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All Journal Jurnal Informatika Jurnal Teknik Elektro Telematika : Jurnal Informatika dan Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Techno LPPM Seminar Nasional Informatika (SEMNASIF) ILKOM Jurnal Ilmiah Jurnal Informatika Dan Tekonologi Komputer (JITEK)
Wilis Kaswidjanti
UPN Veteran Yogyakarta
Computer Science & IT Education Electrical & Electronics Engineering Engineering Other

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SISTEM INFORMASI GEOGRAFIS KOMANDO RAYON MILITER (KORAMIL) DAN KECAMATAN BINAAN KORAMIL DI KOTA YOGYAKARTA Budi Santosa; Sri Rahayu Astari; Wilis Kaswidjanti
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 1 (2017): “e-Defense : Menjaga keamanan data menghadapi cyber warfare untuk memperkokoh ke
Publisher : Jurusan Teknik Informatika

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Abstract

Komando Rayon Militer (Koramil) merupakan satuan komando kewilayahan terkecil dari Tentara Nasional Indonesia (TNI) yang terletak di setiap kecamatan yang berperan sebagai pelaksanaan Sistem Pertahanan Keamanan Rakyat Semesta (sishankamrata). Berdasarkan UU nomor 3 tahun 2002 tentang Pertahanan Negara, Koramil memiliki tugas pokok menyelenggarakan pembinaan teritorial dalam rangka mempersiapkan wilayah pertahanan di darat dan menjaga keamanan wilayahnya untuk mendukung tugas pokok Komando Distrik Militer (Kodim). Pembinaan territorial meliputi segala unsur wilayah geografi, demografi dan kondisi social agar tercipta suatu kekuatan wilayah yang tangguh dalam mengatasi segala ancaman, gangguan dan hambatan yang mengganggu kelangsungan hidup berbangsa dan bernegara serta jalannya pembangunan nasional. Mengingat pentingnya fungsi Koramil dan harus adanya kerja sama antara masyarakat dan Koramil, maka anggota Koramil harus mengetahui daerah binaannya, begitu juga masyarakat yang kesulitan mengetahui Koramil mana yang membina daerahnya dan kegiatan ataupun kejadian apa yang ada di daerahnya, maka di bangun Sistem Informasi Geografis Persebaran Komando Rayon Militer (Koramil) untuk mempermudah anggota serta masyarakat mengetahui informasi letak koramil dan wilayah yang dibina. Metodologi penelitian sistem menggunakan metode waterfall dalam pengembangannya dengan pemetaan menggunakan teknologi Google Maps. Pada sistem terdapat Admin (Kodim dan Koramil) dan User pengguna (Anggota dan Masyarakat). Sistem ini memiliki fitur perbesaran (zoom in) dan pengecilan (zoom out), menampilkan rute dan jarak terdekat menuju koramil, serta informasi kegiatan yang sudah dilaksanakan dan belum dilaksanakan. Pengunjung juga dapat melihat tingkat kejadian disetiap kelurahan melalui diagram statistik setiap bulannya sehingga masyarakat dapat bekerjsama untuk meningkatkan keamanan dan pertahanan wilayah.
IMPLEMENTASI SISTEM PENGONTROLAN STOK BAHAN BAKU DAN BARANG JADI PADA GUDANG TEH Wilis Kaswidjanti; Frans Ricard Kodong; Heru Tricahyono
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 1 (2017): “e-Defense : Menjaga keamanan data menghadapi cyber warfare untuk memperkokoh ke
Publisher : Jurusan Teknik Informatika

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Abstract

Pencatatan inventory produk pada suatu perusahaan merupakan salah satu pendukung utama dalam proses pendistribusian barang. Tidak adanya pengawasan terhadap inventory produk dapat menyebabkan berhentinya pemenuhan permintaan terhadap customer. Oleh sebab itu, dibutuhkan suatu sistem informasi yang mendukung untuk pemeliharaan dan pengawasan suatu perusahaan khususnya dalam mengolah data persediaan stok barang setiap harinya. Dengan telah tersedianya jaringan internet pada perusahaan, pemanfaatan teknologi informasi dapat dimaksimalkan dengan membangun aplikasi sistem pengontrolan stok bahan baku dan barang jadi yang dapat diakses oleh kantor pusat dengan cepat dan tepat. Penelitian yang menggunakan metodologi pengembangan sistem waterfall model process. Fitur yang tersedia pada sistem informasi ini meliputi pencatatan, pengolahan, penyimpanan dan pelaporan data persediaan stok barang di gudang setiap hari. Pengolahan data oleh bagian gudang, sedangkan kantor hanya dapat melihat informasi data. Login dipisahkan menjadi tiga yaitu login untuk gudang, kasir dan kantor
KEGIATAN PENDAMPINGAN PENERAPAN TIK PADA NEXT GEN’S PARTY KOI SHOW KE 2 Budi Suyanto; Mangaras Y F; Wilis Kaswidjanti; Dessyanto Boedi P; Nur Heri Cahyana
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 3 No. 2 (2023): Juli : Jurnal Informatika dan Teknologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v3i2.1377

Abstract

Inspection and implementation of ICT in competition management at Next Gen's Party Koi Show #2. Training with two-way interaction methods, presentations and exercises on how to use the activity registration application and back office application to manage activity participants and provide support on activity days. Next Gen's Party Koi Show #2 Online Registration Application Install Next Gen's Party Koi Show #2 Back Office Online Application Install Next Gen's Party Koi Show #2 Participant Registration Support Activities Next Gen Support Committee Party Koi Show #2 activities in Participant management.
Use of Hybrid Methods in Making E-commerce Product Recommendation Systems to Overcome Cold Start Problems Budi Santosa; Muhamad Azam Fuadi; Mangaras Yanu Florestiyanto; Vynska Amalia Permadi; Wilis Kaswidjanti
Telematika Vol 16, No 1: February (2023)
Publisher : Universitas Amikom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35671/telematika.v16i1.2080

Abstract

The large number of users and the items offered in e-commerce make it difficult for buyers to choose the right items and sellers to offer their items to the right buyers. To overcome this problem, a system that can offer and recommend goods automatically, namely a recommendation system is needed. One of the most popular methods used to create a recommendation system is collaborative filtering, the recommendations are created based on similarities in user behavior. Unfortunately, this method has a weakness, namely cold start, where the recommendations will be inaccurate on data that has a lot of new users and items due to minimal historical data regarding user behavior. This problem will be tried to be solved in this study using a hybrid method, where this method combines more than 1 method to create a list of recommendations so that it will cover the shortcomings of each method. This study uses Amazon's e-commerce product and transaction data. The use of the hybrid method in this study can overcome the cold start problem by using switching and mixed methods, by not using the collaborative filtering model on new user recommendations or users who have little interaction. New users will receive recommendations based on the combination of popularity-based and content-based filtering models. This can be seen from the Mean Absolute Error (MAE) value of the model, where the MAE value for the data with a minimum user has at least 3 times rating is 0.566883, for the minimum 7 times, the MAE value is smaller, 0.487553.
Implementation of Histogram Equalization for Image Enhancement in The Classification of Spices Using K-Nearest Neighbor Safrizal, Busroni Ahmad; Kaswidjanti, Wilis
Telematika Vol 21 No 3 (2024): Edisi Oktober 2024
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v21i3.12070

Abstract

Purpose: To determine the effect of implementing Histogram equalization (HE) at the image preprocessing stage to improve image quality in rhizome spice classification using the K-Nearest Neighbor classification method.Design/Method/Approach: Rhizome spice data was taken directly using a camera with a total of 600 images divided by a ratio of 80:20 for training and testing data. Preprocessing is done starting from resize to 512x512 pixels, then remove background to remove background objects that are not needed, then histogram equalization and also grayscale conversion. Glcm texture feature modeling, rgb color feature and hsv color feature are used as classification parameters. Classification is done using the K-Nearest Neighbor (KNN) method.Findings/result: The test results of this study can be concluded that the application of HE at the image preprocessing stage succeeded in improving classification performance as seen from the accuracy evaluation value. In KNN classification without preprocessing histogram equalization gets an accuracy of 73.8%.  When implementing histogram equalization the classification accuracy increases to 76.1%.From the two accuracy results obtained, it can be seen that the implementation of histogram equalization has a good effect in increasing the accuracy of classification.Originality/value/state of the art: The application of Histogram equalization (HE) in image preprocessing is able to improve image quality so that classification accuracy can increase compared to without using histogram equalization preprocessing.
PENGEMBANGAN SISTEM OFFICE AUTOMATION (SOA) MENGGUNAKAN E-MAILING SYSTEM ONLINE Florestiyanto, Mangaras Yanu; Himawan, Hidayatulah; Kaswidjanti, Wilis; Yuwono, Bambang
Journal TECHNO Vol. 1 No. 1 (2015)
Publisher : Universitas Pembangunan Nasional Veteran Yogayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/journal techno.v1i1.1508

Abstract

Sistem Office Automation (OA) dikembangkan oleh banyak institusi untuk menunjangpeningkatan kinerja sebuah institusi atau organisasi. Sistem ini bertujuan untuk mengalihkanfungsi sumber daya manual perkantoran yang banyak menggunakan tenaga manusia menujufungsi otomasi menggunakan peralatan mekanis e-mailing system secara online. Penelitian inibertujuan untuk mengembangkan e-mailing system/sistem informasi persuratan elektronisdengan melakukan pemantauan persuratan terutama pada permasalahan alur perjalanan suratdan disposisi serta tindak lanjutnya. Penelitian ini menggunakan metode Difine SystemSpecification yang dapat mengatasi kelemahan pada proses alur perjalanan surat dan disposisiserta tindak lanjutnya. Hasil penelitian ini mampu memproses alur perjalanan surat maupuntindak lanjut disposisi surat dengan pemantauan yang lebih baik.System Office Automation (OA) developed by many institutions in support of improving theperformance of an institution or organization. This system aims to divert resources function thatmany manual office using manpower towards automation functions using mechanical equipmente-mailing system online. This research aims to develop e-mailing system / electroniccorrespondence with the information system monitoring the flow of correspondence, especially onissues trips letters and dispositions as well as follow-ups. This study uses difine SystemSpecification which can address the weaknesses in the process flow and disposition journey letterand follow-up. Results of this study were able to process the flow of letters and follow-up tripdisposition letter with better monitoring.Keywords: e-Mailing System, Sistem Office Automation, disposition, Electronic letters
Implementasi Algoritma Region of Interest (ROI) untuk Meningkatkan Performa Algoritma Deteksi dan Klasifikasi Kendaraan Pratomo, Awang Hendrianto; Kaswidjanti, Wilis; Mu'arifah, Siti
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 1: Februari 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

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Abstract

Semakin tinggi kualitas suatu citra maka semakin detail informasi yang akan di peroleh. Tetapi, tidak semua wilayah citra memungkinkan untuk dilakukan analisis dengan kecepatan proses yang tinggi. Pemilihan algoritma yang tepat berpengaruh terhadap kecepatan waktu pemrosesan. Apabila tidak ada pembatasan untuk area yang akan di proses mengakibatkan waktu pemrosesan secara realtime melebihi waktu pemrosesan maksimal yang seharusnya. Tingginya waktu pemrosesan yang terjadi mengakibatkan aliran data menjadi kurang cepat. Sarana/processor yang digunakan juga mampu mempengaruhi kecepatan pemrosesan. Region Of Interest (ROI) adalah cara yang tepat untuk mengurangi tingginya waktu pemrosesan tersebut. ROI mampu menandai area tertentu sehingga dapat digunakan untuk mengoptimalisasikan kinerja sistem untuk mendeteksi, menghitung dan mengklasifikasi kendaraan secara realtime. Tanpa adanya ROI, pemrosesan dilakukan pada seluruh piksel citra tanpa terkecuali. Terdapat beberapa tahapan yang dilakukan di dalam penelitian yaitu menganalisis masalah yang ada, penentuan wilayah ROI, aplikasi ROI sebelum proses pengolahan citra dan menganalisis hasil yang di dapatkan.  Hasil yang diperoleh adalah dengan menggunakan ROI waktu pemrosesan citra menggunakan metode segmentasi MOG2 dan tracking dapat lebih cepat dibandingkan dengan waktu pemrosesan ketika tidak menggunakan ROI dengan selisih 0,026 s atau setara dengan 26 ms/frame. AbstractIncreasing resolution of an image is more detailed information will be obtained especially in the image used to detect vehicles. But, every singles areas are not allow to analize with higher speed process. If there are no restrictions for the area to be processed, the processing time in real time exceeds the maximum processing time that should be. The high processing time that occurs make less rapid data flow. The high processing time can affect to processing speed. Region Of Interest (ROI) is the right way to reduce the high processing time. ROI is able to mark certain areas so that it can be used to optimize system performance to detect, calculate and classify vehicles in realtime. Without ROI, processing is carried out on all pixels without exception. There are several steps taken in the research, namely analyzing existing problems, determining the ROI area, application of ROI before the image processing and analyzing the results obtained. The results obtained are by using ROI image processing time can be faster than the processing time when not using ROI. 
The Implementation of Color Feature Extraction and Gray Level Co-occurrence Matrix Combination in K-Nearest Neighbor Classification Method for Tomato Leaf Disease Identification Agusta, Sandy Wahyu; Kaswidjanti, Wilis
Telematika Vol 20 No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.10009

Abstract

Purpose: Tomato plants are quite important commodities in Indonesia. With a complete and good content of substances, tomatoes become a product that is widely consumed by the public. However, much of the decline in crop production is caused by plant disruptive organisms such as viruses and bacteria. Early identification of plant diseases is expected to prevent the spread of diseases caused by these organisms.Design/methodology/approach: In this study the data used in machine training are data from kaggle sites. This study uses the K-Nearest Neighbor classification method with a combination method of extracting feature on RGB, HSV and GLCM images to obtain the best accuracy value.Findings/Results: Based on the test results among the combination methods of feature extraction in the process of identifying tomato leaf diseases which are classified into 7, namely testing units of RGB, HSV, GLCM followed by a combination of RGB HSV, RGB GLCM, HSV GLCM, and RGB HSV GLCM methods obtained a comparison value of 71.5%, 72.9%, 79%, 82.5%, 90.6%, 87.4% and 87.7%. Based on these data, it was concluded that with the combination of the RGB GLCM method obtained the best accuracy value in the identification of tomato leaf disease with an accuracy rate of 90.6%.Originality/value/state of the art: The use of the K-Nearest Neighbor classification method in this study combines the collection of selected characteristics so as to get a comparison of 7 combination groups between RGB, HSV, and GLCM.
Co-Authors A H Pratomo Agung Tri Utomo Agus Sasmito Aribowo Agusta, Sandy Wahyu Awang Hendrianto Pratomo Azizah, Nisa’ul Bambang Yuwono Bambang Yuwono Bambang Yuwono Budi Santosa Budi Santosa Budi Suyanto Datu Lestari Mallisa Dessyanto Boedi P Dessyanto Boedi Prasetyo E T Paripurno Ervina Amelia Malik Felix Andika Dwiyanto Frans Ricard Kodong Frans Richard Kodong Hafidz Fajar Abdur Rahman, Hafidz Fajar Abdur Hendri Gusaptono Herlina Jayadianti Herry Sofyan Heru Tricahyono Hidayatulah Himawan Indah Ismayasari J D Peasetyo Luthfie Hawari Mangaras Y F Mangaras Yanu F Mangaras Yanu Florestiyanto Mu'arifah, Siti Muhamad Azam Fuadi Novrido Charibaldi Nur Heri Cahyana Nur Heri Cahyana O Y Siregar Rafal Drezewski Rifky Satya Wicaksono, Rifky Satya Riski Aulia Sabihaini Sabihaini Safrizal, Busroni Ahmad Saifullah, Shoffan Santosa, Budi Sri Rahayu Astari Vynska Amalia Permadi