15 research outputs found
PENGARUH SIKAP KERJA DAN KNOWLEDGE SHARING TERHADAP KINERJA PEGAWAI YANG DIMEDIASI RNOLEH OCB PADA PEGAWAI SATPOL PP DAN WH ACEH
No full textDANKNOWLEDGE SHARING PADA KINERJA SATPOL PP DAN WH ACEH* Muhammad Oky, Nurdasila, Syafruddin Magister Manajemen, Universitas Syiah Kuala, Indonesia*Corresponding Author : [email protected] ini dilakukan untuk mengetahui dan menguji Pengaruh Mediating Organizational Citizenship Behavior (OCB) Pada Hubungan Antara Sikap Kerja dan Knowledge Sharing Pada Kinerja Satpol PP dan WH Aceh. Populasinya adalah semua pegawai Dinas Satpol PP dan WH Aceh yang berjumlah 907 orang. Anggota sampel ditentukan dengan menerapkan teknik probability sampling, dan juga melalui rumus Slovin diperoleh jumlah sampel sebanyak 278 orang. Skala pengukuran yang digunakan adalah skala likert dan Peralatan analisis yang digunakan adalah SEM AMOS. Hasil Pengujian Hipotesis deskriptif menunjukkan bahwa Sikap, knowledge sharing, OCB anggota, kinerja anggota Satpol PP dan WH Aceh sudah berjalan dengan baik. Pengujian hipotesis verifikatif menunjukkan bahwa sikap, knowledge sharing, dan OCB berpengaruh terhadap kinerja Satpol PP dan WH Aceh, Sikap dan knowledge sharing berpengaruh terhadap OCB, dan Terdapat pengaruh tidak langsung antara sikap dan knowledge sharing terhadap kinerja Satpol PP dan WH Aceh melalui OCB. Dalam model yang teruji ini, OCB berperan sebagai parsial mediator. Hasil temuan ini membuktikan bahwa peningkatan kinerja Dinas Satpol PP dan WH Aceh merupakan fungsi dari Perbaikan Sikap, Penerapan Knowledge Sharing, dan penerapan OCB- nya.Keyword : Sikap, Knowledge Sharing, OCB, Kinerja Satpol P
Deteksi Ddos pada Unbalanced Dataset Menggunakan PCA dan Local Outlier Factor
No full textDataset DDoS adalah salah satu data yang sering tersedia dalam bentuk tidak seimbang(Unbalanced) antara cluster data serangan dengan cluster data normal. beberapa teknik klasifikasi telah diterapkan untuk mengatasi permasalahan ini salah satunya adalah menggunakan teknik Local Outlier Factor. Tujuan dari penelitian ini adalah untuk mengevaluasi kinerja teknik LOF dalam mendeteksi paket data yang merupakan serangan DDoS.. Sebelum dataset digunakan, dilakukan pembersihan data dan seleksi fitur menggunakan PCA. Penentuan hasil secara keseluruhan menggunakan metrik F1-Score. Nilai F1-Score terendah terdapat pada pengaturan Neighbour=12 dan Contamination=0,5 sebesar 0,619205. Nilai F1-Score tertinggi terdapat pada pengaturan Neighbour=19 dan Contamination=0,1 sebesar 0,957500
Sistem Informasi Sistem Informasi Kartu Ujian Mahasiswa Politeknik Negeri Tanah Laut Berbasis Web
No full textThis research aims to develop a "Web-Based Student Examination Card Information System for Tanah Laut State Polytechnic" to address the issues of loss and damage to student examination cards that can occur in hardcopy form. The system is designed to assist the academic department of Tanah Laut State Polytechnic in searching and storing student data, supervisors, and lecturers digitally. It also helps students to print examination cards online. The information collection techniques used include observation, interviews, and literature studies, relevant to the problem topic, while the development method employed is the waterfall method. The design utilizes Unified Modeling Language (UML) diagrams and Entity Relationship Diagrams (ERD). The testing was conducted using the Black Box method. The test results indicated that all the features on the student examination card website are functioning properly.
Keywords : Student Examination Card Information System, Examination Card Website
Machine learning to Detect Palm Oil Diseases Based on Leaf Extraction Features and Principal Component Analysis (PCA)
No full textPalm oil tree is one of the economically important crops that is the backbone of the Indonesian economy. However, palm oil production is often hampered by various diseases. The disease is difficult to detect in the early stages because infected trees often show no symptoms. Therefore, it is necessary to carry out identification and classification to determine whether this palm coconut plant is sick or infected with disease. In this study the disease was identified in palm coconut by identifying it through leaves by modifying the extraction process features using PCA and comparing it with no PCA for sick and healthy types. Subsequently, the classification will be done using SVM (Support Vector Machine) with various treatments such as variation of the features used and the amount of data to be processed in carrying out experiments or tests. The results obtained show that if the feature used for classifying a number of 4 or more then the accuracy value remains at 97%
PENERAPAN GOOD MANUFACTURING PRACTICE PADA CRITICAL CONTROL POINT MAYA SARDEN KECIL UNTUK MENJAGA KEAMANAN PRODUK PANGAN
No full textJika membutuhkan abstrak atau isi jurnal silahkan menghubungi author melalui email [email protected], [email protected], [email protected]
Analisis dan Implementasi Average Difference Algorithm untuk Deteksi Spatial Outlier Pada Pilkada Kabupaten Bandung di Kecamatan Dayeuhkolot
No full textABSTRAKSI: Outlier merupakan data yang memiliki karakteristik berbeda dari data pada umumnya atau pada lingkungannya. Dalam outlier seringkali terdapat knowledge atau informasi yang sangat berguna. Salah satu masalah outlier yang muncul dari data mining adalah spatial outlier. Spatial outlier adalah objek yang tereferensi spasial dimana atribut non-spasial nya secara signifikan berbeda dari objek di sekitarnya. Terdapat banyak teknik untuk mendeteksi spatial outlier. seperti itterative approach, morran scatterplot, dll . Namun beberapa teknik tersebut tidak mempertimbangkan pengaruh dari hubungan spasial dalam sebuah lingkungan. Oleh karena itu, penulis mengajukan teknik Avgdiff (Average Difference) yang memadukan atribut non-spasial dan atribut spasial dari objek. Sehingga pengaruh hubungan spasial antar objek akan menjadi penting dan selalu dipertimbangkan. Avgdiff dapat digunakan untuk mendeteksi spatial outlier dengan baik dalam beberapa scenario pengujian berdasarkan parameter k, factor weight jarak, factor weight populasi dan parameter evaluasi detection rate dan false-positive rate.Kata Kunci : outlier, spatial outlier, avgdiff, weightABSTRACT: Outliers are data that have different characteristics from the data in general or to the environment. In this outlier there is knowledge or information is often very usefull. One outlier problem tha arise from data mining is the spatial outlier. Spatial outliers are the spatial object referenced where its non-spatial attributes are significanly different from the objects around it. There are many techniques for detecting spatial outliers. Like itterative approach, morran scatterplot, etc.. But, some of these techniques do not consider the affect of spatial relationship within the envvironment. Therefore, the author propose a avgdiff (Average Difference) techniques which combines the non-spatial attribute and spatial attributeof the object. Thus the affect of the spatial relationships between object and its neighboors would be important and must be considered. Avgdiff can be used for detecting spatial outliers well in several test scenarios based on the parameter k, the weight factor of distance, the weight factor of population and evaluation parameters detection rate and false-positive rate.Keyword: outlier, spatial outlier, avgdiff, weigh
KEINDAHAN BAHASA KITAB MAULID DHIYA’U AL-LAAMI’ BI DZIKRI MAULIDI AL-NABI AL-SYAFI’I KARYA AL-HABIB UMAR BIN MUHAMMAD BIN SALIM BIN HAFIDZ (STUDI ANALISIS STILISTIKA)
No full textOne of the special aspects of the Book of Maulid is the beauty of the language style used, which is able to captivate the hearts of both readers and listeners. This is because the Book of Maulid uses a language style that is amazing because of the harmony, beauty and harmony of its composition. This research discusses the beauty of the language of the book Maulid Dhiya'u al-Laami 'using stylistic theory. Stylistics is the study of the linguistic characteristics of a work. The realm of stylistic studies includes phonology, morphology, syntax, semantics, and imagery.
The main problem that becomes the study of this thesis is how beautiful the
language used by the author of the book is. The purpose of this study is to reveal the elements of language style in the text of literary works in the form of verses of prayer and praise to the Prophet, where the use of these language style elements has an influence on the meaning of each of these verses. This research is a library research.
The results of this study are: Phonological aspects include: language compatibility and the effect of phonology on meaning. Morphological aspects include: fi'il amr which is meant to pray, for appeal, for invitation, and ism tafdhil. Syntax aspects include: the use of ism al-nakiroh and ism al-ma'rifah, and the use of exception sentences with the letter illa. Dalali aspects include: Al-Taraduf, al-lafadz al-'aam and the repetition of the word "tikrar". Imagery aspects include: Majaz, Kinayah and Alliteration
Modified Particle Swarm Optimization on Feature Selection for Palm Leaf Disease Classification
No full textPalm oil plantations in Indonesia face challenges in enhancing productivity and profitability, notably due to pest attacks that reduce production. Early identification and classification of plant conditions, particularly palm oil leaves, are crucial for mitigating losses. This study explores the application of artificial intelligence, specifically computer vision and machine learning, for disease detection. Various machine learning techniques, including Local Binary Pattern (LBP), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM), have been used in different studies with varying accuracy. This research focuses on modifying Particle Swarm Optimization (PSO) for feature selection in identifying diseases in palm oil leaves. The PSO modification combined with logistic regression and Bayesian Information Criterion (BIC) significantly enhances KNN performance. Accuracy improved from 95.75% to 97.85%, while precision, recall, and F1-score reached approximately 98.80%. Additionally, the modified KNN+PSO achieved the shortest computation time of 0.0872 seconds, indicating high computational efficiency. These results demonstrate that the PSO modification not only improves accuracy but also computational efficiency, making it an effective method for enhancing KNN performance in detecting palm oil leaf diseases
ANALISIS PENGENDALIAN KUALITAS PRODUK DENGAN METODE SIX SIGMA DI DEPARTEMEN ROLLING MILL 3 (Studi Kasus: PT. Hanil Jaya Steel)
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