Konsep Business Process ReenginEering untuk Memperbaiki Kinerja Bisnis Menjadi Lebih Baik: Studi Kasus Perusahaan Susu Kedelai “XYZ”

Business Process Reengineering is a phase of redesigning business process to improve performance. Business Process Reengineering can be applied to improve micro or medium businesses. One example from them comes from a soymilk company. XYZ Soymilk Company is one of the examples of Small and Medium enterprises with home-industry system. Its organizational structure consists of the director and some divisions. Those divisions, which are run by employees, are: production division, procurement division, finance division, and marketing division. The produced soymilk is packed in plastic bags with Susu Kedelai “XYZ” label on it. This product later is marketed in the canteens of universities, some stores around neighborhoods, and supermarkets. The main market target of this product is university students and people around the location. The promotion is done by attaching promotion flyers on some strategic places. The problem that occurs is a shortage in operational management, the number of command and control in the operating system, as well as recording done still manually. The purpose of using Business Process Reengineering concept processing system is to be more computerized for a better, faster, more accurate, effective and efficient, and improvement in operation management system as an attempt to survive among other competitors. The results of the business process reengineering are some business process ideas

Faktor Bauran Pemasaran Yang Berkontribusi Bagi Konsumen Dalam Memilih Budget Hotel Di Indonesia

Budget hotel menjadi tren dalam dunia perhotelan Indonesia, banyak pengusaha hotel membangun hotel dengan konsep ekonomis, namun seringkali pengusaha budget hotel tersebut mengabaikan apa yang menjadi kebutuhan konsumen sesungguhnya, karena itu peneliti ingin mengetahui faktor apa saja yang berkontribusi bagi konsumen dalam memilih budget hotel di Indonesia. Penelitian ini menemukan empat faktor yang berkontribusi bagi konsumen dalam memilih budget hotel di Indonesia yaitu first impression, hotel's delas, favorable location dan hotel's core product. Diantara keempat faktor tersebut, faktor first impression merupakan faktor dengan kontribusi paling besar

Implementasi Algoritma Dijkstra Dalam Penentuan Jalur Terpendek Di YOGYAKARTA Menggunakan GPS Dan Qt Geolocation

With the development of information technology, the map is no longer in the form of sheet or book. Currently there is a digital map services already invested in mobile devices. Google Maps is one of the leading providers of online digital map which can be accessed using the Application Programming Interface (API) is available using tools such as Qt. Qt is a C + + framework which provides a library to get the location using a GPS device to the library QtGeolocation. By implementing Dijkstra's algorithm, the problem of determining the shortest path towards a desired location of a user's location can be overcome. This study discusses how to implement the algorithm to find the shortest path Djikstra in Yogyakarta-based mobile devices

Prarencana pabrik methyltetrahydrofuran (MTHF) dari levulinic acid (LA) kapasitas produksi : 60.904,404 ton/tahun

MTHF merupakan produk yang dapat digunakan untuk campuran bahan bakar yang dapat diperbaharui. Produk ini belum diproduksi di dalam negeri sehingga memiliki potensi yang cukup besar untuk dikembangkan Proses pembuatan MTHF dari LA ini adalah dengan menggunakan proses hidrogenasi dimana LA dan hidrogen akan direaksikan pada reaktor hidrogenasi pada suhu 221oC dan tekanan 100 bar dengan bantuan katalis Pd-Re/C. Setelah itu, produk yang dihasilkan dialirkan menuju dekanter untuk memisahkan sebagian besar MTHF. Hal ini dilakukan sebelum dilakukan pemurnian MTHF di kolom distilasi sehingga dapat dihasilkan MTHF dengan kemurnian yang tinggi yaitu 99%. Selain itu, pada proses hidrogenasi, dihasilkan produk samping berupa GVL dan pentanol yang cukup banyak sehingga dilakukan proses pemurnian menggunakan kolom distilasi sehingga dapat meningkatkan kemurnian GVL dan pentanol yang masih memiliki nilai jual cukup tinggi di pasaran. Ringkasan penjelasan Pabrik methyltetrahydrofuran (MTHF) dari levulinic acid (LA) dengan kapasitas produksi 60.904,404 ton/tahun adalah sebagai berikut: Bentuk Perusahaan : Perseroan Terbatas (PT) Kapasitas produksi : 60.904,404 ton MTHF / tahun Hari Kerja Efektif : 330 hari/tahun Sistem Operasi : Kontinyu Masa Konstruksi : 2 Tahun Waktu mulai beroperasi : Tahun 2017 Bahan Baku : 101.243.340 kg levulinic acid / tahun Produk • MTHF : 60.904.404 kg/tahun • GVL : 7.745.760 kg/tahun • Pentanol : 6.934.276 kg/tahun Utilitas • Air Pendingin : 10.416.35 m3/hari • Air Sanitasi : 8,78 m3/hari • Listrik terpasang : 438,49 kW • Industrial Diesel Oil : 4,28 m3/tahun • Natural Gas : 16.731.709 m3/tahun Jumlah tenaga kerja : 166 orang Lokasi Pabrik : Jalan Bojonegara, Pulo Ampel, Serang, Banten Luas Pabrik : 27.125 m2 Dari hasil analisa ekonomi yang telah dilakukan didapatkan: • Rate of Return Investment (ROR) sebelum pajak : 19,37 % • Rate of Return Investment (ROR) setelah pajak : 13,82% • Rate of Equity (ROE) sebelum pajak : 32,07% • Rate of Equity (ROE) setelah pajak : 19,05% • Pay Out Time (POT) sebelum pajak : 5 tahun 11 hari • Pay Out Time (POT) setelah pajak : 5 tahun 11 bulan 20 hari • Break Even Point (BEP) : 46,75

Implementasi Deep Learning Menggunakan Metode CNN dan LSTM untuk Menentukan Berita Palsu dalam Bahasa Indonesia

This research aims to implement deep learning techniques to determine fact and fake news in Indonesian language. The methods used are Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). The stages of the research consisted of collecting data, labeling data, preprocessing data, word embedding, splitting data, forming CNN and LSTM models, evaluating, testing new input data and comparing evaluations of the established CNN and LSTM models. The Data are collected from a fact and fake news provider site that is valid, namely TurnbackHoax.id. There are 1786 news used in this study, with 802 fact and 984 fake news. The results indicate that the CNN and LSTM methods were successfully applied to determine fact and fake news in Indonesian language properly. CNN has an accuracy test, precision and recall value of 0.88, while the LSTM model has an accuracy test and precision value of 0.84 and a recall of 0.83. In testing the new data input, all of the predictions obtained by CNN are correct, while the prediction results obtained by LSTM have 1 wrong prediction. Based on the evaluation results and the results of testing the new data input, the model produced by the CNN method is better than the model produced by the LSTM method

Risk factors of severe hypoglycemia among patients with type 2 diabetes mellitus in outpatient clinic of tertiary hospital in Indonesia

Abstract This study aimed to describe risk factors of severe hypoglycemia in type 2 diabetes mellitus (T2DM) patients in a tertiary care hospital in Indonesia. This study was a retrospective cohort study in the Endocrinology Outpatient Clinic of Dr. Cipto Mangunkusumo National General Hospital, Jakarta, Indonesia. All subjects more than 18 years old who had been visiting the clinic for at least a year were included. Subjects were interviewed whether they had any severe hypoglycemia events within the past year, while data on risk factor variables of severe hypoglycemia was taken from medical records one year before data collection. We recruited 291 subjects, among whom 25.4% suffered at least one episode of severe hypoglycemia within one year. History of severe hypoglycemia (OR 5.864, p ≤ 0.001), eGFR less than 60 mL/min/1.73m2 (OR 1.976, p = 0.028), and insulin use (OR 2.257, p = 0.021) were associated with increased risk of severe hypoglycemia. In conclusion, history of previous severe hypoglycemia, eGFR less than 60 mL/min/1.73m2, and insulin use were associated with severe hypoglycemia