Hereditary Tradition: Analyzing Connections among Detective Depictions in Texts by Poe, Doyle, and King using Harold Bloom’s Revisionary Ratios Theory

There has been a longstanding debate about the origin of detective fiction, with most recognizing Poe as its pioneer. However, there remains a need to comprehensively analyze the literary influence that spans across generations in detective fiction. This research introduces a comprehensive analysis of the literary influence that spans across generations in detective fiction, shedding light on the intricate web of connections between Edgar Allan Poe, Sir Arthur Conan Doyle, and Laurie R. King. Central to this investigation is the application of Harold Bloom’s theory of revisionary ratios, which serves as an invaluable analytical framework. Through the application of Harold Bloom’s theory of revisionary ratios, this research provides a comprehensive exploration of the enduring significance of intertextuality in shaping the detective fiction landscape. It underscores the intricate web of influences that connect Poe’s pioneering works with subsequent narratives by Conan Doyle and King. Having the enduring significance of intertextuality that shapes the detective fiction landscape, this study still offers a novel perspective on the genre’s dynamic evolution. The method involves a detailed review of revisionary ratio concepts and their implications for understanding complex literary works more thoroughly. The result reveals the enduring significance of revisionary ratios in understanding the complexities of literary works, with Edgar Allan Poe’s influence resonating in subsequent detective stories by Sir Arthur Conan Doyle and Laurie R. King

The Case of the Sidekick: The Roles of Dr. John Watson in Sherlock Holmes Canon by Sir Arthur Conan Doyle

sidekick in literature is perceived as a supporter of a hero or a man-behind a hero. However, it does not always work that way. In Sherlock Holmes canon, there can be found a well-known dr. John Watson who acts differently as a sidekick for Sherlock Holmes as a protagonist of the stories. Throughout the canon, Watson does not merely act as a supporter or a man-behind who just follows Holmes’s moves. In many occasions, Watson contributes varied significant things in supporting Holmes through some roles he possesses. Moreover, what Watson contributes is found out to be influential to Holmes. Therefore, it can be seen that being a sidekick can do other things apart from following the hero all the time.Based on the facts about Watson’s contributions, this paper is conducted to examine the roles dr. John Watson as a sidekick. The data used in the research are 56 short stories and four novels of Sherlock Holmes bundled together in Sherlock Holmes canon. The method of collecting the data is executed through intensive reading, mapping out the roles of dr. John Watson found during the reading process, and analysing the collected data.Since the focus of this paper is about dr. John Watson’s roles and their influences towards Sherlock Holmes, objective theory is chosen to be employed. Related to the theory, this paper offers the explanation of intrinsic elements with focus on character element and sidekick character

Prediction of Rupiah Against US Dollar by Using ARIMA

The currency exchanges rate is one of the most important things in the economy. The currency exchange rate is needed in the business word for example, investment and profit assessment. Prediction of rupiah rate is done to get the price of the rupiah against US dollar in the future to be used as consideration in decision-making, thereby reducing the risk of loss. Therefore, we need a method that can help in making business decisions about when to make the right trades with a high degree of accuracy. This study aims to predict the value of rupiah against US dollar by using ARIMA (Autoregressive Integrated Moving Average). This study uses four stages, including (1) the preparation of the dataset, (2) preprocessing of data, (3) the use of ARIMA models, (4) test accuracy. The data used for the test is the data rate from January 4th 2010 until June 24th 2016. The result showed that ARIMA method has an accuracy rate of 98.74%. Based on the result, it can be concluded that the development of the predictive value of the rupiah against the US dollar using ARIMA method was accurate to use

Perbandingan Metode Prediksi pada Bidang Bisnis dan Keuangan

Pada era globalisasi ini peran teknologi telah merambah ke berbagai bidang seperti di bidang bisnis dan keuangan. Ekonomi dunia yang selalu berubah-ubah menuntut para investor dan pebisnis untuk dapat mengambil keputusan tepat dan cepat. Peran teknologi diperlukan untuk menghadapi perubahan-perubahan yang terjadi sehingga dapat meminimalisir kekhawatiran investor akan kerugian yang akan dialami. Oleh karena itu, diperlukan suatu pemanfaatan teknologi untuk memprediksi perubahan-perubahan yang akan terjadi dikemudian hari. Salah satu teknologi yang dapat dimanfaatkan adalah dengan menggunakan teknik dan metode data mining. Metode ini memungkinkan untuk melakukan prediksi berdasarkan data sebelumnya pada periode waktu tertentu. Usaha untuk mendapatkan hasil prediksi yang akurat masih terus dilakukan. Maka dari itu perlu adanya pengetahuan mengenai berbagai macam metode yang digunakan dalam prediksi untuk dapat menentukan metode yang tepat dari berbagai kasus dan menghasilkan hasil yang akurat

Penggunaan Metode ARIMA untuk Prediksi Jumlah Penumpang Kereta Api Kota Malang

Saat ini kereta api telah menjadi salah satu transportasi yang diminati oleh masyarakat untuk menempuh perjalanan jarak menengah dan jauh terutama di saat masa liburan. Pada masa liburan jumlah penumpang kereta api sulit untuk diperkirakan. Hal tersebut dapat mengakibatkan adanya lonjakan jumlah penumpang yang mengharuskan pihak PT. KAI (Persero) mengambil tindakan dengan menambahkan keberangkatan kereta api. Untuk mengantisipasi lonjakan penumpang perlu dilakukan prediksi jumlah penumpang. Dengan memanfaat teknologi untuk mengenali pola trend perubahan jumlah penumpang di setiap harinya, maka diharapkan dapat diketahui jumlah penumpang yang akan datang sehingga PT. KAI mampu melakukan upaya dengan mempersiapkan jumlah armada yang akan dibutuhkan. Penelitian ini melakukan prediksi menggunakan metode ARIMA yang mampu menghasilkan tingkat akurasi tinggi dalam peramalan jangka pendek serta mampu menghadapi fluktuasi data musiman. Penelitian ini diharapkan mampu menghasilkan tingkat akurasi tinggi dan dapat menjadi salah satu sumber informasi maupun rujukan dalam mengatasi adanya lonjakan penumpang kereta api di Kota Malang.