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INDONESIA
Statistika
Published by Universitas Islam Bandung
ISSN : 14115891     EISSN : 25992538     DOI : https://doi.org/10.29313/jstat.v19i2.4898
Core Subject : Economy, Science, Education, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Mathematics
STATISTIKA published by Bandung Islamic University as pouring media and discussion of scientific papers in the field of statistical science and its applications, both in the form of research results, discussion of theory, methodology, computing, and review books.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 42 Documents
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Search results for , issue "Vol 4, No 2 (2004)" : 42 Documents clear
PREDIKSI MOF DAN LOF QUASI REAL TIME PADA SIRKIT KOMUNIKASI MANADO-SUMEDANG Habirun Habirun; Sity Rachyany; Anwar Santoso
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 4, No 2 (2004)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v4i2.881

Abstract

Model prediksi frekuensi komunikasi radio HF (High Frequency) telah banyak dilakukan penelitian terutama yang ditelitiadalah model prediksi MUF (Maximum Usable Frequency) dan LUF (Lowest Useble Frequency) jangka panjang denganberdasarkan median bulanan. Model prediksi MUF dan LUF ini dapat pula dikembangkan hingga model prediksi frekuensikomunikasi HF real time melalui MOF (Maximum Observed Frequency) dan LOF (Lowest Observed Frequency) padasirkit komunikasi dengan jarak tertentu. Sehubungan uraian di atas pada makalah ini dibahas pengembangan modelprediksi frekuensi komunikasi HF melalui model prediksi MOF dan LOF quasi real time yang digunakan pada sirkitkomunikasi Manado – Sumedang, menggunakan model rata-rata dan deviasi standar serta validasi model prediksididukung korelasi pola yang cukup memadai antara data pengamatan MOF dan LOF terhadap hasil prediksi. Dari analisisdata MOF dan LOF diperoleh bahwa prediksi MOF dan LOF quasi real time menggunakan model berbasis statistikberdasarkan model rata-rata, deviasi standar dan didukung autokorelasi yang cukup memadai dengan ditunjukkan masingmasingharga koefisien korelasi pola antara data pengamatan terhadap hasil prediksi sebesar 0,9840 dan 0,9987.
USAGE LOGARITHMIC DISTRIBUTION ON PLANKTON COMMUNITY DIVERSITY IN ARTIFICIAL PONDS Arief Budi Yulianti
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 4, No 2 (2004)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v4i2.871

Abstract

The community is arranged of species, that live at same time and on the same area. The measurement methods ofcommunity diversity depend on number of species and number of individuals in each of these species. The community hasrare species, and rich species. Many species only have single individual, two individuals and so on until only a few specieshave many individuals. These data were best fitted by the logarithmic distribution. The measurement of planktoncommunity diversity, that 100 day old, in artificial ponds, had result, it found 27 species and total individual was 10 811599, so logarithmic index was 0.9999999, and diversity index was 1.0811. The distribution became 1.0811; 0.5404;0.3604; 0.2703; and so on. In the short, the plankton community had many species that had one individual and only few species have many individuals. And Structure of community was influenced by the riches species.
PENDUGAAN SELANG KEPECERCAYAAN KOEFISIEN DETERMINASI Suliadi Suliadi
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 4, No 2 (2004)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v4i2.904

Abstract

Dalam analisis regresi, koefisien determinasi merupakan suatu ukuran yang sangat penting. Koefisien ini mengukurkualitas model, yang menunjukkan seberapa jauh model yang kita peroleh dapat menerangkan data. Ada dua macamkoefisien determinasi, yaitu R2 dan 2adj R atau R2 terkoreksi. Permasalahannya adalah bahwa sebaran atau distribusi R2 atau2adj R tidak diketahui, sehingga tidak dapat ditentukan apakah R2 atau 2adj R kita berbeda atau tidak berbeda dengan nol.Tulisan ini membahas penentuan koefisien determinasi dengan menggunakan pendekatan boostrap, dan melakukansimulasi dengan data bangkitan dengan beberapa ukuran contoh (n) untuk beberapa nilai ragam sisaan.
RANCANGAN 2K , 2K-L FAKTORIAL YANG OPTIMALPADA MODEL PERMUKAAN MULTIRESPON ORDE SATU Purhadi Purhadi; Suryo Guritno; Susanti Linuwih
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 4, No 2 (2004)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v4i2.895

Abstract

parameter pada model permukaan multirespon yang bersifat tidak bias, konsisten dan efisien. Kriteria lain agar matrikrancangan percobaan optimal adalah variansi dari penaksir respon-responnya bernilai minimum. Beberapa rancanganpercobaan model orde satu yaitu rancangan Faktorial, Fraksional faktorial, Simplek dan Placket Burman. Denganmenggunakan pembobotan pada titik-titik percobaan sehingga memenuhi kriteria optimum-D, A, E maka didapatkanmatrik rancangan percobaan yang optimal untuk model permukaan multirespon orde satu. Dengan mengunakan ketigakriteria tersebut didapat hasil nilai determinan matrik informasi yang hampir sama. Eff-D digunakan untukmembandingkan beberapa rancangan percobaan.Apabila penambahan titik-titik percobaan dilakukan hal ini dapat secara proposional sesuai dengan nilai pembobotannyasehingga rancangan percobaan masih optimal. Hal diatas bisa juga dilakukan dengan cara menerapkan Algoritma Fedorovatau Algoritma Fedorov yang dimodifikasi jika matrik variansi kovariansi dari error tidak diketahui.
MM*INDO : INTERACTIVE STATISTICS LEARNING IN INDONESIAN LANGUAGE Hizir Sofyan; Noer Azam Achsani
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 4, No 2 (2004)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v4i2.886

Abstract

In line with the development of computer and information technology, interactive learning become analternative choice to the conventional one. MM*Indo is an interactive introductory to the world of statistics usingIndonesian Language. This software would help the student to understand the statistic lectures, especially in theelementary phase, through it’s dynamic explanation and many practical exercises. The software is supported by the XploRestatistical programming language and written in HTML and Javascript, so that it can be executed via World Wide Web andalso CD-ROM. It consists of 12 chapter covering all introductory themas of statistics, from the descriptive statistics,introduction to the probability, hypothesis testing until linear regression.
ANALYZING THE CONSUMER’S RICE PRICE USING MULTIPLE LINEAR REGRESSION AND X-12 ARIMA Dian Kusumaningrum,; Asep Saefuddin; Anang Kurnia
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 4, No 2 (2004)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v4i2.876

Abstract

Rice is one of the main foods in Indonesia. A change of rice price will cause a major effect in the lives of consumers. Onthe other hand, there are so many factors that influence the rice price. Thus finding key factors which are significant to therice price, as well as forecasting the consumer’s rice price are needed in order to maintain the stabilization of rice price.The second objective is to find key factors which influence the rice price by using multiple linear regression models. Theparameters were estimated by ordinary least square methods. There are 6 variables that are significant at α=5%, which arethe consumer’s rice price at the previous period, rice production at the current and previous period, farmer’s GKP price,realization of domestic stock, and total rice import. The rice price will increase if the GKP price and realization of domesticstock increase whereas total rice import and the consumer’s rice price at the previous period have negative influencestowards the rice price. In this model rice production at the current and previous period have positive signs, contradictory tothe microeconomic theory where when the rice production increases, there will be an excess supply and the price will drop.That condition will occur only if the commodity is a free commodity and the rice is at the sufficiency level but inIndonesia, rice is affected by the government’s policy and the rice productivity is left behind by the demand. Forecastingthe consumer’s rice price for the next five years was the last objective of this research. ARIMA Box–Jenkins Method, X-12ARIMA, Winter’s Method, and Trend Analysis were compared to find the best statistical model to forecast the consumer’srice price. X-12 ARIMA turns out to be the best method because it has the smallest MAPE, MAD, and MSD value. Thisresult is a satisfactory because according to Findley et al. (1998) X-12 ARIMA has the capability to adjust seasonal andtrading day factors which usually causes fluctuations in an economic time series data. Besides that, the X-12 ARIMAmethod also enhances the lack of other forecasting techniques used in this research to add regression effects. TheregARIMA makes it possible to add the user defined parameters, in this case the length of month parameter. The length ofmonth parameter rescales the monthly observation by a weight corresponding to the month relative length with respect tothe average length. The seasonal adjusted data from the original time series data is aimed to simplify the data withoutloosing important information.
DAY OF THE WEEK EFFECT AND STOCKMARKET VOLATILITY: FURTHER EVIDENCE FROMMALAYSIA EXCHANGE Zainudin Arsad; Mohd Shahrizan Othman
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 4, No 2 (2004)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v4i2.909

Abstract

This paper examines the day of the week anomalies at the Malaysian Exchange during various economic situations. Inparticular, the paper looks at the existence of day of the week effect for various indices, the popular benchmark CompositeIndex, the broader based Emas Index, smaller capital based Second Board Index, Financial Index of the Main Board andone of the newly created sectoral index of Trade and Services. Three estimation models are used to investigate thepresence of daily effect in these indices: the Ordinary Least Squares regression (OLS), Box and Jenkins ARIMA and theGARCH(p,q) models for capturing changing volatility in the stock returns. The OLS results reveal negative Monday meanreturns for each of the indices for the whole sample period. As expected during the Asian Economic Crisis period, themean returns are negative for each day of the week, with Thursday recording the largest negative returns. Negative meanreturns on Monday are not generally observed for each of the indices in recent years (during the World Economic Crisisand the following Recovery Period). When the changing volatility in the financial market is taken into account, theMonday negative returns remain significant during the whole sample period.
PENERAPAN METODE TRANSFORMASI WAVELET DISKRET UNTUKMENENTUKAN KANDUNGAN SENYAWA GINGEROL PADA TANAMAN JAHE Sony Sunaryo; Khairil Anwar Notodiputro
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 4, No 2 (2004)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v4i2.900

Abstract

Penentuan kandungan senyawa gingerol pada tanaman jahe dilakukan melalui proses yang memerlukan waktu dan biayayang relatif mahal. Alternatif cara lain adalah dengan mengembangkan model kalibrasi peubah ganda . Data spektraabsorban akan berupa sederetan data vektor x = (x1 ,x2 , ... ,xp )T yang berdimensi tinggi dan saling berkorelasi, sehinggapengembangan model kalibrasi peubah ganda E(Y) = X dengan mengikutkan semua data X menjadi tidak efisien. Denganreduksi dimensi yang baik, diharapkan pengembangan model kalibrasi peubah ganda menjadi lebih efisien. Reduksidimensi yang digunakan dalam makalah ini adalah metode transformasi wavelet diskret (DWT). Hasil penelitianmenunjukkan dari 1024 titik data spektra absorban yang diamati pada bilangan gelombang 113 cm-1 sampai dengan 311cm-1, untuk 14 contoh jahe, ternyata hanya dengan 11 koefisien wavelet menghasilkan representasi spektra yang sudahbaik. Pemodelan kalibrasi peubah ganda dengan menggabungkan hasil DWT dan PLS (Partial Least Square) diperolahhasil yang memuaskan yaitu R2 = 99,6 % dan s = 0,0088.
PERBANDINGAN PREPROCESSING METODE NN (NEURAL NETWORK) MENGGUNAKAN DISCRETE FOURIER TRANSFORM (DFT) DAN PRINCIPAL COMPONENT (PC) PADA DATA KALIBRASI Mohamad Atok; Khairil Anwar Notodiputro
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 4, No 2 (2004)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v4i2.891

Abstract

Masalah utama dalam pemodelan data kalibrasi adalah peubah X (absorban senyawa kimia) yang berdimensi lebih besardari peubah Y (konsentrasi zat aktif) dan terjadinya kolinearitas antar peubah X. Dalam makalah ini ingin dikaji ketepatanpendugaan Gingerol (Y) metode Neural Network (NN) menggunakan preprocessing Principle Component (PC) danDiscrete Fourier Transform (DFT). Data peubah X berupa absorban senyawa Gingerol pada 1866 panjang gelombang yangdiukur menggunakan spektrometer FTIR. Peubah Y merupakan hasil pengukuran Gingerol menggunakan metode HPLC.Dari 15 pengamatan, data dibagi 3, bagian pertama dan kedua untuk pembuatan model. dan bagian ketiga untuk mengujimodel. Dengan kriteria NMRSE minimum ketepatan dugaan hasil metode PC-NN dan DFT-NN diperbandingkan. Hasilsimulasi menunjukkan bahwa metode DFT-NN relatif lebih baik daripada PC-NN.
MODEL PREDIKSI DAMPAK BADAI MAGNET PADA FREKUENSI KRITIS FOF2 LAPISAN IONOSFER Habirun Habirun
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 4, No 2 (2004)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v4i2.882

Abstract

Pada uraian ini dibahas model prediksi frekuensi kritis foF2 lapisan ionosfer akibat dampak badai magnet dengan studikasusnya pada peristiwa badai tanggal 7 April 1995 di atas wilayah Biak. Menggunakan metode Kemungkinan Maksimum(Maximum Likelihood) melalui model ARMA (Auto Regression Moving Average) yang mengikuti pola tetap. Karena foF2lapisan ionosfer dinamis akibat pengaruh berbagai aktivitas gangguan maka keluaran dari model ARMA dikontrol modelbadai magnet global Kutiev dengan memperhitungkan dampak variasi diurnal dan semi diurnal. Akurasi model prediksiARMA dibandingkan terhadap model badai magnet global Kutiev, dan pola median pada saat sebelum, sedang, dansesudah badai magnet 7 April 1995 masing-masing galat secara berurutan sebesar 0,581 MHz; 0,983 MHz; dan 0,996MHz. Dari galat yang ditunjukan berarti model prediksi ARMA cukup akurat digunakan memprediksi perubahan foF2lapisan ionosfer pada saat badai magnet.

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