for making the resource available Universitas Syiah Kuala Date A point or period of time associated with an event in the lifecycle of the resource 29-12-2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/49cdcf9fe2dd75e49761fcf7f79eee2c.pdf 7225549e2ab4d1ca90547ab056fe49e9 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 6 NO 6 (2022) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Comparison of the Smoothing Constant Values Among Exponential Smoothing Methods in Commodity Prices Forecasting Subject The topic of the resource forecasting, smoothing constant, exponential smoothing, B-DES, SES. Description An account of the resource Commodity prices forecasting is one of the business functions to estimate future demand based on past data trend. This study aims to implement a trial and error technique of the constant (alpha α) value in the exponential smoothing method. Dealing with confusion that often researchers find in selecting an alpha (α) value among exponential smoothing families, which suits characteristics of the investigated case. As selection of the constant value precisely contributes to reduce the forecasting deviation. This paper used the alpha (α) value in the range 0,1 to 0,9 and utilized the mean absolute percentage error (MAPE) and Mean Absolute Error (MAE) as the parameter to know the grade of prediction. In data training, the authors used Single Exponential Smoothing (SES) and Brown’s Double Exponential Smoothing (B-DES) as methods to compare the results of prediction. It is addressed that forecasting with alpha (α) 0,1 is the most optimal values for Single Exponential Smoothing (SES) in this case with margin error 0,00036 of MAPE and 16,84 of MAE Creator An entity primarily responsible for making the resource 1Hazriani, 2Yuyun, 3Mashur Razak Publisher An entity responsible for making the resource available Handayani University Date A point or period of time associated with an event in the lifecycle of the resource 29-12-2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/fda821be6830a24146f8d921ac58d305.pdf 856cf1c8dc005c7b4e581742b8693862 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 6 NO 6 (2022) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource UI/UX Analysis and Design Development of Less-ON Digital Startup Prototype by Using Lean UX Subject The topic of the resource UI/UX, Lean UX, SUS, Prototype, Less-ON; Description An account of the resource The growth of startups in Indonesia continues to experience upward growth. Behind the growth that continues to move up, there is a success rate statistic which is a contradiction behind its development. The startup statistics show that about 90% of startups fail. As many as 75% of unicorn startups believe that a good UI/UX design can increase startup valuations and additional investors' funds. User Interface (UI) and User Experience (UX) are closely related because UX results from UI interactions. Less-On is a provider of private tutoring service providers who serve as an intermediary bridge between teachers and students. This research will be carried out by integrating the processes in the Lean UX method into every process that exists at the stages of software engineering development. The results obtained from this study are a final prototype validated in terms of criticism and suggestions through a questionnaire as a form of Less-On branding. Positive UX and better usability are significant for further development of the prototype private tutor booking application, which plays a vital role in acceptance, satisfaction and efficiency in using this Less-ON application. The UI has good usability for users, with a SUS scoring earn 85.53, which is above average and acceptable. Creator An entity primarily responsible for making the resource 1Rio Andika Malik, 2Marta Riri Frimadani Publisher An entity responsible for making the resource available University of Perintis Indonesia Date A point or period of time associated with an event in the lifecycle of the resource 29-12-2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/5a7355a897a66c50a6f483967fe8e7e6.pdf 6421edf7762c55882c6a39e0e70f0c21 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 6 NO 6 (2022) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Brain Tumor Classification for MR Images Using Transfer Learning and EfficientNetB3 Subject The topic of the resource Brain Tumor Classification, Convolutional Neural Network, EfficientNet, Transfer learning Description An account of the resource Brain tumors are one of the diseases that take many lives in the world, moreover, brain tumors have various types. In the medical world, it has an technology called Magnetic Resonance Imaging (MRI) which functions to see the inside of the human body using a magnetic field. CNN is designed to determine features adaptively using backpropagation by applying layers such as convolutional layers, and pooling layers. This study aims to optimize and increase the accuracy of the classification of brain tumor MRI images using the Convolutional Neural Network (CNN) EfficientNet model. The proposed system consists of two main steps. First, preprocessing images using various methods then classifying images that have been preprocessed using CNN. This study used 3064 images containing three types of brain tumors (gliomata, meningiomas, and pituitary). This study resulted in an accuracy of 98.00%, a precision of 96.00%, and an average recall of 97.00% using the model that the researcher applied. Creator An entity primarily responsible for making the resource Ahmad Darman Huri1 , Rizal Arya Suseno2 , Yufis Azhar3 Publisher An entity responsible for making the resource available University of Muhammadiyah Malang Date A point or period of time associated with an event in the lifecycle of the resource 29-12-2022 Contributor An entity responsible for making contributions to the resource Fajar Bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/dc381d8efbf4435da2ce21a36d24f642.pdf 2a23bc1dc1ba57dad40f184576e57a60 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 6 NO 6 (2022) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Digital Forensic on Secure Digital High Capacity using DFRWS Method Subject The topic of the resource Digital forensic, sdhc, dfrws, linux, foremost, dc3dd Description An account of the resource As evidenced in the trial, between 2015 and the second quarter of 2022, there were 54 cases involving secure digital high capacity (SDHC) storage hardware as evidenced in trials. In 2021 there will be an increase in cases involving SDHC. The three cases with the highest number are corruption cases, special crimes, and ITE. SDHC is an advanced technology development of Secure Digital (SD) card hardware which functions as storage. SD Card only has a capacity of up to 2 gigabytes, while the largest SDHC capacity is 32 gigabytes. As a storage device that is small, thin, and has a fairly large capacity. this research needs to be done because of the increasingly widespread increase in cases involving SDHC. This study aims to perform digital forensic analysis on SDHC evidence using forensic applications that run on Linux, namely foremost and DC3DD. This study uses the DFRWS method to retrieve valid evidence in court. Based on the research conducted, it was found that the number of files that can be restored at the examination stage using foremost is 77%, and the accuracy of recovered files is 50% with string file hash validation. From this research, it can be concluded that the processing results of DC3DD and Foremost can be used as valid evidence. Creator An entity primarily responsible for making the resource Anton Yudhana1 , Imam Riadi2 , Budi Putra3 Publisher An entity responsible for making the resource available Universitas Ahmad Dahlan Date A point or period of time associated with an event in the lifecycle of the resource 29-12-2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/605d91eea252d79dfffe0e15facf0225.pdf d81eb95a93fb20feaaab552fe7049e1b Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 6 NO 6 (2022) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Measuring the effect of Users' Privacy Concerns on the Use of Jakarta Smart City Mobile Application (JAKI) Subject The topic of the resource smart city, Jakarta, mobile application, privacy concern Description An account of the resource akarta Kini (JAKI) is a super-app developed by Jakarta Smart City that offers a one-stop service to help citizens connect and communicate with the Government. It is undeniable that the use of mobile applications can indeed facilitate people's activities, but on the other hand, it also poses risks and raises concerns in terms of privacy. The purpose of this study is to assess the impact of users' privacy concerns on their tendency to use the JAKI mobile application. To measure the privacy concern, we conduct an online survey of the users of JAKI. The hypothesis and research model were formulated to assess the users' privacy concerns based on the Mobile Users' Information Privacy Concerns (MUIPC) theory, with additional factors, namely prior privacy experience and awareness, as the antecedents. As a result, we found that MUIPC had a significant effect on negatively influencing the intention to use the JAKI application. Our study contributes as a starting point in exploring privacy research in the context of a smart city in Indonesia. Additionally, this study proved that the IPC scales that were originally designed for English-based countries could also be adapted to Bahasa Indonesia and utilized in the Indonesian context. Creator An entity primarily responsible for making the resource Arif Wahyudi, 2Mirza Triyuna Putra, 3Dana Indra Sensuse, 4Sofian Lusa, 5Prasetyo Adi, 6Assaf Arief Publisher An entity responsible for making the resource available Universitas Indonesia Date A point or period of time associated with an event in the lifecycle of the resource : 29-12-2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/3b663fda433792fc932324dfaf4eea75.pdf 41a6f428b306d68e09acbc2a23cfe20e Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 6 NO 6 (2022) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Naïve Bayes-Support Vector Machine Combined BERT to Classified Big Five Personality on Twitter Subject The topic of the resource BERT, Big Five Personality, LIWC, Naïve Bayes-Support Vector Machine Description An account of the resource Twitter is one of the most popular social media used to interact online. Through Twitter, a person's personality can be determined based on that person's thoughts, feelings, and behavior patterns. A person has five main personalities likes Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. This study will make five personality predictions using the Naïve Bayes method – Support Vector Machine, Synthetic Minority Over Sampling Technique (SMOTE), Linguistic Inquiry Word Count (LIWC), and Bidirectional Encoder from Transformers Representations (BERT). A questionnaire was distributed to people who used Twitter to collect and become a dataset in this research. The dataset obtained will be processed into SMOTE to balance the data. Linguistic Inquiry Word Count is used as a linguistic feature and BERT will be used as a semantic approach. The Naïve Bayes method is used to perform the weighting and the Support Vector Machine is used to classify Big Five Personalities. To help improve accuracy, the Optuna Hyperparameter Tuning method will be added to the Naïve Bayes Support Vector Machine model. This study has an accuracy of 87.82% from the results of combining SMOTE, BERT, LIWC, and Tuning where the accuracy increases from the baseline Creator An entity primarily responsible for making the resource Billy Anthony Christian Martani1 , Erwin Budi Setiawan2 Publisher An entity responsible for making the resource available Telkom University Date A point or period of time associated with an event in the lifecycle of the resource 30-04-2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/4c9fde09c6fe1ea575941fa172630adb.pdf b81f3879b7f5a3128e8ac0a2f750d3a9 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 6 NO 6 (2022) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Indonesian Crude Oil Price (ICP) Prediction Using Multiple Linear Regression Algorithm Subject The topic of the resource crude oil, ICP, time series, prediction, linear regression Description An account of the resource Crude oil prices play a significant role in the global economy, therefore accurate prediction of oil prices is very important. Therefore, a forecasting model is needed to predict Crude Oil Prices. The purpose of this study is to forecast the price of crude oil from Indonesia (ICP). The data source is from a website published by the Ministry of Energy and Mineral Resources (ESDM), namely monthly crude oil price data specifically for six main types of crude oil: SLC, Attaka, Duri, Belida, Banyu and SC. The data used is data for a period of 5 years (2018 – 2022). The data available is in the form of time series data. Dated Brent combined with the Alpha factor for each month and year is a reference in determining the ICP price. Forecasting Indonesian crude oil prices in the future is based on the historical oil price of the previous period. The Data Mining algorithm used for forecasting is Multiple Linear Regression. The dataset processed using training data is 80%, and testing data is 20%. The model produced, on average, has a good level of accuracy in calculating MAPE where for SLC = 9%, Attaka = 45%, Duri = 126%, Belida = 33%, Banyu = 150% and SC = 50%. Based on the MAPE calculation value, the Linear Regression Equation to predict Indonesian Crude Oil Prices (ICP) shows that the model produced by SLC crude oil is very good. Attaka, Belida and SC crude oil yielded fair yields and Duri and Banyu crude oil yielded poor yields. Creator An entity primarily responsible for making the resource Des Suryani1 , Mutia Fadhilla2 , Ause Labellapansa3 Publisher An entity responsible for making the resource available University of Islam Riau Date A point or period of time associated with an event in the lifecycle of the resource 30-12-2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/a14251b5e05f710263c0e23d4addbc84.pdf ac363689c49f0ec3e36c85be5db35649 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 6 NO 6 (2022) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faux Insider Hazard Investigation on Non-Public Cloud Computing by Using ADAM’s Technique Subject The topic of the resource Cloud, MITC, Forensics, ADAM, Analysis Description An account of the resource Cloud computing is a service system mechanism that businesses and organizations use to perform computerized and integrated transactions over computer networks. The service system must, of course, be”matched”with a”certain amount”of security. It is applied to” forecast the probability of cybercrime. A Cloud Service Provider (CSP) often offers cloud-based services with a basic level of security. Typically, CSPs are set up to offer their services on the open internet. Data security-focused organizations strive to shield their systems from a wide range of attackers. One of the alternatives is to construct a private cloud computing system. The issue is the potential for Man in the Cloud (MITC) assaults, which compromise and modify identities and are identified in cloud systems as phony insider threats. Based on the ISO 27032 standard research, the goal of this work is to undertake a threat analysis of MITC attack methodologies against private cloud computing services. With regards to risks to cloud services in a private cloud computing environment, it is intended that reporting and documenting the study' findings would lead to suggestions for more research and cybersecurity management procedures Creator An entity primarily responsible for making the resource Dwi Kurnia Wibowo1 , Ahmad Luthfi2 , Yudi Prayudi3 , Erika Ramadhani4 , Muhamad Maulana5 Publisher An entity responsible for making the resource available Indonesian Islamic University Date A point or period of time associated with an event in the lifecycle of the resource : 29-12-2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text https://repository.horizon.ac.id/files/original/38f0b07e5336c9d209935bb2df116244.pdf afd5958bdc8a98a21b690e1e1452263e Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource VOL 6 NO 6 (2022) Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Fire Detection on Video Using ViBe Algorithm and LBP-TOP Subject The topic of the resource fire detection, ViBe algorithm, local binary pattern-three orthogonal planes, support vector machine Description An account of the resource In this research, we built a system to detect fire using the ViBe (Visual Background Extractor) algorithm to extract dynamic targets. The ViBe algorithm is better at detecting moving target objects such as flame combustion. In this research we combined the ViBe algorithm with three frame differencing to gain better results on movement object. The HSI color space model was applied after the movement object was obtained. We used Local Binary Pattern-Three Orthogonal Planes to obtain the feature extraction to be classified with Support Vector Machine. Our result has shown that the proposed system were able to detect the fire using the LBP-TOP and ViBe algorithm methods with an average accuracy rate of 88.10%, and the best accuracy was 90.37%. The parameters used to achieve this accuracy in the feature extraction process were T=120, Radius=2, and frame gap=15, then the threshold value parameter for three-frame difference parameter was 25. Creator An entity primarily responsible for making the resource Febryanti Sthevanie1 , Gamma Kosala2 , Kurniawan Nur Ramadhani3 , Ketut Sudyatmika Putra4 Publisher An entity responsible for making the resource available Telkom University Date A point or period of time associated with an event in the lifecycle of the resource 27-12-2022 Contributor An entity responsible for making contributions to the resource Fajar bagus W Format The file format, physical medium, or dimensions of the resource PDF Language A language of the resource Indonesia Type The nature or genre of the resource Text