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Abdul Fadlil
Ahmad Dahlan University
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Analisis Metode AHP dan Promethee pada Sistem Pendukung Keputusan Penilaian Kompetensi Soft Skills Karyawan yuminah, Yuminah; Umar, Rusydi; Fadlil, Abdul
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 1: Februari 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

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

Abstract

Perusahaan sangat membutuhkan karyawan yang mempunyai kompetensi (soft skills) sikap dan perilaku yang baik untuk menghadapi orang lain dalam menyelesaikan pekerjaan, contohnya komunikasi, kejujuran, kerjasama dan interpersonal. Untuk melakukan penilaian kompetensi soft skills membutuhkan berbagai kriteria yang sangat beragam. Kriteria-kriteria yang terkait untuk menilai sikap dan perilaku sangat banyak, sehingga untuk melakukan penilaian kompetensi soft skills ini dengan hasil yang tepat dan cepat perusahaan mengalami kesulitan. Kondisi tersebut menunjukan bahwa perusahaan  membutuhkan  sebuah sistem yang dapat digunakan untuk penilaian kompetensi soft skills karyawan menggunakan alat bantu berupa komputer. Ada beberapa metode yang dapat digunakan untuk pengambilan keputusan dengan berbagai kriteria di antaranya AHP dan Promethee.  Maka fokus dalam penelitian ini adalah menggunakan metode AHP untuk menentukan pembobotan dan Promethee untuk pemeringkatan penilaian soft skills karyawan. Hasil pembobotan yang diperoleh untuk kriteria komunikasi 41%, kejujuran 38%, kerjasama 14% dan interpersonal 7%. Dengan rasio indeks konsistensi 6%. Dari jawaban responden diperoleh 58 % karyawan mempunyai kompetensi soft skills baik dan 42 % karyawan  kurang baik.AbstractCompanies that really need employees who need competencies (soft skills) Good attitudes and relationships to complete other people's work, for example communication, honesty, cooperation and interpersonal. To evaluate soft skills competencies requires a variety of criteria that are very diverse. The related criteria to assess attitudes and behavior are very many, so to evaluate this soft skills competency with the right and quick results the company has difficulties. This condition shows that companies need a system that can be used to assess the competency of employees' soft skills using computer-assisted tools. There are several methods that can be used for decision making with various criteria including AHP and Promethee. So the focus in this study is to use the AHP method to determine weighting and Promethee to rank the assessment of employee soft skills. The weighting results obtained for communication criteria were 41%, honesty 38%, cooperation 14% and interpersonal 7%. With a consistency index ratio of 6%. From the respondents' answers obtained 58% of employees have good soft skills competency and 42% of employees are not good.
Aplikasi Sistem Temu Kembali Angket Mahasiswa Menggunakan Metode Generalized Vector Space Model Suprianto, Suprianto; Fadlil, Abdul; Sunardi, Sunardi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 6 No 1: Februari 2019
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2593.915 KB) | DOI: 10.25126/jtiik.2019611184

Abstract

Banyak hal yang dapat dilakukan untuk memajukan sebuah perguruan tinggi, salah satunya adalah dengan melakukan evaluasi terhadap angket Mahasiswa pada setiap semester. Salah satu perguruan tinggi yang ada di Kota Tarakan Kalimantan Utara adalah STMIK PPKIA Tarakanita Rahmawati. Banyaknya data yang terdapat pada angket mahasiswa PPKIA membuat pengguna kesulitan menemukan informasi yang sesuai dengan kata kunci yang diberikan. Angket mahasiswa berisi penilaian mahasiswa terhadap pengajaran dosen, pelayanan adminitrasi dan fasilitas kampus yang dibuat dalam bentuk form yaitu memilih grade nilai dari sangat tidak baik sampai dengan sangat baik. Selain itu juga terdapat penilaian dalam bentuk esay yaitu berupa saran dan komentar. Pengisian angket dilakukan pada akhir semester berjalan. Penelitian ini bertujuan untuk menemukan informasi data angket yang relevan terhadap kata kunci. Aplikasi dibangun berbasis web dengan bahasa pemrograman PHP. Aplikasi yang dibuat hanya menggunakan basisdata masih mempunyai kekurangan yaitu tidak dapat mengurutkan dokumen sesuai dengan kata kunci, dikarenakan pengurutan dokumen hanya berdasarkan urutan dokumen pada basisdata saja. Dengan memanfaatkan teknik information retrieval (IR) yang diterapkan pada aplikasi, pengguna akan sangat terbantu dalam menemukan informasi yang dibutuhkan. Aplikasi yang dibuat dapat menampilkan dan mengurutkan dokumen yang paling mirip dengan kata kunci. Aplikasi dibangun dengan metode Generalized Vector Space Model (GVSM) sebagai dasar untuk menyelesaikan permasalahan yang ada. Metode GVSM adalah IR atau biasa disebut sistem temu kembali untuk mencocokkan term atau kata dari kata kunci yang digunakan. Dari hasil uji coba terhadap 5 kata kunci diperoleh nilai precision sebesar 72% dan recall sebesar 100% dengan waktu proses selama 34.4 detik AbstractMany things can be done to advance a university, one of which is by evaluating the Student questionnaire every period. One of the universities in Tarakan City, North Kalimantan is STMIK PPKIA Tarakanita Rahmawati. The large amount of data contained in PPKIA student questionnaires makes it difficult for users to find information that matches the given keywords. Student questionnaires contain student assessments of lecturer teaching, administrative services and campus facilities that are made in the form of selecting grades from very bad to very good. In addition there are also assessments in the form of essays, in the form of suggestions and comments. The questionnaire will be filled in at the end of the period. This study aims to find questionnaire data information that is relevant to the keyword. The application is built web-based with the PHP programming language. Applications that are made using only databases still have a disadvantage of not being able to sort documents according to keywords, because sorting documents is only based on the order of documents on the database only. By utilizing information retrieval (IR) techniques that are applied to the application, users will be very helpful in finding the information needed. The application created can display and sort documents that are most similar to keywords. Applications are built with the Generalized Vector Space Model (GVSM) method as a basis for solving existing problems. The GVSM method is IR or commonly called a retrieval system to match the terms or words of the keywords used. From the results of trials on 5 keywords, the precision value of 72% and recall of 100% were obtained with a processing time of 34.4 seconds.
Analisis Perbandingan Metode Regresi Linier Dan Importance Performance Analysis (IPA) Terhadap Kepuasan Pengguna Pada Layanan E-Government Menggunakan Metode WebQual Modifikasi Septa, Frandika; Yudhana, Anton; Fadlil, Abdul
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 5: Oktober 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020752294

Abstract

Layanan excellent merupakan layanan yang mampu memberikan rasa kepuasan bagi penggunanya, sehingga menimbulkan loyalitas terhadap layanan yang digunakan. Layanan E-Government menjadi penting untuk dilakukan penilaian kualitas layanannya terhadap kepuasan pengguna, karena salah satu tujuan dikembangkannya E-Government adalah memberikan pelayanan yang maksimal kepada masyarakat. Penelitian ini bertujuan untuk menganalisis tingkat kualitas layanan E-Government dalam kasus ini website SIMSARPRAS berdasarkan persepsi pengguna dari website SIMSARPRAS, yaitu madrasah dan operator kementerian agama. Jumlah responden adalah 500 orang yang dikumpulkan dari hasil penyebarah kuesioner secara online menggunakan Google Formulir. Metode dalam penelitian ini menggunakan metode WebQual modifikasi sebagai indikator dalam penyusunan kuesioner secara online, dan metode analisa menggunakan regresi linier berganda dan importance performance analysis (IPA). Hasil kuesioner diolah dan dilakukan pengujian instrumen dengan uji validitas dan uji reliabilitas untuk menunjukkan bahwa kuesioner layak dijadikan sebagai bahan penelitian lebih lanjut untuk dilakukan analisis data. Hasil analisis data diklasifikasikan berdasarkan persentase kepuasan pengguna terhadap layanan webiste SIMSARPRAS dengan tiga klasifikasi, yaitu baik, sedang dan buruk. Hasil analisis data menggunakan regresi linier berganda menunjukkan bahwa website SIMSARPRAS berkualitas sedang, sedangkan dengan IPA website berkualitas baik. Hasil analisis data menggunakan regresi linier berganda diketahui bahwa variabel bebas mampu mempengaruhi kepuasan pengguna sebesar  67,6% dan 32,4% dipengaruhi oleh variabel lainnya, sedangkan hasil dari IPA tingkat kesesuaian sebesar 96,22% dan tingkat kesenjangan antara kinerja dan harapan dari layanan E-Government sebesar –0,12. Hasil dari penelitian ini memberikan kontribusi kepada kementerian agama khususnya sebagai pemilik website SIMSARPRAS untuk dijadikan sebagai bahan referensi dan evaluasi layanan SIMSARPRAS kedepannya. AbstractExcellent service is a service that provides a sense of satisfaction for its users, thereby giving rise to loyalty to the services used. E-Government services are important to do. E-Government services to user satisfaction, because one of the goals that E-Government is developing to provide maximum service to the community. This study analyzes the level of quality of E-Government services in this case the SIMSARPRAS website based on user perceptions from the SIMSARPRAS website, namely madrasah and operators of the ministry of religion. The number of respondents was 500 people collected from the results of a questionnaire search using Google Forms. The method in this study uses the WebQual modification method as an indicator in testing online questionnaires, and the analysis method uses multiple linear regression and performance analysis of interest (IPA). The results of the questionnaire were processed and tested by an instrument with a validity test and a reliability test to prove the questionnaire was worthy of being used as further research material for data analysis. The results of data analysis are based on the percentage of user satisfaction with the SIMSARPRAS website service with three classifications, namely good, moderate and bad. The results of data analysis using multiple linear regression showed a medium-quality SIMSARPRAS site, whereas with a good quality website IPA. The results of data analysis using multiple linear regression owned by independent variables can increase user satisfaction by 67.6% and 32.4% required by other variables, while the results of the IPA level of suitability are 96.22% and the level is in accordance with the results and expectations of the service E-Government is -0.12. The results of this study contribute to the special ministry of religion as the owner of the SIMSARPRAS website for use as a reference material and SIMSARPRAS service solutions going forward.
Identifikasi Emosi Manusia Berdasarkan Ucapan Menggunakan Metode Ekstraksi Ciri LPC dan Metode Euclidean Distance Helmiyah, Siti; Riadi, Imam; Umar, Rusydi; Hanif, Abdullah; Yudhana, Anton; Fadlil, Abdul
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 6: Desember 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020722693

Abstract

Ucapan merupakan sinyal yang memiliki kompleksitas tinggi terdiri dari berbagai informasi. Informasi yang dapat ditangkap dari ucapan dapat berupa pesan terhadap lawan bicara, pembicara, bahasa, bahkan emosi pembicara itu sendiri tanpa disadari oleh si pembicara. Speech Processing adalah cabang dari pemrosesan sinyal digital yang bertujuan untuk terwujudnya interaksi yang natural antar manusia dan mesin. Karakteristik emosional adalah fitur yang terdapat dalam ucapan yang membawa ciri-ciri dari emosi pembicara. Linear Predictive Coding (LPC) adalah sebuah metode untuk mengekstraksi ciri dalam pemrosesan sinyal. Penelitian ini, menggunakan LPC sebagai ekstraksi ciri dan Metode Euclidean Distance untuk identifikasi emosi berdasarkan ciri yang didapatkan dari LPC.  Penelitian ini menggunakan data emosi marah, sedih, bahagia, netral dan bosan. Data yang digunakan diambil dari Berlin Emo DB, dengan menggunakan tiga kalimat berbeda dan aktor yang berbeda juga. Penelitian ini menghasilkan akurasi pada emosi sedih 58,33%, emosi netral 50%, emosi marah 41,67%, emosi bahagia 8,33% dan untuk emosi bosan tidak dapat dikenali. Penggunaan Metode LPC sebagai ekstraksi ciri memberikan hasil yang kurang baik pada penelitian ini karena akurasi rata-rata hanya sebesar 31,67% untuk identifikasi semua emosi. Data suara yang digunakan dengan kalimat, aktor, umur dan aksen yang berbeda dapat mempengaruhi dalam pengenalan emosi, maka dari itu ekstraksi ciri dalam pengenalan pola ucapan emosi manusia sangat penting. Hasil akurasi pada penelitian ini masih sangat kecil dan dapat ditingkatkan dengan menggunakan ekstraksi ciri yang lain seperti prosidis, spektral, dan kualitas suara, penggunaan parameter max, min, mean, median, kurtosis dan skewenes. Selain itu penggunaan metode klasifikasi juga dapat mempengaruhi hasil pengenalan emosi. AbstractSpeech is a signal that has a high complexity consisting of various information. Information that can be captured from speech can be in the form of messages to interlocutor, the speaker, the language, even the speaker's emotions themselves without the speaker realizing it. Speech Processing is a branch of digital signal processing aimed at the realization of natural interactions between humans and machines. Emotional characteristics are features contained in the speech that carry the characteristics of the speaker's emotions. Linear Predictive Coding (LPC) is a method for extracting features in signal processing. This research uses LPC as a feature extraction and Euclidean Distance Method to identify emotions based on features obtained from LPC. This study uses data on emotions of anger, sadness, happiness, neutrality, and boredom. The data used was taken from Berlin Emo DB, using three different sentences and different actors. This research resulted in inaccuracy in sad emotions 58.33%, neutral emotions 50%, angry emotions 41.67%, happy emotions 8.33% and bored emotions could not be recognized. The use of the LPC method as feature extraction gave unfavorable results in this study because the average accuracy was only 31.67% for the identification of all emotions. Voice data used with different sentences, actors, ages, and accents can influence the recognition of emotions, therefore the extraction of features in the recognition of speech patterns of human emotions is very important. Accuracy results in this study are still very small and can be improved by using other feature extractions such as provides, spectral, and sound quality, using parameters max, min, mean, median, kurtosis, and skewness. Besides the use of classification methods can also affect the results of emotional recognition. 
Perbandingan Metode Smart dan Maut untuk Pemilihan Karyawan pada Merapi Online Corporation Nasution, Musri Iskandar; Fadlil, Abdul; Sunardi, Sunardi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 6: Desember 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021863583

Abstract

Penelitian ini merancang sistem untuk menentukan pemilihan karyawan terbaik menggunakan Sistem Pendukung Keputusan (SPK). Perhitungan sistem menggunakan metode SMART dan MAUT. SMART merupakan metode pengambilan keputusan multiatribut yang setiap alternatif terdiri dari sekumpulan atribut dan setiap atribut mempunyai nilai-nilai. Sedangkan MAUT didasarkan pada konsep dimana pembuat keputusan dapat menghitung utilitas dari setiap alternatif menggunakan fungsi MAUT dan dapat memilih alternatif dengan utilitas tertinggi. Metode SMART digunakan karena perhitungannya lebih sederhana dan memungkinkan penambahan serta pengurangan alternatif tanpa mempengaruhi perhitungan pembobotan mengingat jumlah karyawan bisa berkurang dan bertambah secara tidak teratur. Sedangkan metode MAUT digunakan karena memunculkan hasil urutan peringkat dimana akan muncul hasil nilai terbesar sampai nilai terkecil sehingga dapat diketahui karyawan dengan terbaik dengan nilai tertinggi. Sehingga dapat mengambil keputusan dengan efektif atas persoalan yang kompleks dengan menyederhanakan dan mempercepat proses pengambilan keputusan. Metode penelitian yang digunakan adalah metode pengembangan sistem model waterfall, metodologi ini terdapat tahapan-tahapan kegiatan yang harus dilakukan dalam merancang suatu sistem. Perhitungan menggunakan 30 sampel data karyawan dan empat kriteria penilaian. Empat kriteria tersebut adalah presensi dengan bobot 40, masa kerja dengan bobot 30, ijin dengan bobot 20, dan disiplin dengan bobot 10. Data karyawan yang digunakan adalah karyawan yang sama dalam kedua metode serta mempunyai data penilaian yang sama. Hasil perhitungan menggunakan SMART dan MAUT menunjukkan bahwa keduanya dapat diimplementasikan dan berfungsi dengan baik untuk menentukan karyawan terbaik. Dengan menggunakan data alternatif, nilai alternatif, dan bobot kriteria yang sama diperoleh hasil bahwa metode SMART memberikan hasil yang lebih baik dengan 22 peringkat, sedangkan metode MAUT menghasilkan 18 peringkat. Semakin banyak jumlah peringkat yang muncul maka semakin baik karena mampu meminimalisir nilai preferensi yang sama, sehingga perankingan alternatif dapat dilakukan dengan baik. AbstractThis study designed a system to determine the best employee selection using a Decision Support System (SPK). System calculations using the SMART and MAUT methods. SMART is a multi-attribute decision making method in which each alternative consists of a set of attributes and each attribute has values. Whereas MAUT is based on the concept where decision makers can calculate the utility of each alternative using the MAUT function and can choose alternatives with the highest utility. The SMART method is used because the calculation is simpler and allows the addition and subtraction of alternatives without affecting the weighting calculation given the number of employees can be reduced and increased irregularly. While the MAUT method is used because it raises the ranking order results in which the largest value will appear until the smallest value so that it can be known by the employee with the highest value. So that they can make decisions effectively on complex issues by simplifying and accelerating the decision making process. The research method used is the method of developing the system waterfall model, this methodology there are stages of activities that must be carried out in designing a system. The calculation uses 30 employee data samples and four assessment criteria. The four criteria are presence with a weight of 40, tenure with a weight of 30, permission with a weight of 20, and discipline with a weight of 10. Employee data used are the same employees in both methods and have the same assessment data. The results of calculations using SMART and MAUT indicate that both can be implemented and function properly to determine the best employees. By using alternative data, alternative values, and the same criteria weights, the results obtained that the SMART method gives better results with 22 ratings, while the MAUT method yields 18 ratings. The more number of ratings that appear, the better because it is able to minimize the same preference value, so that alternative ranking can be done well. 
Penentuan Guru Berprestasi Menggunakan Metode Analytical Hierarchy Process (AHP) dan VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) Hanif, Kharis Hudaiby; Yudhana, Anton; Fadlil, Abdul
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 9 No 6: Desember 2022
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2022934628

Abstract

Guru merupakan bagian penting dalam memajukan suatu bangsa, karena guru dapat membimbing generasi penerus bangsa. Oleh karena itu penilaian guru berprestasi dibutuhkan untuk menciptakan generasi penerus bangsa yang baik. Penelitian AHP dan VIKOR bertujuan menghasilkan alternatif guru berprestasi di SMA N 2 Purbalingga. Metode AHP digunakan karena  mempunyai kelebihan dalam pembobotan setiap kriteria yang tidak dimiliki oleh VIKOR, metode VIKOR digunakan untuk perangkingan alternatif guru berprestasi. Tahapan-tahapan penelitian yaitu pengumpulan data, menentukan bobot kriteria, metode AHP, metode VIKOR, perhitungan manual dan sistem. Kriteria yang digunakan ada empat kriteria yaitu pedagogik, kepribadian, sosial, dan profesional. Nilai setiap kriteria akan diproses menggunakan metode AHP untuk mendapatkan bobot kriteria. Bobot kriteria selanjutnya dihitung menggunakan  metode VIKOR untuk mendapatkan alternatif guru berprestasi. Hasil perhitungan bobot prioritas kriteria dengan metode AHP dari kriteria pedagogik sampai profesional adalah 0,2236; 0,4187; 0,1162; 0,2414. Nilai-nilai tersebut merupakan nilai bobot kriteria yang akan digunakan untuk metode VIKOR. Bobot kriteria digunakan bersama dengan hasil dari pengisian kuesioner dalam VIKOR dengan data alternatif guru berprestasi untuk mendapatkan alternatif guru berprestasi. Metode AHP dan VIKOR diuji kebenarannya agar bobot dan perangkingan dapat dinyatakan benar. Hasil pengujian menggunakan black box didapatkan persentase 100%, oleh karena itu penelitian SPK dapat dinyatakan sesuai dan hasil perangkingan dapat menyelesaikan masalah yang ada di SMA N 2 Purbalingga. AbstractTeachers are an important part of advancing a nation, because teachers can guide the nation's future generations. Therefore, the assessment of outstanding teachers is needed to create a good future generation of the nation. AHP and VIKOR research aims to produce an alternative for outstanding teachers at SMA N 2 Purbalingga. The AHP method is used because it has advantages in weighting each criterion that VIKOR does not have, the VIKOR method is used for alternative ranking of outstanding teachers. The stages of the research are data collection, determining the criteria weights, the AHP method, the VIKOR method, manual and system calculations. There are four criteria used, namely pedagogic, personality, social, and professional. The value of each criterion will be processed using the AHP method to obtain the weight of the criteria. The weight of the criteria is then calculated using the VIKOR method to obtain an alternative for outstanding teachers. The results of the calculation of the criteria priority weight using the AHP method from pedagogic to professional criteria are 0.2236; 0.4187; 0.1162; 0.2414. These values are the criteria weight values that will be used for the VIKOR method. The weights of the criteria are used together with the results of filling out the questionnaire in VIKOR with alternative data for outstanding teachers to get alternatives for outstanding teachers. The AHP and VIKOR methods are tested for accuracy so that the weight and ranking can be declared correct. The results of the test using a black box obtained a percentage of 100%, therefore the SPK research can be declared appropriate and the ranking results can solve the problems that exist in SMA N 2 Purbalingga. 
Center of Pressure Control for Balancing Humanoid Dance Robot Using Load Cell Sensor, Kalman Filter and PID Controller Wulandari, Cisi Fitri; Fadlil, Abdul
Control Systems and Optimization Letters Vol 1, No 2 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v1i2.22

Abstract

Balance control on the Lanage Jagad humanoid dance robot is one of the means to create flexible dance movements in the robot movement system to make it more stable and can reduce the frequency of the robot falling or being unable to maintain balance when performing the dance. For the position of the robot, it can use a weight sensor or load cell sensor, the sensor measures the resistance value that can control the weight of 4 weight points on each robot leg which will later be converted into a pressure value at each point, in the study. This test was carried out with the same control behavior using an inertial sensor MPU6050. The balance on the robot uses a balance based on a load cell, which is a situation where the position of the robot in coordinates approaches the center of balance or CoP (Center of Pressure) at coordinates (0,0) or if using MPU6050 it is in a far error value condition so that it can balance the conditions so as not to falls close to the value of the robot state based on ZMP (Zero Moment Point) and CoG (Central of Gravity) as the MPU6050 sensor placement. In this study, for the balance control system using the Arduino MEGA 2560 PRO Board as a complement to the OpenCM 9.04 microcontroller, using 8 load cell sensors to determine the balance point which has been made predictions of pressure from the load cell using a kalman filter also PID control to handle the servo motor. The results from the center point of the robot's pressure have succeeded in determining the center of balance or CoP based on the X coordinates of 0 and the Y coordinates of 0 and the quadrant direction based on the center of gravity, so that the results of the balance system in standing and dancing conditions are based on the center of balance using a load cell, the success rate when standing by 87.5% and balance when dancing by 89%.
Wood Type Identification System using Naive Bayes Classification Yulianto, Muhammad Anas; Fadlil, Abdul
Control Systems and Optimization Letters Vol 1, No 3 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v1i3.52

Abstract

Wood, a forest product and natural resource, is a raw material used to make household goods. Some types of wood have almost the same pattern or structure. Wood quality varies greatly depending on the tree species and the environmental conditions in which it grows. This makes it challenging to identify the type of wood, especially for wooden furniture users. Therefore, wood classification is essential to ensure that the wood used meets the required quality standards and requirements. Automatic classification of wood using image processing has several advantages and can make it easier for humans. One of the image processing methods for wood classification is the Naïve Bayes method. Feature extraction technique using GLCM using contrast, correlation, energy, and homogeneity attributes. The GLCM methods can be combined to create a system design to distinguish five wood species using an image-based wood type identification system. The study results have successfully designed a system to determine five types of wood using the framework of an image-based wood type identification system. An application system has been produced to distinguish five types of wood using the framework of an image-based wood type identification system with the GLCM feature extraction method and the Naive Bayes classification method. The application system successfully identified wood species with a test accuracy rate of 88%.
Identification of White Blood Cells Using Machine Learning Classification Based on Feature Extraction Musliman, Anwar Siswanto; Fadlil, Abdul; Yudhana, Anton
JOIN (Jurnal Online Informatika) Vol 6 No 1 (2021)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v6i1.704

Abstract

In various disease diagnoses, one of the parameters is white blood cells, consisting of eosinophils, basophils, neutrophils, lymphocytes, and monocytes. Manual identification takes a long time and tends to be subjective depending on the staff's experience, so the automatic identification of white blood cells will be faster and more accurate. White blood cells are identified by examining a colored blood smear (SADT) and examined under a digital microscope to obtain a cell image. Image identification of white blood cells is determined through HSV color space segmentation (Hue, Saturation Value) and feature extraction of the Gray Level Cooccurrence Matrix (GLCM) method using the Angular Second Moment (ASM), Contrast, Entropy, and Inverse Different Moment (IDM) features. The purpose of this study was to identify white blood cells by comparing the classification accuracy of the K-nearest neighbor (KNN), Naïve Bayes Classification (NBC), and Multilayer Perceptron (MLP) methods. The classification results of 100 training data and 50 white blood cell image testing data. Tests on the KNN, NBC, and MLP methods yielded an accuracy of 82%, 80%, and 94%, respectively. Therefore, MLP was chosen as the best classification model in the identification of white blood cells.
Classification of Stunting in Children Using the C4.5 Algorithm Yunus, Muhajir; Biddinika, Muhammad Kunta; Fadlil, Abdul
JOIN (Jurnal Online Informatika) Vol 8 No 1 (2023)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v8i1.1062

Abstract

Stunting is a disease caused by malnutrition in children, which results in slow growth. Generally, stunting is characterized by a lack of weight and height in young children. This study aims to classify stunting in children aged 0-60 months using the Decision Tree C4.5 method based on z-score calculations with a sample size of 224 records, consisting of 4 attributes and 1 label, namely Gender, Age, Weight, Height, and Nutritional Status. The results of the study obtained a C4.5 decision tree where the Age variable influenced the classification of stunting with the highest Gain Ratio of 0.185016337. Meanwhile, the evaluation of the model using the Confusion matrix resulted in the highest accuracy of 61.82% and AUC of 0.584.
Co-Authors Aang Anwarudin Abdul Azis Achmad Nugrahantoro Aditiya Dwi Candra Ahmat Taufik Aji Pamungkas Alfiansyah Imanda Putra Alfiansyah Imanda Putra Alfian Amiruddin, Nanda Fahmi Andrianto, Fiki Anggit Pamungkas Annisa, Putri Anton Yudhana Anwar Siswanto ANWAR, FAHMI Arief Setyo Nugroho Arief Setyo Nugroho Arif Budi Setianto Arif Budiman Arif Budiman Arif Wirawan Muhammad Aris Rakhmadi Asno Azzawagama Firdaus Atmojo, Dimas Murtia Aulia, Aulia Az-Zahra, Rifqi Rahmatika Aznar Abdillah, Muhamad Bagus Primantoro Basir, Azhar Candra, Aditiya Dwi Darajat, Muhammad Nashiruddin Davito Rasendriya Rizqullah Putra Dewi Soyusiawaty Dhimas Dwiki Sanjaya Dian Permata Sari Dianda Rifaldi Dikky Praseptian M Dimas Murtia Atmojo Doddy Teguh Yuwono Dwi Susanto Dwi Susanto Edy Fathurrozaq Egi Dio Bagus Sudewo Eko Prianto Eko Prianto Elvina, Ade Ermin Al Munawar Ermin Ermin Esthi Dyah Rikhiana Fahmi Anwar Fahmi Auliya Tsani Fahmi Auliya Tsani Fahmi Fachri Fanani, Galih Faqihuddin Al-anshori Faqihuddin Al-Anshori, Faqihuddin Fathurrahman, Haris Imam Karim Fauzi Hermawan Fiki Andrianto Firmansyah Firmansyah Firmansyah Firmansyah Firmansyah Yasin Fitri Muwardi Furizal Gusrin, Muhaimin Gustina, Sapriani Hafizh, Muhammad Nasir Hanif, Abdullah Hanif, Kharis Hudaiby Harman, Rika Helmiyah, Siti Hendril Satrian Purnama Herdiyanto, Erik Herman Herman Herman Yuliansyah, Herman Herman, - Ibnu Rifajar Ibrahim Mohd Alsofyani Ihyak Ulumuddin Ikhsan hidayat Ilhamsyah Muhammad Nurdin Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Irjayana, Rizky Caesar Irwansyah Irwansyah Izzan Julda D.E Purwadi Putra januari audrey Jayawarsa, A.A. Ketut Jogo Samodro, Maulana Muhamammad Joko Supriyanto Joko Supriyanto Kamilah, Farhah Kartika Firdausy Khoirunnisa, Itsnaini Irvina Kusuma, Nur Makkie Perdana Laura Sari Lestari, Yuniarti Lestari, Yuniarti Lin, Yu-Hao Luh Putu Ratna Sundari M. Nasir Hafizh Maftukhah, Ainin Maulana Muhammad Jogo Samudro Mini, Ros Mohd Hatta Jopri Muammar Mudinillah, Adam Mufaddal Al Baqir Muh. Fadli Hasa Muhaimin Gusrin Muhajir Yunus Muhamad Daffa Al Fitra Muhamad Rosidin Muhammad Faqih Dzulqarnain, Muhammad Faqih Muhammad Johan Wahyudi Muhammad Kunta Biddinika Muhammad Ma’ruf Muhammad Nasir Hafizh Muhammad Nur Faiz Muhammad Nurdin, Ilhamsyah Muhammad Rizki Setyawan Muntiari, Novita Ranti Murinto Murinto - Murinto Murinto Murni Murni Musliman, Anwar Siswanto Mustofa Mustofa Muwardi, Fitri Nasution, Dewi Sahara Nasution, Musri Iskandar Nurwijayanti Pahlevi, Ryan Fitrian Ponco Sukaswanto Poni Wijayanti Prabowo, Basit Adhi Prayogi, Denis Priambodo, Bambang Putra, Fajar R. B Putri Annisa Putri Annisa Putri Purnamasari Putri Silmina, Esi Ramadhani, Muhammad Ramdhani, Rezki Razak, Farhan Radhiansyah Rezki Rezki Rifqi Rahmatika Az-Zahra Rizky Andhika Surya Rochmadi, Tri Roni Anggara Putra Rusydi Umar Rusydi Umar S Sunardi S, Sunardi Saad, Saleh Khalifah Safiq Rosad Saifudin Saifudin Saifullah, Shoffan Saleh khalifa saad Santi Purwaningrum Sarmini Sarmini Septa, Frandika Setyaputri, Khairina Eka Setyaputri, Khairina Eka Setyaputri, Khairina Eka Shinta Nur Desmia Sari Siti Helmiyah Subandi, Rio Sukaswanto, Ponco Sukma Aji Sulis Triyanto Sunardi Sunardi Sunardi Sunardi, Sunardi Surya Yeki Surya Yeki Syamsiar, Syamsiar Syarifudin, Arma Tole Sutikno Tresna Yudha Prawira Tresna Yudha Prawira Tri Ferga Prasetyo Tristanti, Novi Tuswanto Tuswanto Virdiana Sriviana Fatmawaty Wahju Tjahjo Saputro Wahyusari, Retno Winoto, Sakti Wintolo, Hero Wulandari, Cisi Fitri Yana Mulyana Yana Mulyana Yasidah Nur Istiqomah Yeki, Surya Yohanni Syahra Yossi Octavina Yulianto, Dinan Yulianto, Muhammad Anas Yuminah yuminah yuminah, Yuminah Yuminah, Yuminah Yuwono Fitri Widodo Zein, Wahid Alfaridsi Achmad Zulhijayanto -