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All Journal Teknomatika: Jurnal Informatika dan Komputer
Nafisa Alfi Sa'diya
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Computer Science & IT

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Membangun Sistem Informasi Presensi Kuliah Berbasis NFC di Prodi Informatika Unjani Yogyakarta Iklil Hisanah; Arif Himawan; Titik Rahmawati; Nafisa Alfi Sa'diya
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.v13i1.1110

Abstract

The Unjani Yogyakarta campus, specifically the Informatics Study Program, currently relies on manual methods such as calling students individually or using journal book signatures for attendance. This approach has drawbacks, including flexible attendance time, time-consuming procedures, and potential disruptions to student focus during lectures. To address these issues, the author conducted research to develop a student attendance information system for the campus. The system utilizes a client-server architecture and incorporates NFC technology on Android smartphones and RFID cards. The research aims to establish fixed attendance times and enable digital attendance through Android devices. It also facilitates monitoring of lecture activities for program administrators by integrating mobile and web applications. The system, developed using JAVA for mobile clients and PHP with CodeIgniter and Bootstrap for the web server, was built using the Research and Development method. The resulting student attendance application streamlines the attendance process for program administrators and lecturers. However, it should be noted that the system relies heavily on an internet connection and can serve as an alternative for online classroom attendance.
Rancang Bangun Sistem Peringatan Dini Bencana Banjir Di Kabupaten Madiun Berbasis Website Dan SMS Gateway Menggunakan Mikrokontroller Arduino Halillur Nur Afandi; Landung Sudarmana; Dayat Subekti; Nafisa Alfi Sa'diya
Jurnal Teknomatika Vol 13 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.v13i2.1111

Abstract

Madiun Regency is one of the districts on the island of Java, precisely in the province of East Java. Based on research from the Center for Volcanology and Geological Disaster Mitigation (PVMBG), Madiun City has several potential disasters, one of which is flooding with a high category. This is because Madiun Regency has two streams, namely Kali Sono and Kali Piring which head up on the slopes of Mount Wilis, Madiun Regency. Both times it ended in the Jerohan River in the Balerejo District, Madiun Regency which is a tributary of the Bengawan Madiun River. When heavy rains fell, parts of Madiun City were immediately inundated by flood waters. To anticipate floods, this research proposes a prototype design of a flood disaster early warning system using multiple sensors based on the Global System for Mobile Communications (GSM) in Madiun Regency. Which in the design uses the waterfall and Arduino methods. The prototype built is able to provide early warning information. The data that has been taken can be displayed on the web which functions as a monitoring system, so that officers can carry out supervision more easily and take action when the situation is dangerous. With the prototype and the system made, it is expected to be able to minimize losses caused by floods.
Aplikasi Android Pencarian Coffee Shop Terbaik Menggunakan Metode Weighted Product Nina Hasbiyah; Muhammad Rifqi Ma’arif; Andika Bayu Saputra; Nafisa Alfi Sa'diya
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.v14i1.1112

Abstract

Coffee Shop is a place to gather and relax with family, friends, relatives to enjoy the weekend or just to unwind from the activities that have been carried out. Currently, there are many coffee shops in Sleman that provide products at affordable prices and comfortable places, so that many students make coffee shops an alternative place to complete assignments. However, many people still ask about the Coffee Shop along with detailed information such as taste, price, service, atmosphere, and distance. The Weighted Product method is one of the weighting methods, where multiplication is used to connect attribute ratings, and the rating of each attribute must be raised first with the weight of the attribute in question. The results of this study are in the form of an Android application to find the best Coffee Shop using the Weighted Product method so that it can make it easier for people to choose a Coffee Shop based on the selected criteria. The application is built using the Dart programming language and utilizes the Flutter framework and MySQL as a database management system.
Analisis Forensik Digital Pada Komentar Youtube Live Menggunakan Sentiment Analysis Uning Kristiana; Alfirna Rizqi Lahitani; Chanief Budi Setiawan; Nafisa Alfi Sa'diya
Jurnal Teknomatika Vol 15 No 1 (2022): 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.v15i1.1115

Abstract

The development of increasingly sophisticated technology can have a positive influence on various aspects of our daily lives. From the survey results of the Indonesian Internet Services Association (APJII) in the second quarter of 2019-2020, it shows that Internet users of the operator spend more time watching online videos. Youtube video content watching is open to the public and all ages can freely watch it. However, the content and comments are not necessarily suitable for audiences of all ages to read. Of course, Youtube video content can also affect behavior, especially minors.The purpose of this research is to conduct digital forensic analysis on Youtube Live Comments using sentiment analysis.The research method used applies the NIST SP 800-86 method, namely Collection, Examination, Analysis, and Reporting. Sentiment analysis resulted in 0.01 in the comments on the two videos tested, namely the PUBG and Free Fire video games. Sentiment analysis resulted in 0.01 in the comments on the two videos tested, namely the PUBG and Free Fire video games.
Analisis Sentimen dan Klasifikasi Terhadap Tren “UU ITE” di Media Sosial Twitter Risky Setyadi Putra; Muhammad Habibi; Aris Wahyu Murdiyanto; Nafisa Alfi Sa'diya
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.v14i2.1116

Abstract

Undang-undang Informasi and Transaksi Elektronik abbreviated UU ITE is a law that regulates information and electronic transactions, or information technology in general. This study discusses sentiment analysis from tweet data with keywords “UU ITE” Who uses as much data 7.407 tweet data and re-tweets taken in the period July 21 - August 16, 2021, with details 914 data that has been manually labeled and 6,493 data labeled using Predicting that the data was taken using authentication on the Twitter API and executed using the Python library. This research uses methods Support Vector Machine because it has several advantages including It is capable of handling the classification of two classes, and its implementation is relatively easy. For the support vector machine stage, namely data retrieval, preprocessing data, manual labeling, data training and testing. As for the solution offered in this research is to create an analysis model that can be used to conduct sentiment analysis about the ITE Law on social media Twitter. This research was successful using the Support Vector Machine method to create a sentiment analysis model with an accuracy of 81.20% for data Training and 87% for data testing. This study provides results that UU ITE have negative sentiments by netizens on social media Twitter based on on the results of classification and calculations on the model and tweet data and the number of Negative discussions.
Analisis Sentimen Kepuasan Pelanggan Perusahaan Telekomunikasi Seluler Telkomsel di Twitter Melia Haerunnissa; Agung Priyanto; Choerun Asnawi; Nafisa Alfi Sa'diya
Jurnal Teknomatika Vol 15 No 2 (2022): 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.v15i2.1117

Abstract

Telkomsel, the largest operator in Indonesia with the most users, collects a significant amount of tweet data on Twitter, containing both positive and negative feedback about their internet service. Analyzing this data can provide valuable insights and accurate information about Telkomsel's internet services based on user tweets, retweets, and comments. The aim is to build a sentiment analysis model to extract relevant information from Telkomsel users' tweets on Twitter, serving as feedback for service evaluation and an educational tool for users. The sentiment analysis process involves data retrieval, preprocessing, training, testing, classification, and visualization using Python programming with the Flask framework. Analysis of customer satisfaction sentiment reveals that Telkomsel has a negative sentiment, with an accuracy of 81.7% for training data and 84% for testing data. The sentiment analysis model was built using the Naive Bayes Classification method.
Sistem Pakar Untuk Mendiagnosa Penyakit Degeneratif Pada Lanjut Usia Menggunakan Metode Certainty Factor Berbasis Web Agung Dwi Saputra; Choerun Asnawi; Andika Bayu Saputra; Nafisa Alfi Sa'diya
Jurnal Teknomatika Vol 16 No 1 (2023): 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.v16i1.1118

Abstract

Elderly is a natural process that undergoes organ changes that ultimately affect the state of the function and ability of the body as a whole. Degenerative diseases that occur in the elderly accompany the aging process in a person. This study aims to diagnose degenerative diseases in the elderly with an expert system.The Expert System which was built to diagnose degenerative in the elderly using the CF method aims to trace the symptoms displayed in the form of questions in order to diagnose diseases with web-based software.Expert system software can recognize degenerative diseases in the elderly experienced by users after answering some of the questions displayed by the application.The expert system designed can diagnose degenerative causes in the elderly because in this expert system knowledge is given in the form of symptoms that are used as input to the user.
Metode Hybrid Menggunakan Pendekatan Lexicon Based dan Naive Bayes Classifier Untuk Analisis Sentimen Terkait Jaminan Hari Tua Rizky Fauzi Akbar; Muhammad Habibi; Puji Winar Cahyo; Nafisa Alfi Sa'diya
Jurnal Teknomatika Vol 16 No 2 (2023): 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.v16i2.1247

Abstract

Badan Penyelenggara Jaminan Sosial (BPJS) Ketenagakerjaan adalah badan aturan publik yang dibuat melalui Undang-Undang No 24 Tahun 2011 Tentang Badan Penyelenggaran Jaminan Sosial menggunakan tujuan untuk mewujudkan terselenggaranya pemberian jaminan terpenuhinya kebutuhan dasar yang layak bagi setiap peserta atau anggota keluarganya. Dalam pelaksanaannya terdapat informasi yang tersebar khususnya pada tweet di Twitter mengenai keputusan Kementrian Kesehatan yaitu mengenai Jaminan Hari Tua (JHT) yang hanya bisa dicairkan/diambil setelah peserta (BPJS) Ketenagakerjaan menginjak usia 56 tahun, menyebabkan adanya pro dan kontra yang ada dikalangan masyarakat. Berdasarkan tweet-tweet pada Twitter yang belum dianalisis maka perlu di analisis secara mendalam untuk mendapatkan informasi yang sesuai berdasarkan opini netizen. Berdasarkan hasil penelitian ini diperoleh nilai akurasi data testing sebesar 92% untuk metode Lexicon Based dan 95% untuk data testing pada metode Naïve Bayes Classifier lalu untuk data training Naïve Bayes Classifier mendapatkan akurasi 82%. Penelitian ini mendapatkan kesimpulan bahwa jaminan hari tua (JHT) pada (BPJS) Ketenagakerjaan mendapat sentimen negatif dari netizen yang banyak membahas mengenai penolakan peraturan baru dimana jaminan hari tua (JHT) pada (BPJS) Ketenagakerjaan, hanya bisa dicairkan atau diambil ketika peserta BPJS Ketenagakerjaan menginjak usia 56 tahun.
Co-Authors Agung Dwi Saputra Agung Priyanto Arif Himawan Aris Wahyu Murdiyanto Chanief Budi Setiawan Choerun Asnawi dayat subekti Halillur Nur Afandi Iklil Hisanah Lahitani, Alfirna Rizqi Landung Sudarmana Melia Haerunnissa Muhammad Habibi Muhammad Rifqi Ma’arif Nina Hasbiyah Puji Winar Cahyo Risky Setyadi Putra Rizky Fauzi Akbar Saputra, Andika Bayu Titik Rahmawati Uning Kristiana