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All Journal JURNAL ILMIAH MATEMATIKA DAN TERAPAN BAREKENG: Jurnal Ilmu Matematika dan Terapan Mathvision : Jurnal Matematika Parameter: Journal of Statistics Jurnal Matematika Integratif Jurnal Pengabdian Farmasi dan Sains

Desy Lusiyanti

Universitas Tadulako

Author-ID : 723781

Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Transportation

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Peramalan Menggunakan Model Generalized Space Time Autoregressive (GSTAR) untuk Indeks Harga Konsumen 4 Kota di Provinsi Sulawesi Selatan Muhammad Alkifar Masdin; Nur' eni; Desy Lusiyanti
Jurnal Matematika Integratif Vol 14, No 1: April, 2018
Publisher : Department of Matematics, Universitas Padjadjaran

Indeks Harga Konsumen (IHK) adalah indeks yang menghitung rata-rata perubahan harga dari suatu paket barang dan jasa yang dikonsumsi oleh rumah tangga dalam kurun waktu tertentu. Data IHK merupakan data runtun waktu, sehingga dapat dimodelkan menggunakan analisis time series. Dari beberapa aplikasi, data runtun waktu dicatat secara bersamaan di sejumlah lokasi yang menghasilkan runtun waktu spasial. Penelitian ini menggunakan metode Generalized Space Time Autoregressive (GSTAR). Penelitian ini bertujuan untuk mendapatkan model GSTAR terbaik dan hasil peramalan untuk data Indeks Harga Konsumen (IHK) di Kota Watampone, Kota Makassar, Kota Pare-Pare dan Kota Palopo. Hasil yang diperoleh dalam penelitian ini ialah model GSTAR (11) I(1) setelah differencing 1 menggunakan bobot lokasi seragam karena menghasilkan residual bobot lokasi yang memenuhi asumsi white noise dengan nilai RMSE 10,63 sehingga model GSTAR yang diperoleh sebagai berikut: Hasil ramalan yang diperoleh pada bulan Januari dan Februari berbeda cukup signifikan dengan data aktual, hal ini dikarenakan adanya perbedaan tahun dasar yang diberlakukan mulai Januari 2014. Mulai Maret 2014, hasil ramalan data IHK 4 kota di Provinsi Sulawesi Selatan relatif stabil dan mendekati nilai data aktual.

OPTIMALISASI PENDISTRIBUSIAN PUPUK DI WILAYAH SULAWESI TENGAH MELALUI MODEL TRANSSHIPMENT DENGAN MENGGUNAKAN METODE VOGEL APPROXIMATION Safir, M; Musdalifah, S; Lusiyanti, D
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 12 No. 2 (2015)
Publisher : Program Studi Matematika, Universitas Tadulako

OPTIMALISASI PENDISTRIBUSIAN PUPUK DI WILAYAH SULAWESI TENGAH MELALUI MODEL TRANSSHIPMENT DENGAN MENGGUNAKAN METODE VOGEL APPROXIMATION

APLIKASI METODE GOAL PROGRAMMING PADA PERENCANAAN PRODUKSI KLAPPERTAART PADA USAHA KECIL MENENGAH (UKM) NAJMAH KLAPPERTAART Sutrisno, D; Sahari, A; Lusiyanti, D
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 14 No. 1 (2017)
Publisher : Program Studi Matematika, Universitas Tadulako

APLIKASI METODE GOAL PROGRAMMING PADA PERENCANAANPRODUKSI KLAPPERTAART PADA USAHA KECIL MENENGAH(UKM) NAJMAH KLAPPERTAART

MERANCANG APLIKASI SMS GATEWAY SEBAGAI UPAYA PELAYANAN INFORMASI KEPATUHAN WAJIB PAJAK DI KPP PRATAMA PALU Khairiah, J; Ratianingsih, R; Lusiyanti, D
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 14 No. 1 (2017)
Publisher : Program Studi Matematika, Universitas Tadulako

MERANCANG APLIKASI SMS GATEWAY SEBAGAI UPAYA PELAYANANINFORMASI KEPATUHAN WAJIB PAJAK DI KPP PRATAMA PALU

PREDIKSI KUALITAS AIR BERSIH PDAM KOTA PALU MENGGUNAKAN METODE BACKPROPAGATION Mustakim, J R; Ratianingsih, R; Lusiyanti, D
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 14 No. 1 (2017)
Publisher : Program Studi Matematika, Universitas Tadulako

PREDIKSI KUALITAS AIR BERSIH PDAM KOTA PALU MENGGUNAKANMETODE BACKPROPAGATION

APLIKASI MODEL NEURO FUZZY UNTUK PENGONTROL TINGKAT INFLASI DI PROVINSI SULAWESI TENGAH Rivaldi, Rivaldi; Ratianingsih, R; Lusiyanti, D
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 14 No. 1 (2017)
Publisher : Program Studi Matematika, Universitas Tadulako

APLIKASI MODEL NEURO FUZZY UNTUK PENGONTROL TINGKAT INFLASIDI PROVINSI SULAWESI TENGAH

KLASIFIKASI STATUS GIZI IBU HAMIL UNTUK MENGIDENTIFIKASI BAYI BERAT LAHIR RENDAH (BBLR) MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM) (STUDI KASUS DI PUSKESMAS LABUAN) Oganis, C; Musdalifah, S; Lusiyanti, D
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 14 No. 2 (2017)
Publisher : Program Studi Matematika, Universitas Tadulako

KLASIFIKASI STATUS GIZI IBU HAMIL UNTUK MENGIDENTIFIKASI BAYIBERAT LAHIR RENDAH (BBLR) MENGGUNAKAN METODE SUPPORTVECTOR MACHINE (SVM) (STUDI KASUS DI PUSKESMAS LABUAN)

DETEKSI RABUN JAUH (MIOPIA) BERBASIS PENGOLAHAN CITRA DIGITAL MENGGUNAKAN METODE BWAREA Anwar, C; Sudarsana, I W; Lusiyanti, D
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 14 No. 2 (2017)
Publisher : Program Studi Matematika, Universitas Tadulako

DETEKSI RABUN JAUH (MIOPIA) BERBASIS PENGOLAHAN CITRA DIGITAL MENGGUNAKAN METODE BWAREA

MENGKAJI PERILAKU HARGA KOMODITI PANGAN DI KOTA PALU MENGGUNAKAN METODE BACKPROPAGATION Peole, I N; Ratianingsih, R; Lusiyanti, D
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 15 No. 1 (2018)
Publisher : Program Studi Matematika, Universitas Tadulako

Artificial neural network is an information processing paradigm that is inspired by biological neural cell systems, like the brain, that processes information. The purpose of this research is to develop neural networks to predict the price of food commodities using backpropagation method. The research was conducted by using the rate of monthly price of food commodities in Palu from January 2011 - December 2015. The data is used to predict food commodity prices forduring 2016. The backpropagation networks consists of three layers. The first layer of input is constructedin the form of monthly prices of IR 64, ciherang, membramo, cimandi, superwin, sintanur, cisantana, sticky black, sticky white, yellow corn dry, white corn, soybeans, peanuts, green beans, cassava, sweet potato, onion, garlic, red pepper large, red pepper curls, cayenne pepper, cabbage round, potatoes, tomatoes, carrots, cauliflower, beans, onion, avocado, red apples, green apples, oranges, jackfruit, mango, pineapple, papaya, banana, banana horns, rambutan, bark, olive, durian, watermelon, and mangosteen from January â€“ December that consist of 12 variables. One hidden layer consistof five neurons and the other one is the output, that isÂ the food commodity prices. The training process shows that on a maximum iterations on 500, constant learning rate 0,3 and 0,6 momentum, the predictions have 97.92% of level accuracy. The identification resultof food commodity prices behavior in Palu is predicted as follow: IR 64 Rp7.387, ciherang Rp8.182, membramo Rp8.150, cimandi Rp8.131, superwin Rp8.228, sintanur Rp8.660, cisantana Rp8.122, black sticky rice Rp21.383, white sticky rice Rp16.558, dry yellow corn Rp5.983, white corn Rp9.283, soybeans Rp14.600, peanuts Rp20.008, green beans Rp16.375, cassava Rp8.225, sweet potato Rp8. 542, red onion Rp28.550, garlic Rp21.208, red chili Rp27.308, curly red chili Rp23.650, cayenne Rp36.450, round cabbage Rp6.833, Rp12.067 potatoes, tomatoes Rp6.108, carrots 11.000, cauliflower Rp8.625, beans Rp10.333, scallion Rp25.242, avocado 11.000, red apple Rp29.023, green apple Rp31.067, orange Rp6.083, jackfruit Rp23.483, mango Rp11.187, pineapple Rp8.183, papaya Rp10.600, bananas Rp8.481, horn banana Rp2.683, rambutan Rp8.450, barking Rp5.625, tan Rp8.366, durian Rp19.208, watermelon Rp14.528 and mangosteen Rp18.067. It is predicted that the food commodity prices increased monthly.

RANCANG BANGUN SISTEM INFORMASI AKADEMIK FMIPA UNIVERSITAS TADULAKO BERBASIS ANDROID Prasetyo, W F; Sudarsana, I W; Lusiyanti, D
JURNAL ILMIAH MATEMATIKA DAN TERAPAN Vol. 15 No. 2 (2018)
Publisher : Program Studi Matematika, Universitas Tadulako

Academic information system based on Android necessary to support the effectiveness management of academic data such as input card study plan and input the value of course. To build Siakad Android application, the authors do the research of the database web Siakad Faculty of Natural Science Tadulako University that includes all the data of students, faculty, courses, card study plan, and card study result. The purpose of this study was to obtain academic information system based on Android Tadulako University Faculty of Mathematics and Natural Sciences. This application is built with features such as view bio, view the result of study, view the transcript, input study plan card, input result study card, wait confirm of study plan, and confirm study plan. Based on the results and discussion, it can be concluded that academic information system can support the effectiveness of academic data processing, such as the study plan input, and the input value of the course.

Co-Authors Agusman Sahari Andri Andri Anwar, C Ayu Lestari Darmawanti, Y Fajri, M Gunawan, I I Wayan Sudarsana Iman Al Fajri Iman Al Fajri Jafaar, I M Jaya, A I Khairiah, J M Rifai Mohammad Fajri Muhammad Alkifar Masdin Musdalifah, S Mustakim, J R Nasria Nacong Natalia, Y Nur' eni Nur'Eni Oganis, C Oktavia, S Ondja, T N Peole, I N Prasetyo, W F Pratiwi, A M Rasna Rina Ratianingsih Riswan Rivaldi, Rivaldi Safaat, M Safir, M Sahari, A Selvy Musdalifah Sudarsana, I W Sutrisno, D Tandi, Andri Tuadi, A A Turilah, N H Usman, R Wardani, N M E

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