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All Journal International Journal of Electrical and Computer Engineering Perfecting a Video Game with Game Metrics Jurnal Informatika INFOKAM Jurnal Inspiration Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Informatika Mulawarman Sinkron : Jurnal dan Penelitian Teknik Informatika International Journal of Artificial Intelligence Research SISFOTENIKA INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi CogITo Smart Journal Jurnal Informatika Universitas Pamulang RESEARCH : Computer, Information System & Technology Management DoubleClick : Journal of Computer and Information Technology JurTI (JURNAL TEKNOLOGI INFORMASI) Matrik : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURTEKSI Jurnal Riset Informatika EKUITAS (Jurnal Ekonomi dan Keuangan) Informasi Interaktif CCIT (Creative Communication and Innovative Technology) Journal JMAI (Jurnal Multimedia & Artificial Intelligence) METIK JURNAL Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi SENSITEK Infotekmesin Jurnal Manajemen Informatika dan Sistem Informasi Journal of Information Systems and Informatics KURVATEK Indonesian Journal of Business Intelligence (IJUBI) Jurnal Tecnoscienza Generation Journal Indonesian Journal of Electrical Engineering and Computer Science Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Infotek : Jurnal Informatika dan Teknologi Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Jurnal Teknologi Informatika dan Komputer International Journal of Computer and Information System (IJCIS) JTECS : Jurnal Sistem Telekomunikasi Elektronika Sistem Kontrol Power Sistem dan Komputer Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi EXPLORE Innovative: Journal Of Social Science Research Nusantara Journal of Computers and its Applications Jurnal INFOTEL
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The effect of Gaussian filter and data preprocessing on the classification of Punakawan puppet images with the convolutional neural network algorithm Kusrini Kusrini; Muhammad Resa Arif Yudianto; Hanif Al Fatta
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp3752-3761

Abstract

Nowadays, many algorithms are introduced, and some researchers focused their research on the utilization of convolutional neural network (CNN). CNN algorithm is equipped with various learning architectures, enabling researchers to choose the most effective architecture for classification. However, this research suggested that to increase the accuracy of the classification, preprocessing mechanism is another significant factor to be considered too. This study utilized Gaussian filter for preprocessing mechanism and VGG16 for learning architecture. The Gaussian filter was combined with different preprocessing mechanism applied on the selected dataset, and the measurement of the accuracy as the result of the utilization of the VGG16 learning architecture was acquired. The study found that the utilization of using contrast limited adaptive histogram equalization (CLAHE) + red green blue (RGB) + Gaussian filter and thresholding images showed the highest accuracy, 98.75%. Furthermore, another significant finding is that the Gaussian filter was able to increase the accuracy on RGB images, however the accuracy decreased for green channel images. Finally, the use of CLAHE for dataset preprocessing increased the accuracy dealing with the green channel images.
Comparison Analysis of Best First Search Algorithm with A * (star) in determining the closest route in the district Sleman Tutik Maryana; Ripto Sudiyarno; Kusrini Kusrini
CCIT Journal Vol 13 No 1 (2020): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1522.128 KB)

Abstract

There are various pathfinding algorithms that have advantages and disadvantages of each algorithm. The purpose of this study is to compare the best-first search pathfinding greedy algorithm with A * (Star) in terms of determining the shortest route in a tent search. The method used in this study is an analytical method for analyzing what algorithms can be applied in track search. Then, the method continued with the design method for the best-first search and A * greedy algorithm, the user interface for the algorithm testing application. The next method is the implementation method, which is the best-first greedy algarithm search and A * implemented in the algorithm testing application. The last method is the method of testing algorithms that will be compared. The conclusions will be drawn from the results of comparison algorithms. The result of this study is the acquisition of a distance comparison between thegreedy best-first search algorithm with A *. The conclusion of this study is that the A * algorithm is able to provide the shortest and optimal route results compared to the BFS algorithm.
Analisys Of Demand and Optimization Of Medicine Prediction Using ABC Analysis and SVR Method In The “MORBIS” Aplication Tutik Maryana; Kusrini Kusrini; Hanif Al Fatta
CCIT (Creative Communication and Innovative Technology) Journal Vol 13 No 2 (2020): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (607.078 KB) | DOI: 10.33050/ccit.v13i2.1098

Abstract

The problem that occurs in hospitals regarding the processing of drug supplies is about the condition of out of stock medicines because hospitals spend around 33% of the total investment in one year only for the investment costs of drugs. To deal with the above problems the hospital must have good logistics management, one way of managing it is by doing good planning. In this research, the writer will use ABC Analysis and Support Vector Regression (SVR) algorithm. For the use of these methods, the following ABC Analysis will be used for the drug classification process, namely by dividing the torch into three main groups based on interests, namely groups A, B and C. Henceforth, the writer will use the SVR motedo to calculate drug predictions. The results that the authors get from this study are ABC analyys classify drugs. Into three groups namely group A with a total of 276 items with a percentage of 22.96% of the total number of items, group B with a total of 396 items with a percentage of 33.11% and C with a total of 528 with a percentage of 43.94% with a total of 1202 drug items. Prediction testing is done by taking a sample of five drugs derived from group classification. The SVR calculation process is done by comparing linear scaling and z normalization preprocessing methods. The result of this research is that MAPE shows that preprocessing with linear scaling produces a better value than compared to z nomrlization and calculation with ABC analysis.
Decision Support System Design Structural Promotion Civil Apparatus Using AHP and TOPSIS Methods Muhamad Yusuf; Kusrini Kusrini; Agung Budi Prasetio
CCIT (Creative Communication and Innovative Technology) Journal Vol 14 No 2 (2021): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (989.078 KB) | DOI: 10.33050/ccit.v14i2.1396

Abstract

The quality of the performance of the State Civil Apparatus (ASN) is a very important resource to be able to determine the capacity of the Regional Apparatus Organization (OPD). One of the efforts to improve the quality of OPD performance is the promotion of positions. Promotion of an award given for work performance and dedication of a civil servant, as well as being excited to improve work performance and loyalty. Therefore, it is necessary to determine a promotion. The weighting method in this study uses the Analytical Hirarchy Process. This study also compares this method with the Technique for Ordering Preference based on Similarities with Ideal Solutions. The resulting criteria are formal and informal. Consists of formal sub-criteria consisting of formal education, position experience, class rank, technical competence, managerial competence and socio-cultural competence. Then for the informal sub-criteria consisting of discipline, innovation, creativity, ideas for institutional functions, the ability to collaborate and work in teams, loyalty, responsibility, leadership, ability to communicate well and recommendations at the provincial and / or ministerial level. Furthermore, calculations are carried out using the AHP and TOPSIS methods for data for 2018 which means 1 position, in 2019 means 2 positions, and in 2020 means 4 positions. In one position consists of 3 ASN alternatives. After comparing the accuracy level of the AHP and TOPSIS methods with experts, the results of the AHP method are better in making recommendations for structural promotion of echelon IV ASN by producing a perfect score of 100% and a TOPSIS value of 71.4%.
Optimasi Query Pada Human Resource Information System (HRIS) di Universitas XYZ Hery Siswanto; Tri Andi; Kusrini Kusrini
JMAI (Jurnal Multimedia & Artificial Intelligence) Vol. 2 No. 1 (2018): Jurnal Multimedia & Artificial Intelligence
Publisher : LPPM Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (305.034 KB) | DOI: 10.26486/jmai.v2i1.53

Abstract

Optimasi merupakan suatu langkah untuk mengoptimalkan waktu menjadi lebih efisien. Ketika sebuah query diberikan pada sistem database, optimasi penting dilakukan untuk memilih strategi yang efisien untuk mengevaluasi ekspresi relasi yang ditentukan. Query optimization adalah suatu proses untuk menganalisis query, menentukan sumber-sumber apa saja yang digunakan oleh query tersebut dan apakah penggunaan dari sumber tersebut dapat dikurangi tanpa merubah output. Kegiatan Pengelolaan manajemen sumber daya manusia yang baik sangat tergantung pada kualitas informasi untuk pengambilan keputusan dibidang sumber daya manusia. Kemampuan organisasi dalam memperoleh, menyimpan, memelihara dan menggunakan informasi sumber daya manusia merupakan faktor penting yang menunjang keberlangsungan hidup perusahaan. Perusahaan harus menyadari pentingnya pemenuhan kebutuhan sumber daya manusia secara berkualitas dan tepat sehingga perlu untuk dikembangkan sistem informasi sumber daya manusia untuk menunjang pemenuhan sumber daya manusia yang berkualitas, Sistem ini yang namanya biasa disebut SISDM atau HRIS (Human Resources Information System). Hasil yang diperoleh dari pengujian sebelum optimasi dan sesudah dioptimasi menunjukan bahwa query yang sudah di optimasi waktu yang di butuhkan dalam melakukan pencarian data lebih cepat. Hasil percobaan pertama dengan 1000 data waktu yang dibutuhkan sebelum optimasi 0.023 dan sesudah di optimasi waktu yang didapatkan 0.015.
Optimasi Algoritma Naive Bayes Menggunakan Metode Cross Validation Untuk Meningkatkan Akurasi Prediksi Tingkat Kelulusan Tepat Waktu Yohakim Benedictus Samponu; Kusrini Kusrini
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Vol. 1 No. 2 (2017)
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/eltikom.v1i2.29

Abstract

Education at this time is an important requirement in facing the demands of an increasingly advanced era in technolo-gy. To compensate this, the existing educational standards in universities must also be improved, this is a bit much affect the pattern of teaching from universities that produce qualified graduates who can compete in the world of work later and indirectly give a positive impact on the university itself. Qualified graduates are of course not only depending on the role of a university but also majors and quality of education as long as students are still in high school / vocational school also plays an important role. Results of the on-time graduation rate prediction research can be used as an information to im-prove the quality and optimization of the education system but it requires a maximum degree of accuracy. This research predicts on time graduation rates by conducting analysis using data mining classification techniques. Naïve Bayes algo-rithm that are used for this research will be discussed as a reference in conducting research. The author performs a series of different experimental scenarios / cross validation to perform comparisons that can give a difference in the level of ac-curacy gained from this research. The results of this research indicate that with the addition of Cross Validation testing scenario there is an increase of 2% accuracy of the test.
Sentiments analysis of customer satisfaction in public services using K-nearest neighbors algorithm and natural language processing approach Elik Hari Muktafin; Pramono Pramono; Kusrini Kusrini
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 1: February 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i1.17417

Abstract

Customer satisfaction is very important for public service providers, customer satisfaction can be delivered with a survey application or writing criticism that can be used to evaluate and improve service. Unfortunately, there are only a few customers who are willing to give an assessment. The survey application cannot represent the overall feeling of the customer, so it is necessary to analyze the content of the conversation between the customer and the service personnel to determine the level of customer satisfaction. In small amounts, it can be done manually, but in large quantities it is more effective to use the system. A solution is needed in the form of a system that converts voice conversations into text and analyzes customer satisfaction to obtain information for evaluation and improvement of services. This research uses K-nearest neighbors (KNN) and term frequency-inverse document frequency (TF-IDF) algorithm with natural language processing (NLP) approach to classify conversations into 2 classes, "satisfied" and " dissatisfied ". The results of this study received 74.00% accuracy, 76.00% precision and 73.08% recall. In conversations with the label "satisfied" shows customers satisfied with the service and fulfillment of customer desires, while in conversations with the label "not satisfied" customers are less satisfied with the waiting time.
Distributed Denial Of Service (DDOS) Attack Detection On Zigbee Protocol Using Naive Bayes Algoritm Ibnu Masud; Kusrini Kusrini; Agung Budi Prasetio
International Journal of Artificial Intelligence Research Vol 5, No 2 (2021): December 2021
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (270.085 KB) | DOI: 10.29099/ijair.v5i2.214

Abstract

Distributed Denial of Service or better known as DDoS is an attempted attack from several computer systems that target a server so that the amount of traffic becomes too high so that the server cannot handle the request. DDoS is usually done by using several computer systems that are used as sources of attacks. So they attack one server through several computers so that the amount of traffic can also be higher. A DDoS attack is like a traffic jam that prevents a driver from reaching their desired destination on time. According to data, 33% of businesses in the world have fallen victim to DDoS attacks. DDoS is hard to trace. Some types of DDoS attacks can be very powerful and even reach speeds of 1.35 Tbps. Additionally, DDoS attacks can cause losses of $ 40,000 per hour if they occur. ZigBee is a standard from IEEE 802.15.4 for data communication on personal consumer devices as well as for business scale. ZigBee is designed with low power consumption and works for low level personal networks. ZigBee devices are commonly used to control another device or as a wireless sensor. ZigBee has a feature which is able to manage its own network, or manage data exchange on the network [1]. Another advantage of ZigBee is that it requires low power, so it can be used as a wireless control device which only needs to be installed once, because only one battery can make ZigBee last up to a year. In addition, ZigBee also has a "mesh" network topology so that it can form a wider network and more reliable data. In the previous research of Muhammad Aziz, Rusydi Umar, Faizin Ridho (2019) based on the results of the analysis carried out that the attack information that has been detected by the IDS based on signatures needs to be reviewed for accuracy using classification with statistical calculations. Based on the analysis and testing carried out with the artificial neural network method, it was found that the accuracy was 95.2381%. The neural network method can be applied in the field of network forensics in determining accurate results and helping to strengthen evidence at trial. The Naïve Bayes model performed relatively poor overall and produced the lowest accuracy score of this study (45%) when trained with the CICDDoS2019 dataset [47]. For the same model, precision was 66% and recall was 54%, meaning that almost half the time, the model misses to identify threats. 
SISTEM PAKAR DIAGNOSA PENYAKIT KOLESTEROL DAN ASAM URAT MENGGUNAKAN METODE CERTAINTY FACTOR Patmawati Hasan; Eka Wahyu Sholeha; Yulius Nahak tetik; Kusrini Kusrini
SISFOTENIKA Vol 9, No 1 (2019): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (744.978 KB) | DOI: 10.30700/jst.v9i1.448

Abstract

Saat ini Kolestrol dan Asam urat merupakan pernyakit yang tingkat kejadianya cukup tinggi. Berdasarkan ahli dari Clinical Research Support Unit (CRSU) Fakultas Kedokteran Universitas Indonesia, Dr. Nafrialdi, PhD menyatakan bahwa 35% penduduk Indonesia memiliki kadar kolesterol lebih tinggi dari batas normal dan Menurut data WHO 2015, penderita asam urat di Indonesia terjadi pada usia dibawah 34 tahun sebesar 32% dan di atas 34 tahun sebesar 68%. Namun ketidaktahuan masyrakat umum terhadap penyakit yang dialami di karenakan mahalnya biaya yang harus di keluarkan untuk mengetahui penyakit lebih dini tanpa harus berkonsultasi ke dokter. Untuk membantu mengatasi permasalahan tersebut penulis membuat program sistem pakar yang dapat mengidentifikasi penyakit kolestrol dan asam urat masyarakat umum. Namun kemampuan sistem dalam mendiagnosa suatu gejala tidak 100% sama dengan diagnosa seorang dokter, masih banyak hal yang tidak pasti atau sehingga dapat menyebabkan kemungkinan kesalahan dalam diagnosa maka salah satu metode dalam perhitungan ketidakpastian adalah metode  certainty factor (CF). Metode Certainty Factor menyatakan kepercayaan dalam sebuah kejadian (fakta atau hipotesis) berdasarkan bukti atau penilaian pakar. Berdasarkan pengujian rekapitulasi sampel data dari 20 orang korespoden didapatkan 50% berpotensi Kolestrol, 35% berpotensi Asam Urat, dan 15% Bukan kedua penyakit. Rekapitulasi Validasi Sistem melalui pakar memberikan keakuratan 80% terhadap sistem pakar tersebut.
Sistem Pendukung Keputusan Pemilihan Suplier Hasil Tani Gabah Menggunakan Metode AHP Patmawati Hasan; Akrilvalerat Deainert Wierfi; Friden Elefri Neno; Kusrini Kusrini
SISFOTENIKA Vol 9, No 2 (2019): SISFOTENIKA
Publisher : STMIK PONTIANAK

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (588.974 KB) | DOI: 10.30700/jst.v9i2.513

Abstract

Gabah merupakan bahan pokok dalam produksi beras di PB Hikmat Tiga Berlian. Untuk menghasilkan beras dengan kualitas yang baik maka dibutuhkan pula supplier yang terbaik dan berkualitas. Salah satu upaya untuk mendapatkan supplier tersebut adalah dengan melakukan pemilihan supplier hasil tani. Namun kendala yang terjadi saat ini adalah pengambilan keputusan pada pemilihan Supplier hasil tani gabah pada saat musim panen dengan kelebihannya masing-masing. Hal ini dikarenakan petani yang membawa hasil tani hari ini dan esok hari adalah petani-petani yang berbeda. Penelitian ini bertujuan untuk merncang sistem pendukung keputusan pemilihan suplier hasil tani gabah menggunakan metode AHP. Prototype Sistem dibangun menggunkan Bahasa pemrograman PHP dan database MySQL. Sistem ini akan meghasilkan nama-nama Supllier yang terpilih untuk menyuplai gabah di PB Hikmat Tiga Berlian. Kriteria yang digunakan adalah kadar air, kadar hampa, harga, jarak lahan ke pabrik, dan transportasi. Penelitian ini menyimpulkan bahwa perancangan prototype SPK telah dapat dilakukan berdasarkan hasil pengujian User Acceptance Test dengan menggunakan 10 Respondent dan 5 pertanyaan bahwa sistem dengan menggunakan metode AHP Dalam pemilihan Supplier dapat diterapkan. Hal ini didasarkan pada nilai rata-rata hasil 68 % responden menjawab Sangat Setuju dan 26 % responden menjawab Setuju. Pengujian terhadap hasil output sistem dan hasil perhitungan manual tidak ditemukan perbedaan hasil.
Co-Authors Achmad Wazirul Hidayat Adhien Kenya Estetikha Aditya Hastami Ruger Aflahah Apriliyani Agatha Deolika Agianto Syam Halim Agung Budi Prasetio Agung Budi Prasetyo Agus Susilo Nugroho Ajie Kusuma Wardhana Akrilvalerat Deainert Wierfi Alfahmi Muhammad Arif Alva Hendi Muhammad Amir Bagja Andi Bahtiar Semma Andi Oktafiqurahman Andi Sunyoto Andi Suyoto Andris Faesal Anggit Dwi Hartanto Anjar Anjani Putra Anwar Sadad Aolia Ikhwanudin Arham Rahim Arif Fajar Solikin Arik Sofan Tohir Sofan Tohir Arnila Sandi Asro Nasiri Asro Nasiri Asro Nasrini Awanda Putra Mahendra Ayu Adelina Suyono Aziz Muslim Candra Adipradana Devina Ninosari Dimaz Arno Prasetio Dina Maulina Dody Pradipta Donny Yulianto Dwi Astuti Dwinda Etika Profesi Eka Wahyu Sholeha Eko Pramono Elik Hari Muktafin Emha Taufiq Luthfi Emha Taufiq Luthfii Erwin Apriliyanto Ewaldus Ambrosius Tukan Fandli Supandi Fendy Prasetyo Nugroho Ferry Wahyu Wibowo Fiyas Mahananing Puri Friden Elefri Neno Hadryan Eddy Hanafi Hanafi Hanif Al Fatta Hasirun Hasirun Henderi . Heri Abijono Heri Sismoro Hery Nurmawan Hery Siswanto Ibnu Masud Ichsan Wasiso Idris Idris Iin Kurniasari Imam Listiono Irma Darmayanti Irwan Oyong Juwari Juwari Kaharuddin Kanafi Kanafi Khoirun Nisa Khomsatun Khomsatun Kumara Ari Yuana Kusnawi Kusnawi Kusuma Chandra Kirana M rudyanto Arief M. Idris Purwanto M. Nurul Wathani M. Rudiyanto Arief M. Rudyanto Arief M. Zainal Arifin Mahmudi Mahmudi Mansur Mansur Marwan Noor Fauzy Mei P Kurniawan Mei P. Kurniawan Mei Parwanto Kurniawan Moh. Badri Tamam Moh. Rizal Bayu Saputro Mohammad Rezza Pahlevi Muh Saerozi Muhamad Fatahillah Z Muhamad Yusuf Muhammad Fajrian Noor Muhammad Resa Arif Yudianto Muhammad Riandi Widiyantoro Muhammad Riza Eko S Muhammad Rudyanto Arief Mukti Ali Mulia Sulistiyono Muqorobin Muqorobin Muslihah, Isnawati Musthofa Galih Pradana Nanang Prasetiyantara Nibras Faiq Muhammad Noor Abdul Haris Noviyanti P. Nur Hamid Sutanto Okta Ihza Gifari Paradise Paradise Pawit Srentiyono Prabowo Budi Utomo Pramono Pramono Prasetyo, Adi Prastowo, Wahit Desta Reflan Nuari Retzi Yosia Lewu Ridlan Ahmad Rifan Ferryawan Ripto Sudiyarno Rita Wati Riyan Abdul Aziz Rizki Mawan Robi Wariyanto Abdullah Rona Guines Purnasiwi Rudyanto Arief Saikin Sapto Pamungkas Sigit Pambudi Siti Fatonah Siti Hartinah Siti Rahayu Siti Rokhmah Slamet Slamet Sri Handayani Sri Wulandari Sry Faslia Hamka Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudiana Sudiana Sugi Harsono Supriantara Supriantara Supriatin Supriatin Supriyati Supriyati Syaiful Ramadhan Teguh Sri Pamungkas Tito Prabowo Tonny Hidayat Tri Andi Tri Anggoro Tri Haryanti Tutik Maryana Tutut Dwi Prihatin Umdatur Rosyidah Vera Wati Victor Saputra Ginting Wahyu Adie Saputro Widdi Djatmiko Winarnie Winarnie Yohakim Benedictus Samponu Yovita Kinanti Kumarahadi Yudha Chirstianto F Yuliana Yulita Fatma Andriani Yulius Nahak tetik Yuni Ambar S Yusuf Fadlila Rachman Zul Hisyam Zulkipli Zulkipli Zumratul Muahidin