Prediksi Komoditas Pangan Pada Masa Pandemi Dengan Metode Forecasting dan Moving Average

Proses mencari pola atau informasi yang berguna pada kumpulan data dengan menerapkan metode tertentu di dalamnya. Untuk memprediksi suatu harga dikemudian hari dalam penelitian ini penulis melakukan pengolahan data pada komoditas pangan yang di dalamnya terdiri dari beberapa variable. Prediksi tersebut tentunya dapat memberikan suatu informasi yang komperhensif kepada seseorang yang membutuhkan informasi mengenai harga dikemudian harinya. Dalam masa pandemi seperti sekarang ini komoditas pangan sudah menjadi kebutuhan pokok yang memang harus dipenuhi, dengan ketersediaan histori data yang diporelah dapat di olah menggunakan beberapa metode, antara lain metode forecasting dan metode moving average, serta menggunakan beberapa literatur terkait yang mengacu pada penelitian-penelitian sebelumnya. Pada penelitian ini untuk pengambilan data didapat dari sumber portal web yang sangat komperhensif dan selalu memberikan data dari hari ke harinya. Dengan menerapkan pendekatan dengan kedua metode tersebut dari sebuah history data yang sudah ada, maka akan di dapatkan sebuah nilai, dimana nilai tersebut dapat menjadi prediksi untuk kedepannya. Nilai tersebut berupa harga dari setiap variable komoditas pangan. Hasil dari kedua metode ini mempu memberikan prediksi harga di setiap komoditas pangan, hal tersebut tentunya akan diperlukan oleh masyarakat umum terlebih lagi sebagai salah satu bentuk strategi guna menjaga kestabilan dan memantau perkembangan harga pangan.

Examining the cohesiveness and nestedness entrepreneurial ecosystems: evidence from British FinTechs

It is not clear if entrepreneurial ecosystems are cohesive wholes within a region that support high-growth entrepreneurship across a variety of sectors or if ecosystems are made up of several, nested sectoral-specific sub-ecosystems. This debate speaks to larger disagreements about what entrepreneurial ecosystems are and how they work. This paper addresses this research gap by using a novel methodology based on career history data of founders and top management teams of high-growth FinTech ventures. This method is used to classify the backgrounds of 1,570 individuals in 380 British FinTech firms based on their prior job histories and employers into categories such as technology or finance. The paper finds substantial evidence of nestedness in the ecosystems, but rather than FinTech ecosystems being specialized finance or technology clusters, more generic forms of managerial know-how remain crucial to firm innovation and growth. This suggests that even very advanced ecosystems remain nested, with few cross-over points between different communities.

Clustering History Data Penjualan Menggunakan Algoritma K-Means

Perusahaan memiliki keinginan dalam mengembangkan peningkatan usahanya agar tidak tergerus dalam persaingan bisnis yang sangat ketat. PT. Baliyoni Saguna merupakan sebuah perusahaan yang bergerak dalam bidang teknologi informasi dan telekomunikasi yang saat ini sudah banyak membantu pelanggannya dalam memberikan solusi-solusi terbaik sesuai dengan kebutuhan pelanggannya. Kualitas produk menjadi faktor utama dalam menjaga agar pelanggan bisa bertahan dan merasa puas dari produk-produk yang diberikan oleh PT. Baliyoni Saguna. Produk-produk tersebut perlu dikaji kembali agar memiliki acuan dalam menciptakan produk terbaik. Clustering merupakan sebuah metode yang bisa digunakan dalam melihat tingkat penjualan yang telah dilakukan berdasarkan cluster yang terbentuk. Algoritma K-Means menjadi metode yang mampu mengolah history data penjualan yang dimiliki PT. Baliyoni Saguna dalam membentuk kelompok-kelompok sesuai dengan kategori item barang tersebut. Algoritma K-Means mampu memberikan kemudahan dalam mengolah data yang besar sehingga dapat diolah lebih cepat dan efisien. Hasil dari penerapan algortima K-Means, membentuk 3 cluster yang mewakili kategori sangat diminati, diminati dan kurang diminati. Pada kategori sangat diminati terdapat 5 jumlah item barang, kategori diminati terdapat 4 jumlah item barang dan kurang diminati terdapat 14 jumlah item barang. Hasil tersebut diharapkan dapat membantu dalam menciptakan barang yang berkualitas sehingga dapat menjaga kulitas produk serta kepuasan dari pelanggan. Kata Kunci— Clustering, Algoritma K-Means, PT. Baliyoni Saguna.

First Successful Run of 17.5 Inch Hybrid Bit in ADNOC Onshore to Drill Deviated Section

In the onshore drilling operation the main objective is always finding ways to optimize cost and improve the efficiency of drilling operations. Among the various available option, one possibility was to drill 17.5" deviated section in one run through the interbedded formation, which cause high vibrations and risk of twist-off. This section previously was drilled with minimum 2-3 bit runs for a heavy casing design. This would definitely reduce the well duration and cost. The plan involved to drill 17.5" deviated section using rotary steerable system using hybrid bit technology. Recent advances in drilling bit design has proved to be very effective in drilling surface hole sections but are limited to drill vertical holes and require multiple runs to complete a section. Special design and cutting structure is required when it comes to drill deviated hole. One supplier has combined the traditional design and come up with hybrid bit structure to achieve this goal of drilling surface deviated hole in one run. This special hybrid bit, drilled successfully 17.5" deviated section in one run with enhanced ROP by 40% compared to previous wells. This saved additional trips to change bit and avoided any stuck pipe and twist off. This kind of strategy has helped to maximize average ROP of 64 ft/hr for the entire section. The main element in optimizing the performance of is the systematic approach towards the bit selection, hydraulics and mud parameters. Outcome of this optimization resulted in case history data which shows that this kind of hybrid bit technology can be used to drill deviated wellbore with better penetration rates, lesser washouts and longer on-bottom time. This technical paper describes the results of first well drilled by a service provider using hybrid bit technology with rotary steerable system in one run. This has resulted in increasing the rate of penetration for the 17.5" deviated top hole section. Applying this kind of hybrid bit technology has not only enhanced the ROP but also helped to save rig days and cost.

An annotated catalogue of bird lice (Insecta: Phthiraptera) from Chile

The species and subspecies of chewing lice (Insecta: Phthiraptera: Amblycera, Ischnocera) parasitic on Chilean birds are listed and annotated, based on records published until October 2021 and from our examination of collections. The current scientific name, its taxonomic history, data on type material, type host, other hosts, geographic distribution within Chile and elsewhere, Chilean literature references and other significant references are given for each species or subspecies of lice. A total of four families, 76 genera, and 245 species and subspecies of lice are listed, including 17 species recorded as genus only, and 31 new records of species. A host-louse list—including a total of 155 bird species (146 native and nine introduced by human agency) belonging to 19 orders, 43 families and 107 genera—is also given.

"An appanage prince of a pattern of developed socialism has emerged". The interests of the ruling regional elites of the USSR in the later 20th c.

В статье реконструируются интересы правящих региональных элит СССР конца 1960-х – 1980-х гг. Анализируются связи и противоречия в описании интересов региональных элит. Корпус источников составили впервые вводимые в научный оборот документы фонда (Ф. 100) РГАНИ; мемуары; данные устной истории. Были проанализированы основные виды властных интересов, включая установление личных неформальных контактов. Была выявлена структура интересов региональной власти в позднем СССР, включавшая декларируемые и скрытые интересы. The article reconstructs the interests of the ruling regional elites of the USSR in the late 1960s - first half of the 1980s. The relations and contradictions in the description of the interests of regional elites are analyzed. The corpus of research sources was made up of archival documents, the documents of the foundation (F.100) of the Russian State Institute of Scientific Research and Entrepreneurship; memoirs; oral history data obtained during interviews. The main types of power interests, including the establishment of personal informal contacts, were analyzed and systematized. The study revealed the structure of the interests of regional authorities in the late USSR, which included 2 interconnected blocks - declared and hidden interests.

Pemanfaatan Data Mining Dalam Memprediksi Produksi Pada PT Pupuk Sriwidjaja Palembang Menggunakan Algoritma Regresi Liniear Berganda

PT.Pupuk Sriwidjaja Palembang is a company that has the main task in the production and marketing of urea fertilizer and npk fertilizer. Production estimates are needed so that companies can determine strategies and breathrought so that the production process runs optimally. This study discusses the application of data mining in predicting the production of NPK Fertilizer Formula 15-15-15 PSO at PT.Pupuk Sriwidjaja Palembang. In its application, this research uses the multiple Linear Regression Algorithm by utilizing production history data for the 2019-2020 period. If you have already mined the production history data for the 2019-2020 period, there will bi predictions in 2021 which are predicted by the rapidminer application and using a multiple linear regression algorithm, which produces a predicted value of fertilizer production in 2021 as much as 70800 tons.

Privacy of study participants in open-access Health and Demographic Surveillance System data: A requirements analysis for data anonymisation (Preprint)

BACKGROUND Sharing and anonymising data have become hot topics for individuals, organisations, and countries around the world. Open-access sharing of anonymised data containing sensitive information about individuals makes the most sense whenever the utility of the data can be preserved and the risk of disclosure can be kept below acceptable levels. In this case, researchers can use the data without access restrictions and limitations. OBJECTIVE The goal of this paper is to highlight solutions and requirements for sharing longitudinal health and surveillance event history data in form of open-access data. The challenges lie in the anonymisation of multiple event dates and the time-varying variables. A sequential approach that adds noise to the event dates is proposed. This approach maintains the event order and preserves the average time between events. Additionally, a nosy neighbor distance-based matching approach to estimate the risk is proposed. Regarding dealing with the key variables that change over time such as educational level or occupation, we make two proposals, one based on limiting the intermediate status of a person (e.g. on education), and the other to achieve k-anonymity in subsets of the data. The proposed approaches were applied to the Karonga Health and Demographic Surveillance System (HDSS) core dataset, which contains longitudinal data from 1995 to the end of 2016 and includes 280,381 event records with time-varying, socio-economic variables and demographic information on individuals. The proposed anonymisation strategy lowers the risk of disclosure to acceptable levels thus allowing sharing of the data. METHODS statistical disclosure control, k-anonymity, adding noise, disclosure risk measurement, event history data anonymization, longitudinal data anonymization, data utility by visual comparisons. RESULTS Anonymized version of event history data including longitudinal information on individuals over time with high data utility. CONCLUSIONS The proposed anonymisation of study participants in event history data including static and time-varying status variables, specifically applied to longitudinal health and demographic surveillance system data, led to an anonymized data set with very low disclosure risk and high data utility ready to be shared to the public in form of an open-access data set. Different level of noise for event history dates were evaluated for disclosure risk and data utility. It turned out that high utility had been achieved even with the highest level of noise. Details matters to ensure consistency/credibility. Most important, the sequential noise approach presented in this paper maintains the event order. It has been shown that not even the event order is preserved but also the time between events is well maintained in comparison to the original data. We also proposed an anonymization strategy to handle the information of time-varying status of educational, occupational level of a person, year of death, year of birth, and number of events of a person. We proposed an approach that preserves the data utility well but limit the number of educational and occupational levels of a person. Using distance-based neighborhood matching we simulated an attack under a nosy neighbor situation and by using a worst-case scenario where attackers has full information on the original data. It could be shown that the disclosure risk is very low even by assuming that the attacker’s data base and information is optimal. The HDSS and medical science research communities in LMIC settings will be the primary beneficiaries of the results and methods presented in this science article, but the results will be useful for anyone working on anonymising longitudinal datasets possibly including also time-varying information and event history data for purposes of sharing. In other words, the proposed approaches can be applied to almost any event history data, and, additionally, to event history data including static and/or status variables that changes its entries in time.