Garuda - Garba Rujukan Digital

Penerapan dan pendampingan pengelolaan website sekolah di SMP Negeri 4 Jombang Kartikadyota Kusumaningtyas; Eko Dwi Nugroho; Adri Priadana
KACANEGARA Jurnal Pengabdian pada Masyarakat Vol 4, No 2 (2021): Juli
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/kacanegara.v4i2.870

Internet telah menjadi salah satu media untuk tujuan pemasaran. Salah satu upaya dalam pemanfaatan media internet adalah untuk proses identitas merek atau sering disebut branding digital. Branding digital juga menjadi salah satu cara untuk menjaga eksistensi suatu lembaga pendidikan. SMP Negeri 4 Jombang merupakan salah satu sekolah tingkat menengah pertama yang terletak di Kabupaten Jombang, Jawa Timur. Permasalahan utama yang dihadapi oleh SMP Negeri 4 Jombang adalah terkait promosi melalui media digital yang belum maksimal dan banyaknya informasi yang ingin disampaikan, baik kepada siswa, orang tua, alumni, maupun kepada masyarakat masih belum dapat disampaikan secara maksimal. Mengarah pada permasalahan-permasalahan tersebut, maka diperlukan adanya sebuah website sekolah. Selain itu, diperlukan juga pendampingan pengelolaan website sekolah agar pihak sekolah dapat mengelola website-nya dengan optimal, baik dalam mengisikan konten profil sekolah, maupun dalam mengisikan konten kegiatan atau berita terkait SMP Negeri 4 Jombang. Tahapan pelaksanaan kegiatan ini terdiri dari tiga tahap, yaitu identifikasi masalah, instalasi web sekolah, serta pelatihan dan pendampingan. Hasil dari kegiatan ini adalah peserta dapat melakukan pengelolaan website sekolah dengan baik. Selain itu, dengan adanya website sekolah, maka dapat membantu promosi SMP Negeri 4 Jombang dan juga sebagai sarana penyampaian informasi ke siswa, orang tua, alumni, maupun kepada masyarakat luas.

Data Mining for Determining The Best Cluster Of Student Instagram Account As New Student Admission Influencer Ahmad Irfan Abdullah; Adri Priadana; Muhajir Muhajir; Syahrir Nawir Nur
Telematika Vol 18, No 2 (2021): Edisi Juni 2021
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v18i2.5067

Purpose: This study aims to apply the web data extraction method to extract student Instagram account data and the K-Means data mining method to perform clustering automatically to determine the best cluster of students' Instagram accounts as influencers for new student admissions.Design/methodology/approach: This study implemented the web data extraction method to extract student Instagram account data. This study also implemented a data mining method called K-Means to cluster data and the Silhouette Coefficient method to determine the best number of clusters.Findings/result: This study has succeeded in determining the seven best student accounts from 100 accounts that can be used as influencers for new student admissions with the highest Silhouette Score for the number of influencers selected between 5-10, which is 0.608 of the 22 clusters.Originality/value/state of the art: Research related to the determination of the best cluster of students' Instagram accounts as new student admissions influencers using web data extraction and K-Means has never been done in previous studies.

Metode Accumulative Difference Images untuk Mendeteksi Berhentinya Putaran Kincir Air Aris Wahyu Murdiyanto; Adri Priadana; Aris Wahyu Murdiyanto
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 2 (2021): Mei 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

Vannamei shrimp is one of Indonesia's fishery commodities with great potential to be developed. One of the essential things in shrimp farming is a source of dissolved oxygen (DO) or a sufficient amount of oxygen content, which can be maintained by placing a waterwheel driven by a generator set engine called a generator. To keep the waterwheel running, the cultivators must continue to monitor it in real-time. Based on these problems, we need a method that can be used to detect the cessation of waterwheel rotation in shrimp ponds that focuses on the rotation of the waterwheel. This study aims to analyze the performance of the Accumulative Difference Images (ADI) method to detect the stopped waterwheel-spinning. This method was chosen because compared with the method that only compares the differences between two frames in each process, the ADI method is considered to reduce the error-rate. After all, it is taken from the results of the value of several frames' accumulated movement. The ADI method's application to detect the stopped waterwheel-spinning gives an accuracy of 95.68%. It shows that the ADI method can be applied to detect waterwheels' stop in shrimp ponds with a very good accuracy value.

Analysis and visualization of BPJS on twitter using K-means clustering Andika Bayu Saputra; Puji Winar Cahyo; Muhammad Habibi; Adri Priadana
International Journal of Health Science and Technology Vol 3, No 3 (2022): April
Publisher : Universitas 'Aisyiyah Yogyakarta

Social security agency (BPJS) Health exists to provide national social security to meet the basic needs appropriate for all levels of society based on the principle of humanity. Originated from a change in the contribution premium policy, it is demanded by the organizers and health service providers to be able to provide safe, quality, affordable health facilities. But unfortunately, the government's efforts in realizing public welfare, especially in the field of health, are not fully supported by the community because of the ever- changing premium contribution policy and the health services they receive. The latest information developments related to BPJS on social media that can be easily accessed by the public. One of them is by using the Twitter platform as a place to exchange information using hashtags. The hashtag data can be processed and obtained information to be used as a tool for decision making. This study aims to analyze and visualize BPJS data on the Twitter platform using the K-Means clustering method. K-Means clustering method is a method of clustering data mining using the descriptive model concept. K- means method can use to explain the algorithm in determining an object into a specific cluster based on the nearest average.

Penerapan Metode Radius, Haversine Formula dan Direction pada Sistem Pencarian Kios Penyedia Produk Pertanian Terdekat Rendi Virgian Fajaryantoro; Ferry Wahyu Wibowo; Adri Priadana
Jurnal Teknomatika Vol 12 No 2 (2020): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v12i2.317

Indonesia merupakan negara agraris yang mengandalkan sektor pertanian sebagai sumber mata pencaharian. Usaha untuk meningkatkan produksi pertanian dipengaruhi oleh banyak faktor. Akan tetapi ada beberapa faktor yang sangat tergantung pada upaya yang dilakukan oleh sumber daya manusia, diantaranya penerapan tata cara budidaya yang benar, cara panen yang tepat dan pengolahan pasca panen. Dalam penyebaran informasi baik produk pertanian terkait ataupun lokasi kios masih belum maksimal sehingga dapat menghambat produktivitas pelaku pertanian. Banyaknya kios pertanian serta penyebaran produk yang belum merata membuat bingung petani untuk mencari informasi lokasi kios serta produk yang apa saja yang dijualnya. Penelitian ini bertujuan untuk membangun sistem yang daapt memudahkan pecarian informasi kios pada lokasi terdekat. Penelitian ini memanfaatkan metode radius, harversine formula, dan direction untuk melakukan pencarian. Berdasarkan dari hasil pengujian, sistem ini mampu mencari dan menampilkan informasi kios terdekat berdasarkan produk pertanian yang dijual oleh kios tersebut. Metode radius, harversine formula, dan direction yang diterapkan pada sistem pencarian pada penelitian ini telah berhasil diterapakan dimana menghasilkan nilai akurasi sebesar 100%.

PENERAPAN METODE SURF DAN FLANN UNTUK MENDETEKSI TERBITAN SPAM PADA INSTAGRAM Dwi Sandi Yulianto; Adri Priadana; Andika Bayu Saputra; Fajar Syahruddin
Jurnal Teknomatika Vol 14 No 2 (2021): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v14i2.1125

Social media is a new media that utilizes the internet to share information, interact, participate and others, and to be used with each other. Currently there are many social media circulating, one of which is Instagram. At first Instagram was only used to share photos, then along with the development of technology and media, Instagram also developed into being able to share videos and shop on Instagram. Instagram is also one of the social media specifically used to upload images and videos. The growing use of Instagram in supporting promotion makes Instagram faced with various problems, one of which is the emergence of spam issues. For example, the publication of spam on Instagram is published by several sellers of products or the like continuously. It's good to promote a product. But on the other hand, it will interfere with other users if the spam often appears. This is exacerbated by the mass use of popular hashtags, done with the aim of getting more views. Popular hashtags are hashtags that are followed by many Instagram users. Based on these problems, it takes a computer program to detect spam issues based on certain hashtags on Instagram. In this final task, the Speeded-Up Robust Features (SURF) and Fast Library for Approximate Nearest Neighbor (FLANN) methods will be applied to detect spam publications on Instagram. The results of experiments that have been conducted on 12 images that produce 66 comparisons, the application of SURF and FLANN methods can be said to be very good in detecting the similarity of images between Instagram publications that indicate that the same image is a spam issue, which is with a maximum accuracy value of 100%.

Sistem Pendukung Keputusan Pemberian Beasiswa Kurang Mampu di SMA Negeri 2 Kupang Menggunakan Metode Profile Matching Jonia Nova Da Costa; Adri Priadana; M. Abu Amar Al Badawi
Jurnal Teknomatika Vol 13 No 1 (2020): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v13i1.1126

At SMAN 2 Kupang, the scholarship program for underprivileged students greatly contributes to their educational attainment. Scholarships at SMAN 2 Kupang are awarded based on parents/guardians' income, number of dependents, possession of smart Indonesian cards, and disabilities. However, there is often an issue of inaccurate scholarship distribution. Some students who do not meet the eligibility criteria receive scholarships, while deserving students who are less fortunate do not receive them. To address this problem, we propose a scholarship decision support system utilizing the profile matching method as the calculation algorithm. The system is developed using the PHP programming language and MySQL database. The primary benefit of this system is to assist in the scholarship selection process based on predetermined criteria. The system includes student registration, profile matching calculation, and the ability to generate registration and calculation reports.

APLIKASI MONITORING DATA KETERSEDIAAN SOAL BERBASIS WEB PADA SITUS TANYA JAWAB BRAINLY Moch. Adji Prasetyo; Andika Bayu Saputra; Adri Priadana; Fajar Syahruddin
Jurnal Teknomatika Vol 14 No 1 (2021): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v14i1.1134

Brainly is a website that allows users to ask each other and answer questions related to school lessons openly to other users. On the site, you must first create an account as a questioner or answerer. Brainly harness the power Freelance to answer questions on the Brainly website. In working on the questions carried out by the Brainly Freelancer, there are often delays in updating questions at the Uniform Resource address Locator (URL) assigned to Freelancers. This results in Freelancers often being hampered in their work meet the target of working on the questions because the questions that have been answered are still not replaced with a new question. Therefore, the researcher designed and built an Application for Monitoring Data Availability of Web-Based Questions on the Tanya Site Answer on the Brainly site which aims to make it easier for Brainly Freelancers to meet their target for working on questions. This application is built using the Python programming language by utilizing the Flask framework. The results of this study state that the process contained in the application has been running smoothly as evidenced by the results of black box testing. User testing is done with Brainly Freelancers opening the application and viewing the availability of unanswered questions on the Brainly URL with a table view.

Instagram Hashtag Trend Monitoring Using Web Scraping Priadana, Adri; Murdiyanto, Aris Wahyu
Jurnal Pekommas Vol 5 No 1 (2020): April 2020
Publisher : Sekolah Tinggi Multi Media “MMTC” Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jpkm.2020.2050103

In recent years, Instagram has become one of the fastest growing social media platforms. Searching images on Instagram can be done by using a particular keyword or often known as the hashtag. The hashtag is one of the parameters that can use to find out the topics that are being talked about on social media. There are many advantages for knowing a hot topic on social media to support decision making. This study aims to monitor trends of hashtags on the Instagram platform using web scraping techniques. This research has succeeded in extracting and analyzing post data on Instagram to provide trend information from a #MerryChrismas hashtag. The results of this study are the visible trend in the #MerryChrismas hashtag experienced an increase in the last two days, namely on 24 and 25 December 2019. In addition, this research also succeeded in displaying posts with the most number of likes and comments from a hashtag at a certain time period.

Sistem Pendukung Keputusan Pemberian Beasiswa Kurang Mampu di SMA Negeri 2 Kupang Menggunakan Metode Profile Matching Da Costa, Jonia Nova; Priadana, Adri; Al Badawi, M. Abu Amar
Jurnal Teknomatika Vol 13 No 1 (2020): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v13i1.1126

At SMAN 2 Kupang, the scholarship program for underprivileged students greatly contributes to their educational attainment. Scholarships at SMAN 2 Kupang are awarded based on parents/guardians' income, number of dependents, possession of smart Indonesian cards, and disabilities. However, there is often an issue of inaccurate scholarship distribution. Some students who do not meet the eligibility criteria receive scholarships, while deserving students who are less fortunate do not receive them. To address this problem, we propose a scholarship decision support system utilizing the profile matching method as the calculation algorithm. The system is developed using the PHP programming language and MySQL database. The primary benefit of this system is to assist in the scholarship selection process based on predetermined criteria. The system includes student registration, profile matching calculation, and the ability to generate registration and calculation reports.

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