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All Journal Prosiding Seminar Nasional Teknoka KLIK: Kajian Ilmiah Informatika dan Komputer
Estu Sinduningrum
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Computer Science & IT Engineering

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PENERAPAN PEMBANGKIT LISTRIK TENAGA SURYA DI LAHAN PERTANIAN TERPADU CISEENG PARUNG-BOGOR Rosalina; Estu Sinduningrum
Prosiding Seminar Nasional Teknoka Vol 4 (2019): Prosiding Seminar Nasional Teknoka
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (868.658 KB) | DOI: 10.22236/teknoka.v4i0.4188

Abstract

Tenaga Surya atau sistem photovoltaic dapat dimanfaatkan untuk menghasilkan tenaga listrik. Modul surya dibuat dari bahan semikonduktor yang mengandung partikel electron dan akan meloncatkan arus listrik saat menerima energy kinetic dari cahaya matahari yang mengandung gelombang elektromagnetik. Dalam periode penelitian kali ini prioritas kearah penerapan teknologi konversi energy listrik dari energy cahaya matahari diubah ke listrik, matahari akan mengisi baterai DC dan kemudian akan diubah oleh inverter menjadi AC, metode yang akan digunakan dalam penelitian adalah perhitungan besar sudut matahari terhadap sel matahari persatuan waktu maka akan diketahui lamanya pengisian baterai secara kontinu, sehingga secara otomatis output AC dari baterai sebagai sumber energy listrik yang akan dipakai untuk menyalakan lampu jalan dan perangkat listrik lainnya. Hasil pengujian modul surya (photovoltaic) diharapkan akan mengahasilkan daya perjam = Wh dengan memakai baterai DCMF 12V 70Ah sebesar 840Wh, ini berarti baterai bisa menyediakan ±840 W selama 1 jam.
Perbandingan Deteksi Tepi pada Metode Robinson dan Kirsch Taupik Kamil; Nunik Pratiwi; Estu Sinduningrum
Prosiding Seminar Nasional Teknoka Vol 8 (2023): Proceeding of TEKNOKA National Seminar - 8
Publisher : Fakultas Teknik, Universitas Muhammadiyah Prof. Dr. Hamka, Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to compare Robinson's edge detection method and Kirsch's method on image with a focus on the disclosure of special features such as texture, watermark, and design elements. Robinson's edge detection method uses a series of filters with eight neighboring pixel operations, while Kirsch's method uses a series of filters with more specific filter orientation to produce sharper edge responses. Paper money images were selected as research objects because they had distinctive features relevant to edge detection, such as differences in intensity on edge lines, smooth paper textures, and special patterns on watermarks. This research using banknote image and lung X-rays image dataset. From the results of comparison of edge detection with Robinson's method and Kirsch method it can be concluded that on Robinson's method the edge image of banknotes displays more detailed design elements of banknotes such as hero photographs, watermark, logo, and nominal. In the Kirsch method the bank image has a sharp edge response so that many of the design elements on the banknote are not clearly visible and contrasted with other banknotes. In a comparison of edge detection between Robinson and Kirsch's methods on pneumonia-infected lung X-rays, it can be inferred that Robinson produced a fine edge line but was difficult to find infection, while Kirsch produced a rough edge line that clarified infection in pneumonia-infected lungs.
Pemanfaatan Augmented Reality dengan Metode MDLC Pengenalan Area Petualangan One Piece Berbasis Android Taupik Kamil; Estu Sinduningrum; Muhammad Iqbal
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1846

Abstract

The development of augmented reality (AR) technology has grown very rapidly in various applications, including in the fields of entertainment and education. One of the uses of augmented reality in new innovations in the field of entertainment is the introduction of adventure areas in the android-based one piece anime. Based on this explanation, this research aims to introduce adventure areas in the one piece anime, especially Marineford with the use of Augmented Reality technology using android to users. The problem faced is the lack of limited visual information in recognizing the adventure area in the anime. The use of augmented reality (AR) technology allows users to recognize 3D objects in the adventure area more interesting and fun. By using marker based technique, users only need to point the android camera device to a sign or target image that has been prepared then the 3D object will appear on the device screen in real-time. The method for developing this application is Multimedia Development Life Cycle (MDLC) because it is suitable for multimedia development including augmented reality. Application testing is done using blackbox testing in testing the functionality of the application on each component runs well. With the development of the adventure area application in anime one piece, augmented reality will present a new introduction for users to know the adventure area in anime one piece into augmented reality technology.
Analisis Sentimen Masyarakat Sebelum Dan Sesudah Terpilihnya Gibran Sebagai Cawapres Prabowo Menggunakan Naïve Bayes Alfito Gaizka; Achmad Rizal Dzikrillah; Estu Sinduningrum
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1876

Abstract

The presidential and vice presidential elections in Indonesia always trigger debate, especially in 2024 which is considered quite grabbing public attention. The latest controversy arose regarding Gibran's candidacy as Prabowo's running mate. This study aims to analyze changes in public sentiment before and after Gibran was selected as a vice presidential candidate in reviews on the Twitter (X) application. The dataset used in this study is a review from Twitter (X) with a period of time from July 2023 to December 2023, or before and after Gibran's nomination as Prabowo's vice president, then the dataset is saved into a csv file into GibranSebelum, GibranSesudah, PrabowoSebelum, dan PrabowoSesudah. The dataset was then analyzed using the Naïve Bayes algorithm by classifying sentiment into positive and negative categories. The Preprocessing stages carried out in this study include Cleansing, Tokenizing, Stopwords, and Transform Cases. This study also used the confusion matrix evaluation method to measure accuracy using three parameters, namely accuracy, precision, and recall. The results showed variations in model performance, GibranSebelum's dataset achieved 42.86% accuracy, 20.00% precision, and 100.00% recall, while GibranSesudah produced 67.80% accuracy, 52.50% precision, and 100.00% recall. PrabowoSebelum's dataset recorded 60.71% accuracy, 44.07% precision, and 100.00% recall, while PrabowoSesudah had 55.00% accuracy, 35.71% precision, and 100.00% recall. Analysis shows a trend of increasing negative sentiment after Gibran was sworn in as Prabowo's vice president, signaling an increase in public dissatisfaction with the condition
Co-Authors Achmad Rizal Dzikrillah Alfito Gaizka Muhammad Iqbal Nunik Pratiwi Rosalina Taupik Kamil