360 research outputs found

    Age, Gender, and Muscle Strength: a Study Based on Indonesian Samples

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    Age and gender have been commonly used as a main criterion in accepting a job aplicant, but it is usually not clear how these affect job performance. While a number of recent studies have been done that describe the relationships between age, gender, and participants capacity (e.g., muscle strength), the results have been inconclusive. In Indonesia, in particular, such issues have been rarely investigated, and it is still important to study the issue since the relationships between these factors are population-specific. This study aimed at describing the relationships between age and muscle strength among workers for both genders. Ninety-six male and female workers (aged 18–65) were recruited in this study, and data on handgrip and lower back strength were collected. Findings of this study show that peak hand-grip strength occured at the age of around 35-40 years of age, regardless of gender. Maximum lower back strengh was identified at the age of 31-35 years old (for males) and 26-30 years old (for females). Comparisons between two extreme age groups (18-20 vs. 61-65 years of age) showed a mean strength decline of 50% for hand-grip and 30% for the lower back. For both protocols, female participants tended to have lower muscle strength (70-80% of their male counterparts). Findings of this study can be used as a basis in evaluating physical requirements of a job, and the corresponding factors (age and gender) relevant for the job

    Perancangan Sistem Penulisan Teks pada Running Text Menggunakan SMS

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    – Teknologi yang dinilai efisien digunakan untuk menyampaikan informasi di tempat-tempat umum adalah menggunakan papan running text. Penulisan teks yang akan dikirim ke running text saat ini mengandalkan peranti komputer ataupun remote. Peranti komputer akan dihubungkan dengan kabel ke papan running text sehingga harus tersedia komputer di dekat tampilan running text, sedangkan secara wireless digunakan remote namun memiliki jarak yang terbatas. Dengan memanfaatkan modul GSM sebagai transceiver penulisan teks dari jarak jauh melalui SMS dapat dilakukan. Penulisan teks melalui SMS dapat mendukung penulisan yang lebih efisien terutama untuk menyebarkan informasi yang sama pada beberapa lokasi running text, sehingga penulisan teks tidak lagi harus berada di dekat running text melainkan dapat dilakukan dipusat informasi yang jauh dari letak running text. Penulisan teks pada running text dilakukan melalui SMS dari ponsel, kemudian pesan diterima oleh modul GSM dan diteruskan ke mikrokontroller untuk menampilkan teks pada display running text. Uji coba dilakukan untuk mengukur waktu pengiriman teks sampai tulisan berhasil ditampilkan. Berdasarkan hasil uji coba, waktu pengiriman SMS berbanding lurus dengan jumlah karakter yang dikirimkan. Rata - rata waktu pengiriman teks menggunakan operator yang sama adalah sekitar 28.31 detik dan bila menggunakan operator yang berbeda adalah sekitar 31.20 detik. Sistem penulisan teks akan semakin cepat apabila digunakan operator GSM yang sama pada ponsel dan modul GMS di sisi display running text

    Teknik Jaringan Syaraf Tiruan Feedforward Untuk Prediksi Harga Saham Pada Pasar Modal Indonesia

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    To predict the condition of stock price, several technical analysis models have been used and expanded such as MACD, Fourier Transform, Accumulator Swing Index , Stochastic Oscillator etc. For input they are using the various prices such as Open, high, low , close , volume, BID, ASK price, and the output is a graphic that shows the decision whether to sell, buy or hold. Another method to determine the stock price by using Fundamental Analysis method. Fundamental method is an analysis that is based on the ratio or financial report from the existing company. Neural Network System Technology has been implemented in various applications especially in introduce the pattern. This power has attracted several people to use Neural Network for medical, Finance, Investment and marketing. Assuming that the prediction of the output system (next output prediction) is deterministic, than the suitable N.N model to predict it is Feed Forward. The prediction of the stock price is the complex interaction between unstable market and unknown random processes factor. The data from stock price can be determined by time series. If we have daily data from a certain period, for example : Xt(t = 1,2,...) than the stock price for the next period (t+h) can be predicted (the timing used can be in hourly, daily, weekly, monthly or yearly). To get the good prediction, the inputs from several aspects of the share prices have to be input in Neural Network after that the weighing principal can be adapted to minimize the wrong prediction in the first future steps. By using the final weighing, an action is done to done to minimize the total error in the second future steps. Due to that, the risk of Investor's decision to sell or buy the stock can be minimized. This paper will discuss on how to use and implement Time Series Neural Network to predict the stock market in Semen Gresik (SMGR) and Gudang Garam (GGRM
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