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All Journal JURNAL SISTEM INFORMASI BISNIS Jurnal Pendidikan Teknologi dan Kejuruan Jurnas Nasional Teknologi dan Sistem Informasi CESS (Journal of Computer Engineering, System and Science) Register: Jurnal Ilmiah Teknologi Sistem Informasi KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan) Jurnal Informatika Upgris E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal Online Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) semanTIK JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA JURNAL ILMIAH INFORMATIKA SINTECH (Science and Information Technology) Journal Jurnal Infomedia J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) Building of Informatics, Technology and Science (BITS) Journal of Computer System and Informatics (JoSYC) Brahmana : Jurnal Penerapan Kecerdasan Buatan Jurnal Tunas Journal of Computer Networks, Architecture and High Performance Computing IJISTECH RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI JPM: JURNAL PENGABDIAN MASYARAKAT Journal of Informatics Management and Information Technology J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Penelitian Inovatif (JUPIN) BEES: Bulletin of Electrical and Electronics Engineering
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ANALISIS ALGORITMA AES DALAM MENGAMANKAN DATA PADA KANTOR WALIKOTA PEMATANGSIANTAR hartato, eko; Gunawan, Indra; Parlina, Iin; Solikhun, Solikhun; Wanto, Anjar
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (363.308 KB) | DOI: 10.33884/jif.v8i01.1799

Abstract

Data is information that is kept very confidential because it contains important information about the company or agency. Computers are currently the main component in the company that is able to store data, speed up work, improve the quality and quantity of services, simplify the transaction process, and others. But in terms of computer security still has several loopholes that allow a person or group to easily retrieve data or information on the computer. To avoid theft and manipulation of data, it is necessary to implement a security system. Cryptography is the study of how to change information from normal conditions / forms (can be understood) into a form that cannot be understood. One method that can be used to secure messages / information is the Advanced Encryption Standard (AES). The application of the AES cryptographic algorithm in securing data at the Pematangsiantar Mayor's Office shows that this algorithm can generate encryption that cannot be understood by humans and produces the exact decryption with the initial plaintext input.
PROYEKSI INDEKS PEMBANGUNAN MANUSIA DI INDONESIA MENGGUNAKAN METODE STATISTICAL PARABOLIC DALAM MENYONGSONG REVOLUSI INDUSTRI 4.0 Kirana, Ika Okta; Nasution, Zulaini Masruro; Wanto, Anjar
Jurnal Pendidikan Teknologi dan Kejuruan Vol 16, No 2 (2019): Edisi Juli 2019
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jptk-undiksha.v16i2.18178

Abstract

Indeks Pembangunan Manusia (IPM) merupakan indikator yang sangat penting dalam mengukur keberhasilan sebuah negara dalam membangun kualitas hidup penduduk/masyarakat nya, termasuk Indonesia. Ekonomi global saat ini sedang pada titik puncak perubahan besar yang sebanding besarnya dengan munculnya revolusi industri 4.0. Penentuan peringkat atau level pembangunan dan ekonomi dari suatu wilayah atau negara dapat dilihat dari IPM. Karena begitu pentingnya Indeks Pembangunan Manusia (IPM), maka perlu dilakukan proyeksi tingkat perkembangan IPM di tahun-tahun selanjutnya, agar pemerintah Indonesia memiliki referensi dan acuan yang jelas untuk menentukan kebijakan ataupun membuat langkah-langkah strategis yang tepat agar Indeks Pembangunan Manusia (IPM) jangan sampai menurun di masa yang akan datang, bahkan meningkat pada tiap tahunnya. Data yang akan diproyeksi pada penelitian ini adalah data Indeks Pembangunan Manusia (IPM) tahun 2010-2018. Sumber data diambil dari Badan Pusat Statistik (BPS) Indonesia. Pada penelitian ini, metode proyeksi yang digunakan untuk melihat perkembangan IPM di Indonesia adalah Statistical Parabolic Projection (Trend Parabolik). Setelah dilakukan perhitungan, diperoleh selisih antara data asli IPM dengan data hasil proyeksi sangat dekat sekali, dengan tingkat MSE sebesar 0,01659. Sehingga dapat disimpulkan bahwa metode Trend Parabolik sangat baik digunakan untuk melakukan proyeksi Indeks Pembangunan Manusia. Oleh karena itu hasil penelitian ini adalah proyeksi Indeks Pembangunan Manusia (IPM) di Indonesia untuk tahun 2019 hingga tahun 2027
PREDIKSI PRODUKSI SUSU SEGAR DI INDONESIA MENGGUNAKAN ALGORITMA BACKPROPAGATION Saragih, Jonas Rayandi; Hartama, Dedy; Wanto, Anjar
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (473.143 KB) | DOI: 10.33884/jif.v8i01.1847

Abstract

Milk is a white liquid produced from female mammals that contain carbohydrates that are useful for humans. Based on data from the Indonesian Statistics Agency, milk productivity in Indonesia from 2012 to 2018 experienced an unstable curve. Therefore this research was conducted to predict and find out the level of development of milk productivity in Indonesia for the following years, so that companies that use milk have a reference to continue to strive to increase milk productivity in Indonesia to remain stable in order to meet the needs of the community and minimize milk imports. This algorithm used is backpropagation neural network. This algorithm is able to predict good data especially data that is sustainable in a certain period of time. to simplify this research the author uses the Matlab 2011 application. To facilitate writers, authors use 5 architectural model, namely 5-9-1 = 94%, 5-12-1 = 88%, 5-14-1 = 88%, 5-15-1 = 94%, 5-17-1 = 94 %. So we get the best architectural model using the architectural mode 5-15-1 with an accuracy rate of 94% with MSE = 0,000999842. Finally, this model is good enough to predict fresh milk production by province in Indonesia
PREDIKSI JUMLAH PENJUALAN PRODUK DI PT RAMAYANA PEMATANGSIANTAR MENGGUNAKAN METODE JST BACKPROPAGATION Syafiq, Muhammad; Hartama, Dedy; Kirana, Ika Okta; Gunawan, Indra; Wanto, Anjar
JURIKOM (Jurnal Riset Komputer) Vol 7, No 1 (2020): Februari 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (256.554 KB) | DOI: 10.30865/jurikom.v7i1.1963

Abstract

Product is the one of thing which more important in the business especially for the retail industry. Ramayana is the one exact place for selling retail products such as clothing, shoes, or slipper. On 2012-2018, the number of sales of products in Ramayana experience curve up and down. That thing can cause profit and lose for Ramayana, to avoid that thing need to be held a prediction for the next months so that Ramayana side can know what will happen in the next months in selling it?s product and can take a step for more effective in selling it?s products. The data which used in this research is the data report monthly product sales of shoes & sandal sourced from Ramayana from 2012 until 2018. This research uses the Backpropagation neural network method using 5 architectures namely 3-26-1, 3-31-1, 3-35-1, 3-39-1 and 3-40-1. The best architecture is 3-35-1 with an accuracy rate of 92%. The results obtained are the results of the prediction of the number of sales for 2019, 2020, 2021 and 2022
Pelatihan dan Bimbingan dalam Pemanfaatan Internet yang Baik dan Aman bagi Pelajar SMK Anak Bangsa Desa Bandar Siantar Kabupaten Simalungun Wanto, Anjar; Suhendro, Dedi; Windarto, Agus Perdana
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 9, No 2 (2018): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v9i2.2116

Abstract

Perkembangan teknologi khususnya internet telah membawa banyak perubahan. Berkat bantuan internet semua pekerjaan menjadi terasa ringan. Bagi para siswa atau pelajar, internet memudahkan mereka dalam mencari literatur atau bahan-bahan tugas sekolah. Akan tetapi kemampuan siswa dalam menggunakan internet dengan cara yang baik dan aman di era globalisasi dewasa ini masih tergolong rendah, terutama pada siswa-siswi SMK Anak Bangsa desa Bandar Siantar Kabupaten Simalungun. Letaknya yang di pedesaan dan jauh dari perkotaan serta kurangnya perhatian pemerintah daerah dalam melakukan sosialisasi, bimbingan dan pelatihan internet membuat banyak siswa khususnya yang tinggal di pedesaan, kurang memahami pentingnya pemanfaatan internet dengan cara yang positif. Sebagian besar para siswa bisa bebas berselancar di dunia maya dan melakukan aktivitas online mereka tanpa adanya pengawasan. Oleh karena itu kegiatan pelatihan dan bimbingan dalam pemanfaatan internet sangat perlu dilakukan untuk mengingatkan serta memberikan kesadaran bagi para siswa bagaimana cara menggunakan internet dengan cara yang bijaksana agar kedepannya kemampuan akademik maupun pengetahuan mereka terhadap dunia pendidikan dan informasi semakin meningkat. Pelatihan ini nanti nya akan menggunakan 4 macam modul diktat yang masing-masing akan dijelaskan berupa presentasi menggunakan power point. Dengan pelatihan dan bimbingan ini diharapkan para pelajar khususnya disekolah ini mampu memanfaatkan internet dengan arif dan bijaksana dalam rangka mendukung upaya pengembangan SDM yang beradab yang memiliki kemampuan bersaing secara global, tidak hanya mampu bersaing secara intelektual tetapi juga memiliki adab dan perilaku yang baik.
SELEKSI PENERIMAAN ASISTEN LABORATORIUM MENGGUNAKAN ALGORITMA AHP PADA AMIK-STIKOM TUNAS BANGSA PEMATANGSIANTAR Wanto, Anjar; Kurniawan, Eko
JURNAL INFORMATIKA DAN KOMPUTER Vol 3, No 1 (2018): FEBRUARI - AGUSTUS 2018
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat - Universitas Teknologi Digital Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (369.019 KB) | DOI: 10.26798/jiko.v3i1.106

Abstract

AMIK Tunas Bangsa is a growing university in Pematangsiantar. Therefore, there are still many university activities and activities that are constrained by problems. One of them is the problem in the selection of employees by the foundation to occupy the position of Laboratory Assistant. Problems that arise in the selection process of acceptance of laboratory assistant at AMIK Tunas Bangsa Pematangsiantar is the absence of tools that can assist management in determining the appropriate candidate laboratory assistant to be the best. By building a system to support the decision of using AHP Algorithm (Analytical Hierarchy Process) is expected to assist the Foundation in conducting the assessment and can be used as input (Reference) by the Foundation to make decisions in selecting the appropriate laboratory assistant candidate accepted. Selection of laboratory assistant acceptance using Analytical Hierarchy Process (AHP) algorithm can yield the best alternative, with criteria in the form of an interview, written test, practice test, and GPA. So the selection of acceptance of laboratory assistants can run exactly and in accordance with the expected.
Analisis Jaringan Saraf Dalam Estimasi Tingkat Pengangguran Terbuka Penduduk Sumatera Utara Wahyuni, Juli; Paranthy, Yuri Widya; Wanto, Anjar
Jurnal Infomedia:Teknik Informatika, Multimedia & Jaringan Vol 3, No 1 (2018): Jurnal Infomedia
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (812.071 KB) | DOI: 10.30811/jim.v3i1.624

Abstract

Abstrak — Pengangguran merupakan salah satu masalah ekonomi yang mempengaruhi kehidupan manusia secara langsung. Di Indonesia tingkat persentase pengangguran cukup tinggi, khususnya pada provinsi Sumatera Utara. Contohnya tercatat pada tahun 2010, kota sibolga memilik tingkat pengangguran yang paling tinggi yaitu berada di angka 17.50% dari total penduduknya. Berbeda dengan Samosir yang hanya memilik 0.55% pengangguran dari total penduduknya. Untuk dapat mengurangi jumlah pengangguran, khususnya di Sumatera Utara maka perlu dilakukan estimasi tingkat pengangguran untuk tahun-tahun mendatang, agar pemerintah memiliki acuan dalam menentukan kebijakan sehingga dapat melakukan penanggulangan terhadap jumlah pengangguran. Data yang digunakan pada penelitian ini terfokus pada data tingkat pengangguran terbuka penduduk umur 15 tahun keatas dari tahun 2010-2015 di Sumatera Utara. Metode yang digunakan dalam penelitian ini yaitu Jaringan Saraf Tiruan Backpropagation. Analisa data dilakukan dengan algoritma backpropagation menggunakan Matlab. Arsitektur jaringan yang digunakan ada 5 model (4-55-1, 4-57-1, 4-59-1, 4-61-1 dan 4-77-1), dengan model yang terbaik adalah 4-55-1 dengan Learning Rate yang digunakan 0.01. Sehingga menghasilkan tingkat akurasi 88% dengan nilai Mean Squared Error (MSE) adalah 0,55701127.Kata kunci— Pengangguran, Estimasi, Penduduk, Jaringan Saraf, Sumatera Utara.Abstract — Unemployment is one of the economic problems that affect human life directly. In Indonesia the level of unemployment is quite high, especially in North Sumatra province. For example, recorded in 2010, sibolga city has the highest unemployment rate that is at 17.50% of the total population. In contrast to Samosir who only have 0.55% unemployment out of the total population. In order to reduce the number of unemployment, especially in North Sumatra, it is necessary to estimate the unemployment rate for the coming years, so that the government has a reference in determining the policy so that it can handle the number of unemployed. The data used in this study focuses on open unemployment rate data of the population aged 15 years and over from 2010-2015 in North Sumatra. The method used in this research is Artificial Neural Network Backpropagation. Data analysis is done by backpropagation algorithm using Matlab. Network architecture used there are 5 models (4-55-1, 4-57-1, 4-59-1, 4-61-1 and 4-77-1), with the best model is 4-55-1 with Learning Rate used 0.01. So as to produce an accuracy of 88% with the Mean Squared Error (MSE) is 0.55701127.Keywords— Unemployment, Estimation, Population, Neural Network, North Sumatera.
Analisis Jaringan Syaraf Tiruan untuk prediksi volume ekspor dan impor migas di Indonesia Andriani, Yuli; Silitonga, Hotmalina; Wanto, Anjar
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 4, No 1 (2018): January-June
Publisher : Prodi Sistem Informasi - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1572.598 KB) | DOI: 10.26594/register.v4i1.1157

Abstract

Analisis pada penelitian penting dilakukan untuk tujuan mengetahui ketepatan dan keakuratan dari penelitian itu sendiri. Begitu juga dalam prediksi volume ekspor dan impor migas di Indonesia. Dilakukannya penelitian ini untuk mengetahui seberapa besar perkembangan ekspor dan impor Indonesia di bidang migas di masa yang akan datang. Penelitian ini menggunakan Jaringan Syaraf Tiruan (JST) atau Artificial Neural Network (ANN) dengan algoritma Backpropagation. Data penelitian ini bersumber dari dokumen kepabeanan Ditjen Bea dan Cukai yaitu Pemberitahuan Ekspor Barang (PEB) dan Pemberitahuan Impor Barang (PIB). Berdasarkan data ini, variabel yang digunakan ada 7, antara lain: Tahun, ekspor minyak mentah, impor minyak mentah, ekspor hasil minyak, impor hasil minyak, ekspor gas dan impor gas. Ada 5 model arsitektur yang digunakan pada penelitian ini, 12-5-1, 12-7-1, 12-8-1, 12-10-1 dan 12-14-1. Dari ke 5 model yang digunakan, yang terbaik adalah 12-5-1 dengan menghasilkan tingkat akurasi 83%, MSE 0,0281641257 dengan tingkat error yang digunakan 0,001-0,05. Sehingga model ini bagus untuk memprediksi volume ekspor dan impor migas di Indonesia, karena akurasianya antara 80% hingga 90%.   Analysis of the research is Imporant used to know precision and accuracy of the research itself. It is also in the prediction of Volume Exports and Impors of Oil and Gas in Indonesia. This research is conducted to find out how much the development of Indonesias exports and Impors in the field of oil and gas in the future. This research used Artificial Neural Network with Backpropagation algorithm. The data of this research have as a source from custom documents of the Directorate General of Customs and Excise (Declaration Form/PEB and Impor Export Declaration/PIB). Based on this data, there are 7 variables used, among others: Year, Crude oil exports, Crude oil Impors, Exports of oil products, Impored oil products, Gas exports and Gas Impors. There are 5 architectural models used in this study, 12-5-1, 12-7-1, 12-8-1, 12-10-1 and 12-14-1. Of the 5 models has used, the best models is 12-5-1 with an accuracy 83%, MSE 0.0281641257 with error rate 0.001-0.05. So this model is good to predict the Volume of Exports and Impors of Oil and Gas in Indonesia, because its accuracy between 80% to 90%.
PREDIKSI PRODUKTIVITAS JAGUNG DI INDONESIA SEBAGAI UPAYA ANTISIPASI IMPOR MENGGUNAKAN JARINGAN SARAF TIRUAN BACKPROPAGATION Wanto, Anjar
SINTECH (Science and Information Technology) Journal Vol 2 No 1 (2019): SINTECH Journal Edisi April 2019
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1128.657 KB) | DOI: 10.31598/sintechjournal.v2i1.355

Abstract

Corn is a staple food that is still widely consumed by the population of Indonesia. Based on data from the Indonesian Statistics Agency, corn productivity in Indonesia from 2005 to 2015 calculated an unstable curve. Therefore this research was conducted to predict and see the large growth of maize in Indonesia for the following years so that the government has a reference to continuously strive to increase corn productivity in Indonesia in order to remain stable in order to meet the needs of Indonesian people to minimize corn imports. This study uses data on corn productivity in Indonesia in 2005-2015 sourced from the Indonesian Central Bureau of Statistics. The prediction algorithm used is the Backpropagation Neural Network. This algorithm is able to predict data well, especially data that is maintained for a certain period of time. To facilitate data analysis, the author uses the Matlab 2011b application. In this study, a training and testing process will be carried out using 5 network architecture models, namely 5-25-1, 5-43-1, 5-76-1, 5-78-1 and 7-128-1. Of the 5 architectural models, the best is 5-25-1 with the percentage of 88% and the MSE value of 0.00992433.
Analisis Dan Pemodelan Posisi Access Point Pada Jaringan Wi-Fi Menggunakan Metode Simulate Annealing Wanto, Anjar; Hardinata, Jaya T; Silaban, Herlan F; Saputra, Widodo
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 1, No 1 (2017): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (955.334 KB) | DOI: 10.30645/j-sakti.v1i1.35

Abstract

Laying the position of the access point on the Wi-Fi network in a room is needed to optimize the signal strength received from the transmitter to the receiver. The parameters that determine the performance of the access point is the value of the signal strength. Strong or weak a signal access point will be affected by distance and barriers that exist between the access point and a client that accesses the access point. This study has been performed several simulations in multiple rooms are placed the access point to the receiver. The parameters used to measure the signal strength using inSSIDer applications that generate value RSSI (Received Signal Strength Indication) of a transmitter to the receiver and barriers (barriers) that may influence the strength of the signal. From this research strength of the signal received by the receiver not only in pengaruhui by the distance between accespoint to the recipient, but rather influenced by barriers (barriers) which is in a room. From the results of the research are expected to be able to obtain appropriate modeling to optimize access point placement position using the Simulate annealing method.
Co-Authors Agung Pratama Agus Perdana Windarto Amri, Muhammad Aliyul Arminarahmah, Nur Astria, Cici Batubara, Dinda Nabila Damanik, Irfan Sudahri DANIEL SITORUS Desiana, Eva Dewi, Rafiqa Eko Kurniawan Eko Purwanto Fardhani, Ayu Artika Febriyati, Nur Ahlina Fitri Anggraini, Fitri Ginantra, Ni Luh Wiwik Sri Rahayu GS , Achmad Daengs Gultom, Widya Tri Charisma Hanafiah, Mhd Ali Hardinata, Jaya T Hardinata, Jaya T Hardinata, Jaya Tata Hardinata, Jaya Tata Hartama, Dedy Hartama, Dedy Hartama, Dedy hartato, eko Hartato, Eko Heru Satria Tambunan, Heru Satria Hutabarat, Meychael Adi Putra Hutasoit, Rahel Adelina Hutasoit, Rahel Adelina Imandasari, Tia Indra Gunawan Irnanda, Khairunnissa Fanny Jalaluddin Jalaluddin Jufriadif Na`am, Jufriadif Julham, Muhammad JULHAM, MUHAMMAD Kirana, Ika Okta Lubis, M.Ridwan Mesran Mesran, Mesran Muhammad Ridwan Lubis, Muhammad Ridwan MUHAMMAD SYAFIQ Napitupulu, Flora Sabarina Nasution, Zulaini Masruro Okprana, Harly Paranthy, Yuri Widya Parlina, Iin Parlina, Iin Perdana Windarto, Agus Poningsih Pradipta, Asro Pranata, Ruri Eka Pratama, Agung Yusuf Purba, Nuraysah Zamil Putra, Okta Andrica Retno Andani, Sundari S Sumarno Sadewo, Mhd Gading Sadewo, Mhd Gading Safii, M Saputra, Widodo Saputra, Widodo Saputra, Widodo Saragih, Edu Wardo Saragih, Ilham Syahputra Saragih, Irfan Christian Saragih, Jonas Rayandi Saragih, Mhd. Billy Sandi Sari, Riyani Wulan Sari, Riyani Wulan Sarjon Defit Sembiring, Rahmat W Setti, Sunil Sianipar, Vasma Vitriani Silaban, Herlan F Silaban, Herlan F Silfia Andini, Silfia Silitonga, Hotmalina Silitonga, Hotmalina Simanjuntak, Desi Insani Natalia Simarmata, Roulina Simbolon, Imelda Asih Rohani Sinaga, Samuel Palentino Sinaga, Samuel Palentino Sinaga, Titin Handayani Siregar, Sandy Putra Situmorang, Marseba Solikhun Solikhun Solikhun, Solikhun Solikhun, S Suhendro, Dedi Sumarno Sumarno Syafrika Deni Rizki, Syafrika Deni Syahri Ramadhan, Syahri Vidya utari, Venny Wahyuni, Juli Widyasuti, Meilin Widyasuti, Meilin Yatussa’ada, Fikri Yuhandri Yuhandri, Yuhandri Yuli Andriani