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All Journal CYCLOTRON Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Jurnal JEETech
Abd Rabi
Universitas Merdeka Malang
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Klasifikasi Tingkat Kematangan Kopra Mengunakan Metode naïve bayes Yunaldi Adang; Abd Rabi; Rahman Arifuddin
CYCLOTRON Vol 3, No 1 (2020): CYCLOTRON
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (425.364 KB) | DOI: 10.30651/cl.v3i1.4307

Abstract

Abstrak-NegaraoIndonesiaomemiliki banyakojenis macamoperkebunan, salahosatunya yaituoperkebunan kelapa. Salahosatu bentuk pengolahanokelapa adalahodengan menjadikannyaokopra. Kopra adalahokelapa yangotelah dikeluarkanoisinya danodikeringkan. Pengeringan kopraobiasanya dengan caraopengasapan, danopengeringan dibawah sinaromatahari. Perkembanganoperangkat kerasodan perangkat lunakokomputer yang begitu cepat dan didukungokonsep data miningoberupa klasifikasiopola sertaoteknik-teknik pengolahanocitra, maka diharapkan penentuanoklasifikasi kualitasokopra dengan bantuanokomputer dapatodirealisasikan untukomembantu mempercepat pekerjaanomanusia pada umumnyaodan penjual kopraosecara khususnya.otujuan penelitianoini adalahomembangun aplikaasiountuk memperdiksiopersentase kekeringanosampel dagingokelapao(kopra). Salah satuocaraomeningkatkanonilaioekonomisokopra terutama untukopasar ekspor danomempermudah petani dalam membedakan kualaitasokopra dan hargaojual menjadiolebih baik sesuai dengan tingkat kematangannya. Dengan memperhatikan halotersebut maka penulis melakukanopenelitian denganojudul “Klasifikasi Tingkat  KematanganoKopraoMengunakanoMetode SegmentasioNaiveoByes’’.  Kata kunci- Kopra ,oRaspberry pi,oKamera,oCitra Digital Abstract-Indonesiaohas manyotypes ofoplantations,oone ofowhich isococonut plantations.oOne form ofococonut processing isoby making it copra.oCopra is coconutothat has been extracted and dried.oCopra drying is usually by fogging,oand drying inothe sun.oThe developmentoof computerohardware andosoftware is so fastoand supported by theoconcept of data mining inothe form of patternoclassification andoimage processingotechniques, it is expected that the determination of copra quality classifications with the help of computers can be realized to help speed up human work in general and copra tokeh in particular. the purpose of this study was to develop an applicationoto predict theopercentage ofococonut meato(copra) drought.oOne of the waysoto improveocopra economic value is mainly for the export market and it is easy for farmers to differentiate copra quality and selling priceoaccording to their level ofomaturity.oWith that in mind,othe authorsoconducted a studyoentitled "Copra MaturityoClassification Using theoDigital ImageoNaive Byes". Keywords - Copra,oRaspberry pi,oCamera,oDigitaloImage
Citra Identifikasi Warna dengan Metode Nilai Hue Secara Realtime Berbasis Web Camera dan Raspberry Pi Karitas Darson; Yandhika Surya Akbar Gumilang; Abd Rabi
Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) 2023: SNESTIK III
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/p.snestik.2023.4100

Abstract

Di era society 5.0 dimana teknologi sudah berkembang cukup masif perlunya adaptasi pada masyarakat untuk mulai mengimplementasikan teknologi pada kehidupan sehari-hari. Salah satunya yaitu teknologi dibidang pengolahan citra. Penelitian ini mengimplementasikan pengolahan citra untuk mendeteksi 6 warna. 6 warna yaitu merah, kuning, hijau, ungu, biru, dan oranye. Digunakan raspberry pi sebagai otak proses dan web camera 2 megapiksel sebagai inputan. Pendeteksian warna menggunakan metode nilai hue. Deteksi warna merah rentang nilai hue 1 sampai 4, oranye 5 sampai 22, kuning 23 sampai 32, hijau 33 sampai 77, biru 78 sampai 130 dan violet 131 sampai 169. Setelah dilakukan penelitian, dapat disimpulkan bahwa penelitian ini dapat dinyatakan valid karena memiliki presentase pendeteksian 88% berhasil mendeteksi 6 warna. Jika warna yang dideteksi diluar 6 warna yang sudah ditentukan maka alat akan mendeteksi warna yang rentang hue-nya mendekati.
Deteksi Kantuk Untuk Keamanan Berkendara Berbasis Pengolahan Citra Charlos Kurniawan Umbu Nggiku; Abd Rabi; Subairi Subairi
Jurnal JEETech Vol. 4 No. 1 (2023): Nomor 1 May
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/jeetech.v4i1.4107

Abstract

Traffic accidents are increasing in Indonesia. One of the main causes of accidents is driver fatigue. Drowsiness generally occurs at night when the body needs rest. However, some are caused by fatigue during activities. When driving a car, this situation must be taken into account to avoid the number of accidents caused by fatigue. Because of these problems, we need a tool that can detect automatically whether the driver is asleep or conscious using the facial landmark method. The initial process starts with streaming the camera by the webcam which will be processed by the raspberry pi 3b to detect the face area using the eye aspect ratio then the algorithm on the eye aspect ratio is used to detect sleepy eyes with the output in the form of a speaker, where the speaker will emit a sound that can be changed according to at the will of the driver. This research succeeded in designing a drowsiness detection device and obtaining data from tests that have been carried out by detecting closed or closed eyes with accuracy results using the facial landmark method and eye aspect ratio detecting drowsiness with an average accuracy of 90.4%.
Co-Authors Arifuddin, Rahman Charlos Kurniawan Umbu Nggiku Karitas Darson Subairi Subairi Yandhika Surya Akbar Gumilang Yunaldi Adang