<p>ABSTRAK. Pada umumnya sistem pembejaran di Perguruan Tinggi saat ini menggunakan media pembelajaran visual yang disalurkan melalui proyektor, sehingga masih kurang efektif untuk memvisualisasikan materi perkuliahan bagi mahasiswa. Di sisi lain, perkembangan Teknologi Informasi memungkinkan penggunaan Multimedia interaktif yang dilengkapi dengan alat pengontrol yang dapat dioperasikan oleh pengguna, sehingga pengguna dapat mengendalikan sistem pembelajaran secara efektif. Paper ini menyajikan konsep penerapan multimedia development life cycle pada aplikasi media pembelajaran interaktif. Metode pengembangan media pembelajaran berbasis Multimedia development life cycle melalui Enam tahap meliputi: konsep, perancangan, pengumpulan materi, pembuatan, pengujian dan distribusi. Hasil uji program melalui uji Blackbox menunjukkan fitur-fitur fungsionalitas telah sesuai dengan kebutuhan pengguna. Kata kunci: Media pembelajaran, Multimedia interaktif, Multimedia development life cycle <br /> <br />ABSTRACT.  In general, the current education system in tertiary institutions uses visual learning media that is channeled through a projector, so it is still ineffective in visualizing lecture material for students. On the other hand, the development of Information Technology allows the use of interactive multimedia which is equipped with a controller that can be operated by the user, so that the user can control the learning system effectively. This paper presents the concept of implementing the multimedia development life cycle in interactive learning media applications. Multimedia development life cycle based on learning media development methods through six stages including: concept, design, material gathering, manufacture, testing and distribution. The test results of the program through the Blackbox test show that the functionality features are in accordance with user needs. Keywords: Learning media, Interactive multimedia, Multimedia development life cycle</p>

<p><em>Abstrak. </em>Ujian merupakan tes evaluasi hasil belajar untuk mengetahui tingkat pemahaman siswa terhadap kompetensi tertentu dalam mengikuti sesi pembelajaran. Terdapat dua model sistem pelaksanaan ujian saat ini, yaitu model konvensional dan model <em>online</em>. Pelaksanaan ujian tidak luput dari terjadinya kecurangan, sehingga perlu ada tindakan pencegahan agar kecurangan dapat diatasi secara dini.  Artikel ini menyajikan penggunaan metode <em>Linear Congruential Generator </em>dan <em>Fisher Yates </em>untuk pengacakan soal ujian <em>online</em>. Hasil dari pengujian menunjukan bahwa dengan menggunakan metode tersebut setiap siswa mendapat soal ujian yang berbeda berdasarkan nomer nis setiap siswa, dan dengan hasil tersebut dapat mencegah kecurangan pada soal ujian.</p><p><strong>Kata kunci</strong><strong>:</strong><em> Pengacakan, Soal Ujian, Algoritma Linear Congruential Generator, Algoritma Fisher Yates.</em></p><p><em> </em></p><p><strong><em>Abstract. </em></strong><em>The test is an evaluation test of learning outcomes to determine the level of student understanding of certain competencies in participating in learning sessions. There are two models of the current test implementation system, namely the conventional model and the online model. Examination is not free from fraud, so there needs to be preventive measures so that cheating can be tackled early. This article presents the use of the Linear Congruential Generator and Fisher Yates methods for randomizing online exam questions. The results of the test show that by using this method each student gets different exam questions based on the nis number of each student, and with these results it can prevent cheating on exam questions.</em></p><p><strong><em>Keywords:</em></strong><em> Randomization, Exam Questions, Linear Congruential Generator Algorithm, Fisher Yates Algorithm.</em></p>

Coronavirus Disease (COVID-19) has made Indonesia's health condition critical. Therefore, the President of the Republic of Indonesia disclosed Presidential Decree No. 7 in 2020 regarding the Task Force for the Acceleration of Coronavirus Disease 2019 (COVID-19) Handling. The decree relates to Act No. 14 in 2008 regarding Public Information Disclosure, Presidential Regulation No. 95 in 2018 concerning Electronic-Based Government Systems, and Presidential Instruction No. 3 in 2003 concerning National Policies and Strategies for E-Government Development. The decree demands information system development, similar to https://covid19.go .id, which describes COVID-19 nationwide. The site explains what COVID-19 and data of the COVID-19 outspread with geolocation and digital map, which may attract public attention. The presidential instruction forces local governments to build an information system, which is in line with the site by the central government. This paper describes the development of the system using a spiral model. It involves a variety of free and open-source software such as CodeIgniter, Mapbox, Morris Chart, MySQL, and WordPress. The site has been operational, and it attracts 150 visitors a day with 200 visits per day. As of January 6, 2021, the website has recorded 89,852 views.

<p><strong>Abstrak. </strong>SMK Al-Mizab Sukabumi merupakan lembaga pendidikan sekolah menengah kejuruan yang ada di Jampang Tengah Sukabumi. Sekolah ini memiliki banyak data yang terkait dengan kegiatan akademik, misalnya data kelulusan siswa. Data-data tersebut belum dimanfaatkan semaksimal mungkin, misalnya untuk memprediksi kelulusan siswa, sehingga dapat diambil tindakan untuk memaksimalkan persiapan pelaksanaan ujian akhir. Penelitian ini dilakukan untuk membuat rancangan sistem aplikasi menggunakan teknik klasifikasi yang dapat mengolah data dalam jumlah besar untuk menemukan pola yang terjadi pada data siswa. Pengolahan data tersebut digunakan untuk memprediksi kelulusan siswa. Teknik klasifikasi yang digunakan yaitu decision tree dengan penerepan algoritma C4.5 Inputan yang digunakan yaitu berupa atribut dari data siswa meliputi nilai persemester dari semester 1 sampai 5, dan nilai sikap. Pengujian aplikasi menggunakan data training 104 data siswa yang sudah lulus pada tahun 2016 sampai 2018. Pengetahuan yang diperoleh dari hasil traning aplikasi diharapkan dapat dimanfaat oleh manajemen SMK Al-Mizab sebagai alat bantu pengambilan keputusan yang lebih efektif dalam rangka perencanaan dan persiapan ujian akhir siswa.</p><p><strong>Kata kunci</strong><strong>: </strong><em>Rancangan Aplikasi, Prediksi Kelulusan Siswa, Algoritma C4.5, Decision Tree</em></p><p><em> </em><strong><em>Abstract. </em></strong><em>“SMK Al-Mizab Sukabumi” is a vocational high school educational institution in Jampang Tengah Sukabumi. This school has a lot of data related to academic activities, for example student graduation data. These data have not been fully utilized, for example to predict student graduation, so that action can be taken to maximize preparation for the final exam. This research was conducted to design an application system using classification techniques that can process large amounts of data to find patterns that occur in student data. Data processing is used to predict student graduation. The classification technique used is a decision tree with a C4.5 algorithm. The input used is in the form of attributes from student data including the scores per semester from semester 1 to 5, and attitude values. Application testing uses training data of 104 student data who have passed in 2016 to 2018. The knowledge gained from the results of application training is expected to be used by the management of SMK Al-Mizab as a more effective decision-making tool in planning and preparing for student final exams.</em></p><p><strong><em>Keywords:</em></strong><em> Application Design, Student Graduation Prediction, C4.5 Algorithm, Decision Tree</em></p>

<p><em>Abstrak. </em><em>Perkembangan bidang sains dan teknologi memberikan kemudahan bagi umat manusia diberbagai aspek bidang kehidupan  salah satunya ialah peramalan. Peramalan penerimaan mahasiswa bagi perguruan tinggi swasta akan membantu memaksimalkan sumber daya yang dimiliki dan dipergunakan secara optimal untuk pelayanan, sarana dan prasarana hingga peningkatan sumber daya manusia didalam perguruan tinggi swasta. Metode regresi untuk melihat sejauh mana biaya promosi dalam peningkatan penerimaan mahasiswa ditahun mendatang dikarenkan pembiayaan promosi yang kurang tepat mengakibatkan jumlah penerimaan mahasiswa tidak sesuai harapan. Peramalan ini akan valid ketika menggunakan sebuah model tingkat keakuratan peramalan yang dilakukan. Berdasarkan hasil perhitungan penelitian ini, tingkat keakuratan dengan menggunakan model MAPE (Mean Absolute Percentage Error) sebesar 2,7% selisih antara data aktual dan data peramalan, namun setiap periode tidak semua memiliki nilai keakurtan kecil karena faktor setiap periode data yang berbeda.</em></p><p> </p><p><strong><em>Kata kunci</em></strong><strong><em>:</em></strong><em> </em><em>Peramalan, Penerimaan Calon Mahasiswa, </em><em>Metode </em><em>Regresi</em><em>, </em><em>Mean Absolute Percentage Error</em><em></em></p><p> <em>Abstract. </em><em>The development of science and technology provides the convenience for mankind in various aspects of the field of life, one of which is forecasting. Forecasting student acceptance for private universities will help maximize the resources owned and used optimally for service, facilities and infrastructure to increase human resources in private universities. The regression method to see the extent to which the cost of the promotion in the improvement of student acceptance in the future is offered less precise promotional financing resulting in the number of admission of students is not as expected. This forecasting will be valid when using a model level of forecasting accuracy done. Based on the results of this research, the level of accuracy using the Mean Absolute Percentage Error (MAPE) model amounted to 2.7% of the difference between the actual data and forecasting data, but each period does not all have a small accuracy value due to the factors of each different data period.</em></p><p><strong><em>Keyword</em></strong><em>:</em> <em>Forecasting, New Student Admission, Regression Method, Mean Absolute Percentage Error</em><strong><em></em></strong></p>