https://stt-pln.e-journal.id/petir/issue/feed PETIR: Jurnal Pengkajian dan Penerapan Teknik Informatika 2020-09-21T06:24:11+00:00 Editorial Jurnal Petir riki.ruli@sttpln.ac.id Open Journal Systems <p style="margin-bottom: 0in; line-height: 150%;" align="justify"><strong><span style="color: #21409a;"><span style="font-family: Abyssinica SIL;"><span style="font-size: xx-large;"><span style="font-weight: normal;"><span style="font-family: Times new roman, serif;"><span style="font-size: medium;">Petir: Jurnal Pengkajian dan Penerapan Teknik Informatika </span></span></span></span></span></span></strong><span style="font-family: Times new roman, serif;"><span style="font-size: medium;">Journal is a scientific journal published by Sekolah Tinggi Teknik PLN Informatics Engineering Department, established in 2007.&nbsp;Petir: Jurnal Pengkajian dan Penerapan Teknik Informatika Journal has been <strong>Accredited </strong>by the <strong>National Journal Accreditation</strong> (ARJUNA) managed by the Ministry of Research, Technology, and Higher Education of the Republic of Indonesia with Class Four (<strong><a href="http://sinta2.ristekdikti.go.id/journals/detail?id=4522" target="_blank" rel="noopener">SINTA 4</a></strong>) from 2018 to 2023 in accordance with the Decree<strong>. No. 23 / E / KPT / 2019.</strong></span></span></p> <p style="margin-bottom: 0in; line-height: 150%;" align="justify"><span style="font-family: Times new roman, serif;"><span style="font-size: medium;">Petir is published twice a year in March and September and contains researches in the field of Informatics Engineering, specifically in Electrical Power, Telecommunication, Control System, Electronics, Computer Systems and Information Systems.&nbsp;The article entered will be peer reviewed. </span></span><span style="font-family: Times new roman, serif;"><span style="font-size: medium;">During the review process, the results of the review will be informed to the authors of the papers through the journal Open Journal System journal PETIR system and also by email of the author.&nbsp; </span></span><span style="font-family: Times new roman, serif;"><span style="font-size: medium;">Please read and understand the author guidelines thoroughly. Author who submits a manuscript to the editors of PETIR Journal should comply with the author guidelines. If the submitted manuscript does not comply with the guidelines or using a different format, it will be rejected by the editorial team before being reviewed. Editorial Team will only accept a manuscript that meets the specified formatting requirements. </span></span></p> <p style="margin-bottom: 0in; line-height: 150%;" align="justify"><span style="font-family: Times new roman, serif;"><span style="font-size: medium;">T</span></span><span style="font-family: Times new roman, serif;"><span style="font-size: medium;">he journal registered in the CrossRef with </span></span><strong><span style="font-family: Times new roman, serif;"><span style="font-size: medium;">Digital Object Identifier&nbsp;(DOI)&nbsp;prefix</span></span></strong><span style="font-family: Times new roman, serif;"><span style="font-size: medium;">: <a href="https://search.crossref.org/?q=PETIR" target="_blank" rel="noopener"><span style="text-decoration: underline;"><strong>10.33322</strong></span></a></span></span></p> <p style="text-align: justify;" align="justify"><strong><span style="font-family: Times new roman, serif;"><span style="font-size: medium;">P-ISSN: <a href="https://portal.issn.org/resource/ISSN-L/1978-9262" target="_blank" rel="noopener">1978-9262</a>,&nbsp;&nbsp;e-ISSN: <a href="https://portal.issn.org/resource/ISSN/2655-5018#" target="_blank" rel="noopener">2655-5018</a>&nbsp; &nbsp;</span></span></strong></p> https://stt-pln.e-journal.id/petir/article/view/659 Optimalisasi Image Thresholding pada Optical Character Recognition Pada Sistem Digitalisasi dan Pencarian Dokumen 2020-09-21T06:24:11+00:00 Ridwan Rismanto rismanto@polinema.ac.id Arief Prasetyo arief.prasetyo@polinema.ac.id Dyah Ayu Irawati dyah.ayu.irawati@gmail.com <p>The administration activity in an institute is largerly done by using a paper based mailing and document as a media. Therefore, a great effort needs to be performed in the case of management and archiving, in the form of providing storage space through the categorizing system. Digitalization of document by scanning it into a digital image is one of the solution to reduce the effort to perform the work of archiving and categorizing such document. It also provide searching feature in the form of metadata, that is manually written during the digitalization process. The metadata can contains the title of document, summary, or category. The needs to manually input this metadata can be solved by utilizing Optical Character Recognition (OCR) that converts any text in the document into readable text storing in the database system. This research focused on the implementation of the OCR system to extract text in the scanned document image and performing optimization of the pre-processing stage which is Image Thresholding. The aim of the optimization is to increase OCR accuracy by tuning threshold value of given value sets, and resulting 0.6 as the best thresholding value. Experiment performed by processing text extraction towards several scanned document and achieving accuration rate of 92.568%.</p> 2020-03-21T00:00:00+00:00 ##submission.copyrightStatement## https://stt-pln.e-journal.id/petir/article/view/766 Sistem Informasi Pengelolaan Tugas Akhir Mahasiswa dan Jurnal Penelitian Internal Jurusan Teknik Informatika Politeknik Negeri Ketapang 2020-09-21T06:24:10+00:00 Eka Wahyudi ekawahyudi_algebra@ymail.com Indra Pratiwi indrapratiwi@gmail.com <p><em>Information system is a matter that must be owned by an agency to be able to support managerial activities and performance in any field. Each agency must have its own information system. The system built in this study is the Final Project Management and Internal Research Journal of the Informatics Engineering Department at the Ketapang State Polytechnic. This analysis is used by collecting data in research. In designing, the authors create a computerized work through the process of designing component models, databases, and user interface components. This system is designed to provide information for students about each Final Project from students of the Informatics Engineering Study Program at the State Polytechnic of Ketapang. Final Project Management can provide services to students. Therefore this study aims to develop IT technology in the Informatics Engineering Department of the Ketapang State Polytechnic. This system was built to facilitate users such as admins and students in managing student final assignments.</em></p> 2020-03-21T00:00:00+00:00 ##submission.copyrightStatement## https://stt-pln.e-journal.id/petir/article/view/768 Implementasi Algoritma Neural Network untuk Mendukung Keputusan di Desa Tamanmekar 2020-09-21T06:24:09+00:00 Amril Mutoi Siregar amrilmutoi@ubpkarawang.ac.id Hanny Hikmayanti H hanny.hikmayanti@ubpkarawang.ac.id <p><em>Tingkat kesejahteraan masyarakat pedesaan yang terutama jauh dari perkotaan, masih banyak ditemukan dibawah garis kemiskinan. Mengingat akar permasalahannya adalah hampir semua desa tidak mempunyai data yang benar, akurat dan tepat tentang kondisi permasalahan dan potensi desa yang dimiliki. Padahal pemerintah pusat menyalurkan anggaran tiap tahun untuk setiap desa, hampir mencapai 1 milyar pertahun. Dengan tidak memiliki data yang akurat dan benar, sehingga pembangunan tidak tepat sasaran termasuk penyaluran beras rakyat miskin (Raskin), Bantuan langsung tunai (BLT). Masih ditemukan penyaluran yang tidak tepat sasaran, sesuai dengan yang rencanakan oleh pemerintah. Dengan penelitian ini diharapkan salah cara untuk menganalisa data penduduk, baik &nbsp;permasalahan dan potensi yang dimiliki. Sehingga penyaluran bantuan lainya tepat sasaran. Metode pengolahan data, untuk diimplementasikan agar desa memiliki data yang benar dan akurat. Untuk seleksi fitur dalam penelitian ini menggunakan algoritma Neural Network (Jaringan syaraf tiruan), hasil accuracy algoritma penelitian ini adalah 94.96 %. Sehingga dapat digunakan sebagai referensi untuk mengolah data untuk Bantuan dari pemerintah.</em></p> 2020-03-21T00:00:00+00:00 ##submission.copyrightStatement## https://stt-pln.e-journal.id/petir/article/view/858 Perbandingan Algoritma Long Short-Term Memory dengan SVR Pada Prediksi Harga Saham di Indonesia 2020-09-21T06:24:08+00:00 Adhib Arfan adhib.arfan@gmail.com Lussiana ETP LussianaETP@gmail.com <p><em>Banyak investor masih ragu dengan risiko dalam berinvestasi, hal ini disebabkan oleh fluktuasi indeks harga saham dalam waktu singkat. Telah banyak dikembangkan metode untuk memperkirakan harga saham yang akan datang namun masih memiliki keterbatasan di antaranya adalah ketergantungan jangka panjang. Tujuan penelitian yang ingin dicapai adalah menghasilkan model peramalan harga saham yang lebih efektif dan memberikan hasil yang akurat. Tahapan yang dilakukan terdiri dari pengumpulan data, preprocessing data, pembagian data, perancangan LSTM, pelatihan LSTM dan melakukan pengujian. Berdasarkan hasil pengujian, LTSM mampu memprediksi harga saham pada tahun 2017-2019 dengan performa yang baik dan tingkat kesalahan yang relatif kecil. Sedangkan pengujian menggunakan metode Support Vector Regression (SVR), LSTM memiliki nilai loss lebih baik dari algoritma SRV. Rentang data pada LSTM mempengaruhi waktu latih yang digunakan, semakin besar rentang data maka semakin lama waktu latih yang digunakan. Rentang data pada SVR mempengaruhi nilai loss, semakin besar rentang data maka semakin besar nilai loss yang dihasilkan. Dengan demikian dapat disimpulkan bahwa LSTM mampu menanggulangi ketergantungan jangka panjang dan mampu memprediksi harga saham dengan hasil yang akurat.</em></p> 2020-03-21T00:00:00+00:00 ##submission.copyrightStatement## https://stt-pln.e-journal.id/petir/article/view/869 Penentuan Rute Pengiriman Barang Dengan Metode Nearest Neighbor 2020-09-21T06:24:07+00:00 Sandi Martono sandi.martono@gmail.com Harco Leslie Hendric Spits Warnars spitswarnars@googlemail.com <p>Semakin cepat barang sampai ke konsumen maka menjadi lebih mudah untuk mendapatkan barang dan keuntungan perusahaan semakin bertambah. Pada pendistribusian membentuk salah satu pemecahan masalah untuk mencari rute dengan meminimumkan jarak dari lokasi gudang ke toko dan memiliki jumlah permintaan barang yang berbeda-beda. Menggunakan metode nearest neighbor untuk menyelesaikan penentuan rute distribusi barang dari gudang ke toko, dengan tujuan mengurangi total jarak pengiriman, waktu dan beban biaya yang dibebani perusahaan. Hasil pencarian rute menggunakan metode nearest neighbor menghasilkan jumlah rute paling sedikit dibandingkan dengan sebelum menggunakan metode dan pada total jarak dengan menggunakan metode 98610 meter atau 98,61 km sedangkan jika pada rute sebelum mengunakan metode 124198 meter atau 124,198 km terjadi pengurangan jarak 25588 atau 25,588 atau sebesar 20.6026 %.</p> 2020-03-21T00:00:00+00:00 ##submission.copyrightStatement## https://stt-pln.e-journal.id/petir/article/view/870 Menentukan Prediksi Kredit Nasabah Menggunakan Metode Analytical Hierarchy Prosess (AHP) pada PD BPR Kerta Raharja 2020-09-21T06:24:06+00:00 Afrilia Astari afrilia@raharja.info Harco Leslie Hendric Spits Warnars spitswarnars@googlemail.com <p>Teknologi saat ini semakin maju serta berkembang pesat dan kebutuhan akan informasi semakin meningkat bukan hanya pada perusahaan tetapi pada instansi perbankan juga demikian. Maka dari itu dibutuhkan sistem informasi untuk membantu kinerja pegawai dalam mengelola data dengan efektif dan efisien. Salah satunya dalam kegiatan penentuan prediksi kredit yang ada pada PD BPR Kerta Raharja yang &nbsp;sekarang masih menggunakan system prediksi manual dalam penentuan kelayakan dan belum terkomputerisasi dengan baik. Dalam hal ini pengunaan Sistem Penentuan Prediksi &nbsp;sangatlah dibutuhkan dalam menentukan prediksi kelayakan pemberian pinjaman kredit. Diperlukan menggunakan metode yang bias bahkan mampu mendukung dalam menentukan prediksi kredit nasabah dengan lebih efektif. Yakni dengan menggunakan sebuah metode <em>Analytical Hierarchy Process</em> (AHP) karena metode ini dapat melakukan kriteria majemuk secara detail dengan suatu kerangka berfikir dan perhitungan suatu kriteria bobot yang <em>komprehensif</em>. Dengan membandingkan sub-kriteria terbagi dalam kategori : baik, cukup baik dan kurang dalam menentukan prediksi kredit. Penelitian ini kami lakukan dengan metode observasi, wawancara dan studi pustaka serta menggunakan <em>Unified Modelling Language</em> (UML) dalam menggambarkan prosedur diagram sistem yang berjalan. Hasil dari penelitian kami dengan menerapkan sistem baru pada PD BPR Kerta Raharja, dan menjadikan proses menentukan prediksi kredit nasabah menjadi lebih efektif serta akurat.</p> <p>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;</p> 2020-03-21T00:00:00+00:00 ##submission.copyrightStatement## https://stt-pln.e-journal.id/petir/article/view/893 Perbandingan Metode Newton-Raphson & Metode Secant Untuk Mencari Akar Persamaan Dalam Sistem Persamaan Non-Linier 2020-09-21T06:24:03+00:00 Endang Sunandar abahendang1969@gmail.com Indrianto Indrianto indrianto@itpln.ac.id <p style="text-align: justify;"><em>The numerical method is a technique used to formulate mathematical problems so that it can be solved using ordinary arithmetic operations. In general, numerical methods are used to solve mathematical problems that cannot be solved by ordinary analytic methods.&nbsp;</em><em>In the Numerical Method, we recognize two types of systems of equations, namely the Linear Equation System and the Non-Linear Equation System. Each system of equations has several methods. In the Linear Equation System between methods is the Gauss Elimination method, the Gauss-Jordan Elimination method, the LU (Lower-Upper) Decomposition method. And for Non-Linear Equation Systems between the methods are the Bisection method, the Regula Falsi method, the Newton Raphson method, the Secant method, and the Fix Iteration method.&nbsp;</em><em>In this study, researchers are interested in analyzing 2 methods in the Non-Linear Equation System, the Newton-Raphson method and the Secant method. And this analysis process uses the Java programming language tools, this is to facilitate the analysis of method completion algorithm, and monitoring in terms of execution time and analysis of output results. So we can clearly know the difference between what happens between the two methods.</em></p> 2020-03-21T00:00:00+00:00 ##submission.copyrightStatement## https://stt-pln.e-journal.id/petir/article/view/908 Penggunaan Global Contrast Saliency dan Histogram of Oriented Gradient Sebagai Fitur untuk Klasifikasi Jenis Hewan Mamalia 2020-09-21T06:24:02+00:00 Yohannes Yohannes yohannesmasterous@mdp.ac.id Muhammad Ezar Al Rivan meedzhar@mdp.ac.id <p>Mammal type can be classified based on the face. Every mammal’s face has a different shape. Histogram of Oriented Gradient (HOG) used to get shape feature from mammal’s face. Before this step, Global Contrast Saliency used to make images focused on an object. This process conducts to get better shape features. Then, classification using k-Nearest Neighbor (k-NN). Euclidean and cityblock distance with k=3,5,7 and 9 used in this study. The result shows cityblock distance with k=9 better than Euclidean distance for each k. Tiger is superior to others for all distances. Sheep is bad classified.</p> 2020-03-21T00:00:00+00:00 ##submission.copyrightStatement## https://stt-pln.e-journal.id/petir/article/view/925 Penerapan Metode K-Means Dan C4.5 Untuk Prediksi Penderita Diabetes 2020-09-21T06:24:01+00:00 Andika Prasatya andika1531220@sttpln.ac.id Riki Ruli A. Siregar riki@trisakti.ac.id Rakhmat Arianto ari87anto@gmail.com <p style="text-align: justify;"><em>The purpose of this study is to predict HbA1c in diabetics. The obstacles behind the prediction of HbA1c is the limitations in the laboratory to provide services for diabetics regarding HbA1 check-up. HbA1c prediction is made by a combination of K-Means and C4.5 methods. K-Means is used to classify continuous data. From the results of the K-Means classification will be used by C4.5 to create a rule (decision tree). The prediction results obtained will be carried out as a validation process to determine the level of accuracy by using K-Fold Cross-Validation. The accuracy value obtained is 72%. The resulting benefit from the prediction of HbA1c can be used as an alternative solution to overcome limitations in the laboratory in terms of HbA1c check-up servicing and the results of HbA1c prediction can also be used as a recommendation by doctor in determining the medical decision for diabetics.</em></p> 2020-03-22T00:00:00+00:00 ##submission.copyrightStatement## https://stt-pln.e-journal.id/petir/article/view/891 Audit Tingkat Kematangan Proses Internal Key Logistics System Menggunakan Kerangka Kerja Cobit 4.1 Pada Perusahaan Ekspedisi XYZ 2020-09-21T06:24:05+00:00 Albaar Rubhasy albaar.rubhasy@gmail.com Dewi Murti Milasari dewimurtimilasari9@gmail.com <p><em>The purpose of this study is to evaluate the level of IT maturity that occur in XYZ</em><em> Shipping Company</em><em> using COBIT 4.1 framework as a best practice in </em><em>information technology audit</em><em>. </em><em>The company is highly depend on Key Logistics System as a core system in shipping process. For this reason, the company wants to focus on internal processes by increasing efficiency while minimizing costs, so COBIT IT Process was chosen</em><em>: PO3, AI2, AI5, AI3, AI4, AI7, PO6, DS3, DS7, DS8, DS9, PO5, and DS6. </em><em>An assessment was conducted on 26 Key Logistics System users as respondents. Stages of research to be carried out include: identification of the COBIT 4.1 process; data collection; measurement of current and target maturity levels; gap analysis; and preparation of recommendations. </em><em>Result has shown that the average maturity score of the Key Logistics System is 3</em><em>,</em><em>50 or in maturity level 4 (managed). At this level the key logistics system process has been carried out and part of it has been standardized. However, results shows that there are some gaps below the target, such as IT Process PO5, AI2, and AI5 which have maturity level 3 (defined). In order to improve the maturity level, XYZ</em><em> Shipping Company</em><em> has to optimize the IT investement, application maintenance, and IT resources. </em></p> 2020-03-21T00:00:00+00:00 ##submission.copyrightStatement##