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All Journal Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Komtika (Komputasi dan Informatika) Jiko (Jurnal Informatika dan komputer) JURIKOM (Jurnal Riset Komputer) Jurnal Linguistik Komputasional Jurnal Abdimas Mandiri Jurnal Pengabdian Dharma Bakti Journal of Informatics, Information System, Software Engineering and Applications (INISTA) Journal of Dinda : Data Science, Information Technology, and Data Analytics IJCOSIN : Indonesian Journal of Community Service and Innovation Jurnal Pengabdian Bisnis dan Akuntansi Soedirman SmartComp Journal of Software Engineering and Multimedia (JASMED) Jurnal Komtika (Komputasi dan Informatika)
Auliya Burhanuddin
Institut Teknologi Telkom Purwoketo
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Sistem Rekomendasi Pemilihan Peminatan Menggunakan Density Canopy K-Means Ridho Ananda; Muhammad Zidny Naf’an; Amalia Beladinna Arifa; Auliya Burhanuddin
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 1 (2020): Februari 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (623.312 KB) | DOI: 10.29207/resti.v4i1.1531

Abstract

The carelessly selection of specialization course leaves some students with difficulty. Therefore, it is needed a recommendation system to solve it. Several approaches could be used to build the system, one of them was K-Means. K-Means required the number of initial centroid at random, so its result was not yet optimal. To determine the optimal initial centroid, Density Canopy (DC) algorithms had been proposed. In this research, DC and K-Means (DCKM) was implemented to build the recommendation system in the problem. The alpha criterion was also proposed to improve the performance of DCKM. The academic quality dataset in the 2018 informatics programs students of ITTP was used. There were three main stages in the system, namely determination of the weight of the course in dataset, implementation of DCKM, and determination of specialization recommendations. The results showed that the system by using DCKM has good quality based on the Silhouette results (at least 0.655). The system also used standar valuation scale in ITTP and silhouette index in the process of system. The results showed that 176 (65.91%) students were recommended in IT specialization, 25 (9.36%) students were recommended in MM specialization and 66 (24.7%) students were recommended in SC specialization.
PENENTUAN JUMLAH CLUSTER IDEAL SMK DI JAWA TENGAH DENGAN METODE X-MEANS CLUSTERING DAN K-MEANS CLUSTERING Rifki Adhitama; Auliya Burhanuddin; Ridho Ananda
JIKO (Jurnal Informatika dan Komputer) Vol 3, No 1 (2020)
Publisher : Journal Of Informatics and Computer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v3i1.1635

Abstract

SMK merupakan salah satu intrumen penting dalam pengembangan Sumber Daya Manusia (SDM) di Indonesia pada umumnya dan di Jawa Tengah pada khususnya. Belum adanya pengelompokan SMK berdasarkan data pokok kemendikbud di jawa tengah merupakan sebuah peluagn untuk mengembangkan arah revitalisasi SMK menjadi lebih baik dan jelas. X-means merupakan salah satu metode clustering yang dikembangkan dari metode clustering yang cukup popular, yaitu K-means. Penelitian ini menggunakan data pokok kemendikbud untuk menghitung pembagian cluster terbaik dengan menggunakan metode X-means dengan membandingkan nilai DBI X-means dengan nilai DBI K-means pada variasi ukuran cluster mulai dari empat, enam, delapan dan sepuluh cluster. Hasil penelitian ini menunjukkan bahwa secara konsisten nilai DBI terbaik ada pada ukuran cluster empat, baik menggunakan X-means ampun K-means dengan nilai DBI X-means sebesar 0,933 dan nilai DBI K-means sebesar 0,914, sedangkan nilai DBI paling besar juga konsisten pada ukuran cluster 10, sebesar 1,439 pada X-means dan 1,322 pada K-means. Berdasrkan hasil tersebut maka SMK di Jawa Tengah dapat dibagi ke dalam 4 kelompok yaitu kurang, cukup, baik, dan unggul.
Analisis K-Means Untuk Mengetahui Kelompok Tingkat Antusias Netizen Twitter Pada Kejadian Letusan Gunung Tangkuban Perahu Auliya Burhanuddin; Rifki Adhitama; Apri Junaidi
Journal of INISTA Vol 3 No 1 (2020): November 2020
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v3i1.165

Abstract

Internet merupakan produk terknologi yang menandai era revolusi industri 4.0 dimana telah merubah cara berkomunikasi dengan jenis interaksi sosial yang baru. Pada 27 Agustus 2010 gunung sinabung meletus dan banyak kerugian dirasakan. Gunung tangkuban perahu meletus pada 26 Juli 2019 pukul 15.48. Belajar dari meletusnya gunung Sinabung yang merugikan maka memunculkan empati dari masyarakat, bantuan moral dan spiritual. Untuk mendapatkan data twiter dari website twitter maka dapat dilakukan proses crawling data yang dicari. Dari hasil crawling twetter akan didapatkan data user berupa total tweet, total follower, total likes, website, source, bio profile, id, akun, nama, dan lokasi. Kemudian dilakukan proses pengelompokkan/clustering menggunakan metode K-Means Clustering untuk mengetahui kelompok antusias dari netizen sebelum, ketika, dan pasca kejadian bencana. Hasil yang didapat adalah jumlah tweet sebelum gunung meletus yaitu 11.324 Tweet ketika meletus 35 tweet, dan pasca meletus 26 Juli 2019 yaitu 1.170 tweet dan 26-29 juli 2019 yaitu 1.512 tweet. Tingkat antusias sebelum kejadian 6.572 antusias dan 4.696 sangat antusias. Setelah gunung meletus 812 dan 798 antusias; dan 346 dan 575 sangat antusias. Tingkat antusias netizen sangat tinggi pada sebelum kejadian maka dapat dilakukan aktivitas sosial yang dapat dimanfaatkan pasca kejadian bencana sehingga dapat membantu secara langsung setelah kejadian bencana terjadi.
Penerapan X Means Clustering Pada UMKM Kab Banyumas Yang Mendukung Mega Shifting Consumer Behavior Akibat Covid-19 Rifki Adhitama; Auliya Burhanuddin; Atik Febriani
Journal of INISTA Vol 4 No 1 (2021): November 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v4i1.429

Abstract

The Covid-19 has become a epidemic that is troubling the public because of the extent and speed of the virus spreading. The Covid-19 has resulted in people being unable to move outside their homes freely so that household consumption has decreased. This condition is similar to the crisis in 1997-1998, where MSMEs and small traders could survive. In Banyumas district, the percentage of MSMEs are in the large, medium, and small groups that can support the habit of Mega Shifting, or businesses that can be done at home so that they can be an economic savior in the covid-19. Clustering is a method of grouping similar objects which are taken from several criteria. X-Means is a grouping method that can be used to effectively calculate the value of K. As for testing the quality of a cluster using the Purity test method, it is said to be "Good" if the results of this Purity are close to 1. The total of MSMEs in the Banyumas district which be grouped is 27,574 MSMEs. The purity based on the results of the cluster is 0.9892 (3 groups), 0.9894 (4 groups), 0.9928 (5 groups), and 0.9677 (6 groups). In 3 groups, the results of grouping are 58 MSMEs belong to large groups, 381 MSMEs belong to medium groups, and 26,602 MSMEs belong to small groups. The recommended MSMEs sectors to face mega shifting are food stalls, culinary, agriculture, snacks, traders, craftsmen, workshops, furniture, constructions, and grocery stores.
Prediksi Harga Saham Bank Bri Menggunakan Algoritma Linear Regresion Sebagai Strategi Jual Beli Saham Janur Syah Putra; Rima Dias Ramadhani; Auliya Burhanuddin
Indonesian Journal of Data Science, IoT, Machine Learning and Informatics Vol 2 No 1 (2022): February
Publisher : Research Group of Data Engineering, Faculty of Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/dinda.v2i1.273

Abstract

Shares are securities as proof of ownership of investors in a company. Stocks have a volatile nature, this makes stocks difficult to predict. Stock prediction is an effort to estimate the stock price, especially in the Bank Rakyat Indonesia company that will appear in the future, and to increase investors' profit opportunities in making investment decisions. During the COVID-19 pandemic, Bank BRI's shares experienced significant ups and downs in four months, which illustrates the sensitivity of the stock to an event. Therefore, it is important to predict stock prices to reduce the risk accepted by investors. The prediction itself requires time series data. Time series is data that is collected sequentially from time to time. The method used for time series data is Linear Regression because this method can handle time-series data. Based on these problems, stock prediction research will be conducted at the Bank Rakyat Indonesia company using the Linear Regression method. Bank Rakyat Indonesia share price data were obtained from the investing.com website from the period starting on January 1, 2008, to June 1, 2020. The data is processed starting from preprocessing to determine attributes, remove unnecessary attributes, and change the contents of the data type, then process split data to divide the dataset into training and test data. The attributes used in this study are Date and Price and the distribution of the data used is 60:40, 65:35, 70:30, 75:25, and 80:20. The best ratio is at 80:20 which produces train and test accuracy of 0.89 and 0.91, Then each training data and testing data are entered into the linear regression model for prediction. The error results from the predictions were calculated using MAPE and yielded a percentage of 13.751% for training data, 13.773% for test data, and 13.755% for overall data. The MAPE results indicate that the linear regression method can be used to predict the stock price of BRI Bank.
Sistem Pakar Deteksi Penyakit Bawang Merah dengan Metode Case Based Reasoning Yohani Setiya Rafika Nur; Auliya Burhanuddin; Dasril Aldo; Widya Lelisa Army
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 3 (2022): Juli 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i3.4180

Abstract

Shallots are tubers commonly consumed by Indonesians. Shallots are one of the three members of the Allium genus that are much-loved and have high economic value. In the process of cultivating shallots susceptible to pests and diseases. Onion caterpillars, leaf flies, earthworms, purpura, fusarium wilt, onion mosaic and leaf spot are some of the pests and diseases that often attack shallot plants. Farmers will immediately give pesticides or methods that are sometimes not suitable for pests and diseases that attack. As a result, maintenance is not optimal and new pests or diseases often arise. This study aims to help farmers find early symptoms of shallot pests and diseases, so that pest and disease control is more optimal and on target. Processed as many as 10 attack data using Case Based Reasoning method. This method will process data in the form of symptoms seen in shallots, so that they can detect types of pests and diseases of shallots and their handling steps with 100% accuracy. Therefore, this method is relevant for the identification of shallot disease
Rancang Bangun Aplikasi Aplikasi Iuran Sampah RT/RW Menggunakan Metode Rapid Application Development Berbasis Android Aditya Pratomo Sutrisno; Ariq Cahya Wardhana; Auliya Burhanuddin
JURIKOM (Jurnal Riset Komputer) Vol 9, No 4 (2022): Agustus 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i4.4185

Abstract

RT047/RW008 or Jl. Aries is a Neighborhood Association located in Sungai Besar Village, Banjarbaru City, South Kalimantan province. Within this RT environment, weekly and monthly activities are often held. One of the activities in this area is the monthly waste fee. This activity has been around for a long time when this environment was formed. However, in this monthly waste fee activity, we still use the recording method by recording data on a physical citizen membership fee card. In addition, the manufacture of this garbage contribution card still uses the service of making a contribution card which requires traveling and also incurs some costs. In the process of monthly waste contribution activities, it often results in the loss or damage of the citizen membership dues card, in which the treasurer has to make another card at the contribution card making service. Based on the problems found, a solution to the problem that can be found is to design an Android-based application that can run on Android Smartphone devices. This application will be designed using the Rapid Application Development method which will go through the process of data collection to application design. This application can perform the administrative process of digital waste dues. In addition, in the application there is also a reminder feature that will be sent to Whatsapp for every registered member of the group. Because this application runs on Android Smartphone devices, it can make it easier for users to input data and change data anywhere and anytime. The method used for designing this application is to analyze to find out what is needed in an application that you want to build. The final result of the implementation process in the form of Java programming and test results by users. By using the white box testing and black box testing methods, the result is that the application can run well and in accordance with the needs required by the user. With this android application, the RT environment can be more focused and become an RT that can be in line with current technological developments
Analisis Aksesibilitas 10 Website E-Commerce Menggunakan Metode Fuzzy Analytical Hierarchy Process dan Simple Additive Weighting Zhafirah Zhafirah; Auliya Burhanuddin; Dwi Januarita
Journal of INISTA Vol 4 No 2 (2022): Mei 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/inista.v4i2.532

Abstract

Perkembangan e-commerce cukup pesat di kalangan masyarakat Indonesia. Aksesibilitas merupakan faktor penting untuk pengukuran kualitas dan perkembangan website e-commerce yang bertujuan memberikan kenyamanan pada user. Dalam pengukuran kualitas, pengambil keputusan seringkali kesulitan menentukan bobot kriteria yang bersifat subjektif. Untuk mengatasi hal tersebut, diperlukan metode yang memperhatikan kriteria yang bersifat subjektif melalui penilaian oleh pakar. Fuzzy Analytical Hierarchy Process (FAHP) digunakan untuk menentukan bobot kriteria yang bersifat subjektif dan metode Simple Additive Weighting (SAW) digunakan untuk melakukan penjumlahan dari bobot yang sudah dihasilkan. Input utama dalam penelitian ini adalah penilaian para pakar sebagai pengambil keputusan yang bersifat subjektif dengan data 10 website e-commerce yaitu Tokopedia, Shopee, Bukalapak, Lazada, Blibli, Orami, Ralali, Bhinneka, JD.ID dan Zalora. Dari penelitian ini dihasilkan analisis kualitas website e-commerce terbaik berdasarkan aksesibilitasnya yaitu website Bukalapak memperoleh nilai jumlah akhir tertinggi yaitu 0,83 dan menduduki peringkat pertama, sedangkan website JD.ID memperoleh nilai jumlah akhir terendah yaitu 0,12 dengan posisi peringkat terakhir. Permasalahan yang paling banyak muncul pada WCAG 2.1 A 4.1.2 Bagian 508 (2017) A 4.1.2 mengenai label kosong sehingga perlu ditambahkannya label untuk kontrol terkait agar mudah dipahami oleh pengguna/user.
Sistem Pendukung Keputusan Pemilihan Tujuan Wisata Di Cilacap Menggunakan Metode Weighted Product Hasan Nizar; Auliya Burhanuddin; Diandra Chika Fransisca
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 12, No 3 (2023): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v12i3.5234

Abstract

Penelitian ini dilatar belakangi permasalahan yang sering muncul untuk wisatawan yaitu masih merasa kurang puas karena  pemilihan  obyek  wisata kurang sesuai dengan keinginan. Akibatnya, calon wisatawan  hanya  mengunjungi  obyek-obyek  wisata yang menurut orang lain bagus padahal  belum tentu kriteria sesuai yang diinginkan. Tujuan dari penelitian ini adalah membuat sebuah sistem pendukung keputusan yang mampu memberikan rekomendasi wisata terbaik di Kabupaten Cilacap sesuai keinginan pengguna. Kriteria yang digunakan adalah harga tiket masuk, kelengkapan fasilitas, jarak wisata dengan terminal kota Cilacap dan Nilai review wisata. Metode yang digunakan adalah Weight Product dengan proses awal pemberian bobot pada tiap kriteria dan bobot tersebut kemudian di normalisasi untuk selanjutnya mencari nilai Vektor S dan Vektor V. Penelitian ini akan berbentuk web. Hasil dari perhitungan sistem dan perhitungan manual mengeluarkan rekomendasi wisata yang sesuai. Sistem ini menghasilkan kesimpulan dari hasil perankingan sistem tersebut, maka didapatkan hasil 5 wisata terbaik dengan inputan bobot kepentingan Harga Tiket Masuk Murah, Kelengkapan Fasilitas Cukup Lengkap, Jarak dari Terminal Kota Sangat Dekat dan Nilai Review Baik adalah 1. Benteng Pendem sebesar 5,243%, 2. Hutan Manggroove/ Payau Kampung laut sebesar 5,209%, 3. Pantai Pasir Putih Nusakambangan sebesar 5,093%, 4. Wisata Hutan Payau sebesar  4,926% dan Pantai Teluk Penyu sebesar  4,673%.
Sistem Pakar dalam Identifikasi Penyakit Pada Ikan Nila dengan Menggunakan Metode Forward Chaining dan Certainty Factor Alifta Salma Shafira; Auliya Burhanuddin; Diandra Chika Fransisca
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 11, No 3 (2022): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v11i3.3788

Abstract

Ikan nila merupakan salah satu jenis ikan air tawar yang melimpah dan mudah dibudidayakan karena pertumbuhannya yang sangat cepat. Salah satu kendala dalam pengembangan budidaya ikan nila adalah sulitnya pengendalian hama dan penyakit ikan nila. Petani ikan nila di desa tidak mengetahui penyakit ikan, oleh karena itu, diperlukan seorang ahli di bidang ini. Namun menggunakan tenaga ahli atau ahli ikan tentunya akan menimbulkan masalah, salah satunya terbatasnya ketersediaan di suatu daerah, dan biaya yang cukup besar. Tujuan dari penelitian ini adalah untuk membuat sistem pakar untuk mengidentifikasi penyakit pada ikan nila. Tujuan penggunaan sistem pakar adalah sistem yang berusaha mengadopsi atau menyerupai pengetahuan manusia (ahli) ke komputer. Metode yang digunakan untuk mengidentifikasi penyakit pada ikan nila dalam penelitian ini adalah metode forward chaining dan metode certainty factor. Metode forward chaining digunakan karena penelitian ini akan dimulai dengan beberapa fakta dari pengguna kemudian diproses oleh sistem. Metode certainty factor digunakan untuk mengatasi ketidakpastian. Data yang digunakan merupakan hasil wawancara dengan pakar ikan nila. Alur kerja sistem diawali dengan menginputkan gejala pada ikan, selanjutnya akan masuk ke proses forward chaining untuk menentukan penyakitnya. Kemudian masuk ke certainty factor dan hasilnya berupa diagnosis penyakit serta solusinya. Hasil akurasi sistem juga cukup memuaskan sebesar 91.67% dari total pengujian yang telah dilakukan
Co-Authors Ade Riyani Aditya Pratomo Sutrisno Aditya Wijayanto Aditya, Ashwin Nanda Alifta Salma Shafira Alika, Shintia Dwi Amalia Beladinna Arifa Andi Widiyanto Andi Widiyanto Apri Junaidi, Apri Apriliana, Dian Apriliana, Dian Ariq Cahya Wardhana Aufa Salsabila Nahrowi Dasril Aldo Dewisita, Nurprastia Amanda Dewisita, Nurprastia Amanda Diandra Chika Fransisca Dwi Januarita Emilya Ully Artha Endah Ratna Arumi, Endah Ratna Fatmala, Fungki Febriani, Atik GITA FADILA FITRIANA Hasan Nizar Indriyati, Rini Janur Syah Putra Khusnul Fauziah Mahendra, Yonny Danies Mahendra, Yonny Danies Mochammad Hanif Muhammad Zidny Naf'an Mukhtar Hanafi Nuryanto Nuryanto Nuryanto Nuryanto Nuryanto, Nuryanto Paradise, Paradise Ramadhani, Rima Dias Rendi Putra Pradana Ridho Ananda Rifki Adhitama, Rifki Rochman Beny Riyanto Rosa Mustika Dina Uky Yudatama, Uky Utami, Annisaa Vyan Martha, Aldo Wahyu Adi Prabowo Wibowo, Fahrudin Mukti Widya Lelisa Army Yohani Setiya Rafika Nur Zhafirah Zhafirah