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All Journal Sainteks Jurnal Teknologi dan Manajemen Informatika Jurnal Informatika Telematika SMATIKA Jurnal Ilmiah KOMPUTASI Jurnal Pendidikan Informatika dan Sains INTEGER: Journal of Information Technology JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Pendas : Jurnah Ilmiah Pendidikan Dasar Jurnal Teknoinfo Martabe : Jurnal Pengabdian Kepada Masyarakat Digital Zone: Jurnal Teknologi Informasi dan Komunikasi JURTEKSI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) EDUMATIC: Jurnal Pendidikan Informatika JSAI (Journal Scientific and Applied Informatics) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Teknologi Dan Sistem Informasi Bisnis Zonasi: Jurnal Sistem Informasi Jurnal Tekinkom (Teknik Informasi dan Komputer) Journal of Computer System and Informatics (JoSYC) Infotek : Jurnal Informatika dan Teknologi Indonesian Journal of Cultural and Community Development Community Empowerment Jurnal Abdimas Serawai Jurnal Abdimas Indonesia : Jurnal Abdimas Indonesia Bulletin of Computer Science Research Indonesian Journal of Innovation Studies Indonesian Journal of Public Policy Review Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) PELS (Procedia of Engineering and Life Science) Procedia of Social Sciences and Humanities Prosiding University Research Colloquium Malcom: Indonesian Journal of Machine Learning and Computer Science JOINCS (Journal of Informatics, Network, and Computer Science) STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer SAGA: Journal of Technology and Information Systems "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Komunita: Jurnal Pengabdian dan Pemberdayaan Masyarakat Innovative Technologica: Methodical Research Journal Physical Sciences, Life Science and Engineering Indonesian Journal of Applied Technology Journal of Social Comunity Services Journal of Technology and System Information Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Journal for Technology and Science semanTIK Jurnal Farmasi Galenika IJHCS Smatika Jurnal : STIKI Informatika Jurnal Academia Open
Ade Eviyanti
Informatika, Fakultas Sains Dan Teknologi, Universitas Muhammadiyah Sidoarjo, Indonesia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Other

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Rancang Bangun Sistem Informasi Penjualan Pakan Ternak Berbasis Web Menggunakan Framework Laravel Kurniawati, Indah; Eviyanti, Ade
Indonesian Journal of Applied Technology Vol. 1 No. 1 (2024): January
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ijat.v1i1.3094

Abstract

Dalam konteks kemajuan teknologi yang semakin cepat, sangat penting bagi entitas bisnis untuk mengadopsi komputerisasi untuk mengurangi atau menghilangkan keterlambatan, kesulitan, dan ketidakefisienan yang melekat dalam proses manajemen informasi tradisional. Hal ini terlihat dalam metode konvensional yang masih digunakan dalam pembelian dan penjualan pakan hewan, yang tidak memenuhi tuntutan layanan pelanggan modern. Untuk mengatasi tantangan ini, sebuah sistem informasi penjualan pakan hewan dikembangkan menggunakan kerangka kerja Laravel. Sistem tersebut dibangun mengikuti metode waterfall, yang mencakup tahapan perencanaan, pemodelan, konstruksi, dan pengiriman sistem perangkat lunak kepada pelanggan/pengguna, yang diakhiri dengan fase pemeliharaan untuk aplikasi tersebut. Temuan dari penelitian ini menunjukkan bahwa implementasi sistem informasi berbasis website untuk pencatatan penjualan pakan hewan secara signifikan memperlancar berbagai proses transaksi di Toko Budi Jaya.
Implementasi Data Mining Dalam Melakukan Prediksi Penyakit Diabetes Menggunakan Metode Random Forest Dan Xgboost Salsabil, Muhammad; Azizah, Nuril Lutvi; Eviyanti, Ade
Jurnal Ilmiah Komputasi Vol. 23 No. 1 (2024): Jurnal Ilmiah Komputasi : Vol. 23 No 1, Maret 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.23.1.3507

Abstract

Penyakit diabetes telah menjadi isu global dalam bidang kesehatan. Penelitian ini berfokus pada implementasi dua teknik data mining yaitu Random Forest dan XGBoost untuk memproyeksikan perkembangan penyakit diabetes. Kedua metode ini memanfaatkan dataset klinis dan biokimia yang terkait dengan diabetes. Setelah fase preprocessing, dilakukan evaluasi performa menggunakan metrik evaluasi seperti akurasi, presisi, recall dan f1 score. Dataset yang digunakan sebanyak 768 entri dan 9 indikator yang diperoleh dari platform Kaggle. Dalam Penelitian ini data diolah melalui tahap preprocessing diantaranya handling missing value, handling outlier dan normalisasi data, dan didapatkan data yang akan diolah sebesar 688. Setelah didapat data hasil preprocessing, dilakukan tahapan pelatihan dan pengujian dengan Cross Validation dan dilakukan pengujian untuk mengetahui parameter-parameter terbaik yang akan digunakan, lalu dilakukan evaluasi kinerja model Random Forest dan XGBoost menggunakan metrik akurasi, presisi, recall, dan F1-score. Hasil evaluasi model menunjukkan performa yang baik dalam penelitian ini, didapatkan hasil akurasi keseluruhan dalam penggunaan random forest sebesar 74% dan penggunaan XGBoost sebesar 76%.Penyakit diabetes telah menjadi isu global dalam bidang kesehatan. Penelitian ini berfokus pada implementasi dua teknik data mining yaitu Random Forest dan XGBoost untuk memproyeksikan perkembangan penyakit diabetes. Kedua metode ini memanfaatkan dataset klinis dan biokimia yang terkait dengan diabetes. Setelah fase preprocessing, dilakukan evaluasi performa menggunakan metrik evaluasi seperti akurasi, presisi, recall dan f1 score. Dataset yang digunakan sebanyak 768 entri dan 9 indikator yang diperoleh dari platform Kaggle. Dalam Penelitian ini data diolah melalui tahap preprocessing diantaranya handling missing value, handling outlier dan normalisasi data, dan didapatkan data yang akan diolah sebesar 688. Setelah didapat data hasil preprocessing, dilakukan tahapan pelatihan dan pengujian dengan Cross Validation dan dilakukan pengujian untuk mengetahui parameter-parameter terbaik yang akan digunakan, lalu dilakukan evaluasi kinerja model Random Forest dan XGBoost menggunakan metrik akurasi, presisi, recall, dan F1-score. Hasil evaluasi model menunjukkan performa yang baik dalam penelitian ini, didapatkan hasil akurasi keseluruhan dalam penggunaan random forest sebesar 74% dan penggunaan XGBoost sebesar 76%.
Prediksi Kelayakan Pemberian Kredit Menggunakan Metode Random Forest Firmansah, Noval; Uce Indahyanti; Ade Eviyanti
Jurnal Ilmiah Komputasi Vol. 22 No. 4 (2023): Jurnal Ilmiah Komputasi : Vol. 22 No 4, Desember 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.22.4.3515

Abstract

Penelitian ini menggunakan data dari Kaggle, yang terdiri dari 32,581 baris dan 12 kolom, untuk mengembangkan model prediksi kelayakan kredit. Tujuan penelitian adalah mengidentifikasi faktor-faktor yang memengaruhi kelayakan kredit dan mengembangkan model yang akurat dalam memprediksi apakah seorang peminjam layak atau tidak menerima kredit. Penelitian melibatkan langkah-langkah pra-pemrosesan data, termasuk imputasi missing value dan penanganan outlier, serta pembagian dataset menjadi data latih dan data uji. Hasil menunjukkan bahwa model mencapai akurasi sebesar 93,28%, dengan parameter terbaik 'max_depth': 30, 'min_samples_leaf': 1, 'min_samples_split': 2, dan 'n_estimators': 100. Penelitian ini memberikan kontribusi dalam pemahaman kelayakan kredit dan pengembangan model prediksi yang dapat digunakan oleh lembaga keuangan untuk pengambilan keputusan kredit yang lebih tepat.
Penerapan Algoritma Support Vector Machine untuk Memprediksi Tingkat Partisipasi Pemilu terhadap Kualitas Pendidikan Anggraeni, Anifah Warda; Fitrani, Arif Senja; Eviyanti, Ade
Jurnal Pendidikan Informatika (EDUMATIC) Vol 8 No 1 (2024): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v8i1.24838

Abstract

Elections are a democratic means of choosing leaders. Public participation in elections is important for a healthy democracy. The quality of education influences public participation in elections. Therefore, the government needs to improve the quality of education in the Pasuruan Regency area. This research aims to predict the level of participation in elections on the quality of education in Pasuruan Regency. This research uses the Education sector dataset obtained from BPS data for Pasuruan Regency in 2022 and the level of election participation obtained from the recapitulation of the 2019 election results. Data analysis was carried out in an experimental stage to determine the variables to be predicted (target variables) and the variables used to predict it (predictor variable) using the Support Vector Machine (SVM) algorithm with three kernels, namely linear, rbf, and polynomial. The findings show an accuracy of 88.4% for the linear kernel, 88.5% for the rbf kernel, and 88.5% for the polynomial kernel. The quality of education can influence the level of election participation. This is because high quality education can increase public awareness of the importance of participating in elections.
DEVELOPMENT OF VERTICAL CULTURE CULTIVATION IN THE MUHAMMADIYAH STUDENT ASSOCIATION OF CANDI Abror, M.; Miftakhurrohmat, A.; Prihatiningrum, Andriani Eko; Eviyanti, Ade
Journal of Social Comunity Services Vol. 1 No. 3 (2024): Journal of Social Comunity Services (JSCS)
Publisher : Antis-publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61796/jscs.v1i3.181

Abstract

General Background: Food security and independence are critical issues in urban environments, where limited land poses challenges for traditional agriculture. Specific Background: Vertical culture cultivation has emerged as a potential solution to optimize narrow land for agricultural purposes, but its application remains underutilized in many communities. Knowledge Gap: While many individuals possess basic agricultural knowledge, there is limited familiarity with vertical culture systems, particularly among youth organizations such as the Muhammadiyah Student Association (IPM) in Candi District. Aims: This community service program aimed to improve participants' understanding and skills in vertical culture cultivation to support food independence on narrow land. Results: Through a structured process of socialization, training, and mentoring, participants gained the ability to design and implement vertical culture systems, leading to improved agricultural productivity in terms of both quantity and quality of harvests. The program's evaluation showed a significant increase in participant knowledge and the successful adoption of vertical farming techniques. Novelty: This program uniquely demonstrates the integration of technology and sustainable practices in vertical cultivation, providing a practical and scalable model for urban agriculture. Implications: The success of this initiative highlights the potential for vertical culture cultivation to contribute to food security in urban areas, with opportunities for further development through continuous innovation and broader community engagement. This program serves as a blueprint for future urban agricultural efforts, offering a sustainable approach to maximizing the use of narrow land in densely populated regions.
SISTEM PAKAR REKOMENDASI JURUSAN MENGGUNAKAN METODE FORWARD CHAINING Erika Anjani Putri; Ade Eviyanti; Hindarto Hindarto
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.1071

Abstract

SMK Antartika 2 Sidoarjo provides instruction in seven different areas of competence. With so many choices of majors, it causes several problems in choosing majors, including not in accordance with interests, or not knowing their interests and potential. Expert Systems are one part of artificial intelligence that is created to help make decisions in solving problems like experts. The Forward chaining method provides conclusions that begin by using rules that relate facts. The Department Recommendation Expert System using the Forward chaining method that was built runs well. This system is designed to assist new SMK students in determining the majors to be taken according to the talent interests of new students by providing department recommendations, based on the results of testing department recommendations in the system with the same results of determining the majors of interest resulting in a percentage of 90%. Based on black box testing that has been carried out on this system in accordance with what was expected by 40 respondents, the percentage of department recommendations was 89.33%, and ease of access was 93.33%. The expert system is made based on a website that can be accessed online and can be used at any time.
PENGEMBANGAN ARTIFICIAL INTELLIGENCE BERUPA VIRTUAL ASSISTANT MOBILE MENGGUNAKAN FRAMEWORK FLUTTER Reyhan Haqiqi Alif Fourniawan; Ade Eviyanti; Suhendro Busono
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1169

Abstract

Various technologies have been developed today, with Artificial Intelligence (AI) being a prime example. This technology has had a significant impact on our lives, assisting in tasks, jobs, and everyday activities. In this research, an artificial intelligence-based virtual assistant will be developed to facilitate and complete tasks. This artificial intelligence takes the form of a virtual assistant that answers user's questions. This artificial intelligence will be helpful in various fields, including healthcare, economics, education, technology, and more. Additional-ly, the development will focus on a mobile platform to make it user-friendly. Developing an AI-based virtual assistant on a smartphone or mobile platform is highly relevant to the current technological advancements. With this virtual assistant, users can access information or assis-tance anytime, anywhere, making it a practical solution in daily life. Furthermore, in the de-velopment of this virtual assistant, it has already undergone testing using the black-box meth-od. In these tests, the virtual assistant application has successfully passed testing for both its user interface and all of its features.
SISTEM INFORMASI PENGAWASAN TAMAN KOTA PADA DINAS LINGKUNGAN HIDUP DAN KEBERSIHAN KABUPATEN SIDOARJO Achmad Alfian Fajriansyah; Nuril Lutvi Azizah; Ade Eviyanti
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.909

Abstract

Utilization of Information Technology at the Sidoarjo Regency Environment and Hygiene Service has a positive impact on service progress. Computerized systems create a very important part of today's technological advances and ease of communication. For this reason, the author wants to develop a computer system that can facilitate the work of the Sidoarjo Regency Environment and Sanitation Service to meet the needs expected by the environmental service or the community for the Sidoarjo city's landscaping environment. The goal obtained from this urban park monitoring information system is that people do not need to come to the environmental service office to do reporting and complaints if there is a park in the Sidoarjo area that needs to be fixed. The technique used in this application is the waterfall method and uses the codeigniter framework. the result of user testing is 68% with the highest observation aspect, namely whether the city park monitoring information system makes it easier for people to mix about landscaping in the Sidoarjo area.
PENGEMBANGAN TEKNOLOGI OPTICAL CHARACTER RECOGNITION DI FLUTTER BERUPA DETEKSI TEKS PADA GAMBAR Shierly Mayco Angela; Ade Eviyanti; Metatia Intan Mauliana
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1167

Abstract

This research aims to develop Optical Character Recognition (OCR) technology integrated with the Flutter platform to detect text in images in mobile applications. OCR technology allows extracting text from images automatically, eliminating the need for manual intervention, and is implemented using the Tesseract OCR library which is known to have a high level of accuracy. By combining Flutter, a multi-platform application development framework developed by Google, this research produces an application that is able to detect text from images taken via the kamera or cell phone gallery with fast response and high accuracy. The Rapid Application Development (RAD) approach was used in developing this system. Research stages include requirements planning, system design, system development, and implementation. System testing is carried out using the Black box testing method to ensure all features work according to specifications, as well as User Acceptance Testing (UAT) to assess user satisfaction. The test results show that the application runs well and is accepted by users with a strongly agree level of approval (88%). This research contributes to creating an efficient and intelligent mobile application for detecting text in images, which can be used for various purposes, such as searching for digital comic references, detecting text on food menus, and identifying vehicle number plates.
IMPLEMENTASI ALGORITMA APRIORI UNTUK MENENTUKAN POLA PEMBELIAN PADA KOLEGA COFFEE via nabila banda; Ade Eviyanti; Uce Indahyanti
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.1103

Abstract

Kolega Coffee is one of the coffee shops that sells a variety of coffee variants and other menus. The sold menus will be recorded in the sales system for the sales report. The increasing number of visitors generates a lot of sales transaction data. And the data only serves as sales reports and archives. However, if the data is processed further, it will acquire new information for decision-making in business strategy. The research aims to find menus that are often purchased simultaneously through sales transaction data from January to June 2023 using a priori algorithm whose rule has the advantage of being able to know patterns of purchasing products at the same time. by defining frequent itemsets that are useful to form association rules. The results of this study resulted in five association rules from 1917 sales transaction data. For example, if someone buys onion rings, they're also likely to buy a mix platter with a 38.33% confidence rate. This study can give advice for business strategies to coffee colleagues for example for promotion of menu packages or other discounts.
Co-Authors Abdiansah, Lutfi Abdul Haris Setya Nugraha Abror, M Abror, M. Achmad Alfian Fajriansyah Achmad Danu Zakaria Adam Putra Addriana Fatma Putri Indah Sari adham Adi Putra, Lutfi Adiffanani Ramdansyah Adilla Syafira Putri Adimas Priyambadha Agil Fajar Dwi Prasetyo Agus Miftakhurrohmat Agustin, Erlina Ahmad Muflih Aisha Hanif Aldo Ardiansyah Aliful Fatikh Pulunggono Suseta Alim, Kholqi Aminy, Ritzana Aisyah Andriani Eko Prihatiningrum Andrinai Eko Prihatiningrum Anggraeni, Anifah Warda Arif Senja Fitrani Arif Senja Fitriani Ayu Anggilina Ayu Dwi Ratna Ningsih Azizah, Nurul Lutfi Azmuri Wahyu Azinar Bisri, Muhammad Anhar Chulloh, Dafid Mizta Cornelius, Cornelius Daffa Fauzanrio Iswinarko Damara, Rivaldi Garindra Damasta, Ifanda Reza Deby Kurniawan Armananda Diba, Naila Farah Dimas Bayu Anjasmara Dimas Sya’aldi Pasa Dini Aprilia Puspitasari Dini Yocta Prabayanti Dona Ardiansyah Donni Adeleo Ardana Dulkarnain, As’ad Dwi Cahyono, Qitfirul Erika Anjani Putri Eriyanto, Sandi Eko Erlina Agustin Faiqotul Himma Ramadhanti Fanani, Muchammad Ichsanuddin Fandy Rachmatulloh Febri Rosita Dewi Feny Anggraeny Firmansah, Noval fitria, Saniya Izza Fitriah Fitriah Fuad Azis Muslim Ghozali, M Fahruddin Ginanjar Agung Sudrajat Gita Wardani Guko, William Yviis Habib Husain Amirullah Hamid, Moch Siddiq Hamza Setiawan Hamzah Setiawan Hazmi Ramadhan Al fatri Hendri Hermawan Hermawan, Tunggal Hibatullah Putra, Dimas Radito Hindarto Hindarto Hindarto Ika Ratna Ika Ratna Indra Astutik Imanda, Almyra Gitta Indah Kurniawati Indrawati, Marcella Jamal Hasan khoirunnisa devita sari Lazuardi, Fajar Lola Herawati Luqmanul Hakiym Maulana M Fahruddin Ghozali Macfhul Indrakurniawan Makhfudzoh, Fury Maulana, Mahardika Rafi Ma’ruf , Mohammad Rizal Metatia Intan Mauliana Miftahurrohmat, A Miftakhurrohmat, A. Moch Alfan Rosyid Moch Siddiq Hamid Mochamad Alfan Rosid Mochammad Alfan Rosid Mochammad Raflie Lazuardi Moh. Attar Jibran Mohammad Fadli Zaka Mohammad Rizal Ma'ruf Muchammad Bagus Sasmita muchammad david mahendra Muhammad Abror Muhammad Alfin Firdiansyah Muhammad Alifiansyah Putra Muhammad Arif Fa’i Muhammad Arshiel Naufal Dzaki Muhammad Fajar Alfian Muhammad Farid Yuliansyah Muhammad Rozzaq Muhammad Zainal Abidin Nahriyan Zidan Bahar Rizqi Naila Adiba Nanda Mujahidah Andini Naufal Raihan naufal Nila Sekardhani Hadian Nisa, Umi Khoirun Nouval Aulia Rachman Novia Ariyanti Novia Ariyanti Nuril Lutvi Azizah Nurul amiroh Octavia, Elga Padova Bima Maldini Pranatadityo, Billy Prasetyana, Dwi Gilang Ramadhan Pratama, Hepi Yoga Pratama, Robby Pratiwi, Rosa Machmuda Putra F, M. Bagus Putra, Fariq Abdillah Maulana Putri, Revanda Silva Astianto Reyhan Haqiqi Alif Fourniawan Rizki, M. Alvan Rohman Dijaya Rukhi Alfian, Muhammad Sabilah, Hasya Saiful Arifin Saiful Arifin Salsabil, Muhammad Saputra, Abhirama Septya Bayu Andita Serlindha Tri Andini Shiddqy Hidayat, Syahril Shierly Mayco Angela Siti Nurjanah Ramadhany Steven Gerrard Suhendro Busno Suhendro Busono Sukma Aji Sumarno , Sumarno Sumarno . Sumarno Sumarno Syaifudin, Hilmi Fajar Sylfanie Sekar Mayang Tasya Gusti Amalia Taurusta, Cindy Teguh Hardianto Putra Teguh Prasetyo Uce Indahyanti Umi Khoirun Nisak Vevy Liansari Vevy Liansari via nabila banda Viarini, Dina Dwi Okta Wardani, Gita Wijaya, Naufal Ariq Wijayanto, Moch Eri Witno, Kasaifi Al Qurdhowi Bin Wulandari, Alidza Septiam Yanita Wardhani Yulian Findawati Yunianita Rahmawati Yuzefa, Hihaniza Lela Zahputra, Aldy Trisza Zaka, Mohammad Fadli Zuyyina Fihayati