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Sistem Penjadwalan Kuliah Menggunakan Metode Algoritma Genetika (Studi Kasus: Fakultas Kedokteran Dan Kesehatan Universitas Muhammadiyah Jakarta)

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Sistem Penjadwalan Kuliah Menggunakan Metode Algoritma Genetika (Studi Kasus: Fakultas Kedokteran Dan Kesehatan Universitas Muhammadiyah Jakarta) CORE Metadata, citation and similar papers at core.ac.uk Provided by STUDIA INFORMATIKA: JURNAL SISTEM INFORMASI Studia Informatika: Jurnal Sistem Informasi , 9(2), 2016, 177-188 SISTEM PENJADWALAN KULIAH MENGGUNAKAN METODE ALGORITMA GENETIKA (STUDI KASUS: FAKULTAS KEDOKTERAN DAN KESEHATAN UNIVERSITAS MUHAMMADIYAH JAKARTA) Andrie Tri Laksono1, Meinarini Catur Utami2, Yuni Sugiarti3 Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Syarif Hidayatullah Jakarta Jl. Ir. Juanda No. 95 Ciputat 15412 Indonesia Email: [email protected], [email protected], [email protected] ABSTRAK Pada penelitian ini terdapat permasalahan yang terjadi pada Fakultas Kedokteran dan Kesehatan Universitas Muhammadiyah Jakarta (FKK UMJ) yaitu dengan adanya dosen yang sebagian besar berprofesi sebagai dokter mengakibatkan sulitnya menentukan jadwal kuliah yang tepat sesuai dengan kesiapan waktu dosen mengajar yang sering berubah dan lokal yang tersedia terbatas, selain itu proses pembuatan penjadwalan kuliah yang masih manual mengakibatkan sulitnya mengelola data penjadwalan kuliah. Penelitian ini bertujuan merancang Sistem Informasi Penjadwalan Perkuliahan Berbasis Web dengan Metode Algoritma Genetika yang merupakan sarana terkait proses penentuan jadwal perkuliahan. Sistem ini digunakan untuk FKK UMJ bidang akademik dalam membuat jadwal perkuliahan, serta memudahkan staf akademik, dosen dan mahasiswa mengakses data penjadwalan kuliah. Metode penjadwalan menggunakan Algoritma Genetika, metode pengumpulan data yaitu studi pustaka dan studi lapangan (wawancara dan observasi) dan studi literatur sejenis, dan metode pengembangan sistem menggunakan Rapid Application Development (RAD) dengan pemodelan menggunakan UML, serta menggunakan PHP dengan framework Laravel, MySql, Codelobster sebagai tools dan software dalam pengembangan sistem. Hasil penelitian ini dapat memberikan kemudahan dalam mengelola penjadwalan kuliah yang tepat sesuai kesiapan waktu dosen mengajar dan lokal yang tersedia sehingga membantu proses pembuatan jadwal perkuliahan menjadi lebih baik lagi. Kata kunci: Sistem Informasi, Penjadwalan, FKK UMJ, Perkuliahan, Algoritma Genetika, Rapid Application Development (RAD), PHP, Laravel, MySql, Codelobster, UML. 1. Pendahuluan profesi sebagai dokter. Adanya dosen-dosen luar ini menyebabkan sulitnya menentukan jadwal kuliah yang Universitas Muhammadiyah Jakarta (UMJ) tepat sesuai dengan kesiapan waktu mereka dan lokal merupakan salah satu institusi pendidikan tinggi agama yang tersedia, dimana kesiapan waktu mengajar dosen Islam di Indonesia. UMJ memiliki 9 Fakultas dengan (dosen luar) dan lokal sangatlah terbatas. Kesulitan 43 Program Studi yang meliputi Fakultas Ekonomi, menentukan jadwal kuliah tersebut dikarenakan belum Fakultas Teknik, Fakultas Agama Islam, Fakultas tersedianya sistem yang secara khusus melakukan Pertanian, Fakultas Kedokteran dan Kesehatan, penjadwalan kuliah karena untuk proses penjadwalan Fakultas Ilmu Pendidikan dan Fakultas Ilmu masih dilakukan secara manual belum terotomasi oleh Keperawatan serta sekolah Pasca Sarjana yang sistem, sehingga angka kesalahan semakin besar dan memiliki sejumlah program magister yang meliputi membutuhkan waktu yang lama untuk membuat jadwal Magister Ilmu Hukum, Magister Studi Islam, Magister dan sering kali terjadi jadwal yang bentrok yang Manajemen, Manajemen Ilmu Administrasi, Magister menyebabkan proses belajar mengajar terhambat. Akuntansi, Magister Kesehatan Masyarakat dan Mahasiswa juga merasa kesulitan apabila ada Magister Ilmu Keperawatan. Saat ini, UMJ tengah perubahan jadwal. Dimana untuk pengumuman jadwal memproses dibukanya program doktor untuk bidang masih manual yaitu menggunkan papan pengumuman. Ilmu Agama, Manajemen dan Bisnis dan Ilmu Hukum. Hal ini yang menyebabkan sulitnya sosialisasi jadwal Fakultas Kedokteran dan Kesehatan merupakan kuliah terbaru apabila terjadi perubahan. salah satu fakultas yang terdapat di UMJ yang Untuk memudahkan dalam proses penjadwalan memiliki sistem informasi akademik yang dikelola tersebut, Fakultas Kedokteran dan Kesehatan merasa secara tersendiri. Dalam bidang akademik, Fakultas perlu dibuatnya sistem yang dapat memudahkan Kedokteran dan Kesehatan ini memerlukan pembuatan jadwal kuliah yang secara otomatis dosen-dosen yang berkualitas dalam hal belajar menempatkan kesiapan mengajar dosen pada lokal mengajar yang saat ini masih menggunakan yang tersedia secara optimal. Penulis mengajukan dosen-dosen dari luar dan sebagian besar memiliki algoritma genetika sebagai metode untuk mencari 177 Copyright ©2016, Studia Informatika: Jurnal Sistem Informasi, P-Issn 1979-0767 Sistem Penjadwalan kuliah.. Laksono, AT, Dkk solusi dari suatu permasalahan penjadwalan kuliah bit, pohon, array bilangan real, daftar aturan, elemen yang berkaitan dengan optimalisasi ruangan yang permutasi, elemen program, atau representasi lainnya terbatas dengan kesiapan dosen yang terbatas. Di yang dapat diimplementasikan untuk operator genetika. dalam banyak kasus metode ini memiliki solusi yang String Biner optimal dan sangat efektif. 0 1 0 | 1 0 0 1 | 0 1 1 1 Berdasarkan latar belakang di atas, penulis Gen 1 Gen 2 Gen 3 bermaksud mengangkat permasalahan tersebut untuk b. Fungsi Fitness menyusun skiripsi dengan judul “RANCANG Fungsi Fitness, alat ukur yang digunakan untuk BANGUN SISTEM INFORMASI PENJADWALAN proses evaluasi kromosom. Nilai fitness dari suatu KULIAH BERBASIS WEB DENGAN METODE kromosom akan menunjukkan kualitas kromosom ALGORITMA GENETIKA (STUDI KASUS : dalam populasi tersebut [8]. Rumusan fitness yang FAKULTAS KEDOKTERAN DAN KESEHATAN digunakan adalah sebagai berikut : UNIVERSITAS MUHAMMADIYAH JAKARTA)”. F = ∑ Kesediaan Waktu Dosen Minggu 2. Landasan Teori F = Fitness A. Pengertian Rancang Bangun ∑ = Jumlah Keseluruhan Menurut Stair dan Reynolds [7], Perancangan c. Prosedur Inisialisasi sistem adalah fase pengembangan sistem yang Ukuran populasi tergantung pada masalah yang akan mendefinisikan bagaimana sistem informasi akan dipecahkan dan jenis operator genetika yang akan melakukan perancangan untuk mendapatkan solusi diimplementasikan. Setelah ukuran populasi di pemecahan masalah. Sedangkan menurut Laudon dan tentukan, kemudian harus dilakukan inisialisasi Laudon [5], Perancangan Sistem merupakan terhadap kromosom yang terdapat pada populasi keseluruhan rencana atau model untuk sistem yang tersebut. Inisialisasi kromosom dilakukan secara acak, terdiri dari semua spesifikasi sistem yang memberikan namun demikian harus tetap memperhatikan domain bentuk dan struktur. solusi dan kendala permasalahan yang ada [8]. d. Pembangkitan Populasi Awal B. Pengertian Penjadwalan Populasi awal dibangun secara acak, sedangkan Penjadwalan adalah pengurutan pembuatan atau populasi berikutnya merupakan hasil evolusi pengerjaan produk secara menyeluruh yang dikerjakan kromosom-kromosom melalui iterasi yang disebut pada beberapa buah mesin. Dengan demikian masalah generasi [8]. sequencing senantiasa melibatkan pengerjaan sejumlah e. Fungsi Evaluasi komponen yang sering disebut dengan istilah job. Job Ada 2 hal yang harus dilakukan dalam melakukan sendiri masih merupakan komposisi dari sejumlah evaluasi kromosom, yaitu evaluasi fungsi objektif elemen-elemen dasar yang disebut aktivitas atau (fungsi tujuan) dan konversi fungsi objektif ke dalam operasi. Tiap aktivitas atau operasi ini membutuhkan fungsi fitness. Secara umum, fungsi fitness diturunkan alokasi sumber daya tertentu selama periode waktu dari fungsi objektif dengan nilai yang tidak negatif. tertentu yang sering disebut dengan waktu proses [6]. Fungsi objektif adalah fungsi yang nilainya akan dioptimalkan. Fungsi objektif bisa bernilai maksimum C. Algoritma Genetika dan minimum tergantung pada kasusnya. Jika fungsi Algoritma genetika merupakan evaluasi atau objektif biaya produksi, maka nilainya dicari yang perkembangan dunia komputer dalam bidang minimum. Tapi kalau fungsi objektifnya berupa kecerdasan buatan (artificial intelligence). keuntungan, maka nilainya yang maksimum. Kemunculan algoritma genetika ini terinspirasi oleh f. Kriteria optimasi tercapai teori Darwin dan teori-teori dalam ilmu biologi, Beberapa kriteria berhenti yang sering digunakan sehingga banyak istilah dan konsep biologi yang antara lain : digunakan dalam algoritma genetika, karena sesuai 1. Berhenti pada generasi tertentu. dengan namanya, proses-proses yang terjadi dalam 2. Berhenti setelah beberapa generasi berturut-turut algoritma genetika sama dengan apa yang terjadi pada didapatkan nilai fitness tertinggi/terendah. evaluasi biologi [10]. 3. Berhenti bila dalam n generasi berikutnya tidak Menurut Kusumadewi (dalam Ulisna Ade Rifai diperoleh nilai fitness yang lebih [12]), Terdapat 8 komponen utama dalam algoritma tinggi/rendah. genetika, yaitu : g. Operator genetika a. Teknik Penyandian Operator standar yang biasa digunakan dalam Teknik penyandian disini meliputi penyandian gen algoritma genetika adalah selection, crossover dan dari kromosom. Gen merupakan bagian dari mutation. Berikut ini akan dijelaskan masing-masing kromosom. Satu gen biasanya akan mewakili satu operator yaitu : [1] variabel. Variabel adalah suatu sebutan yang dapat 1. Seleksi diberi nilai angka (kuantitatif) atau nilai mutu Seleksi bertujuan memberikan kesempatan (kualitatif). Variabel merupakan pengelompokan secara reproduksi yang lebih besar bagi anggota populasi logis dari dua atau lebih atribut dari objek yang diteliti yang paling fit. Langkah pertama dalam seleksi ini [11]. Gen dapat direpresentasikan
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