<p class="Abstrak">Prediksi  kelulusan  dibutuhkan  oleh  manajemen  perguruan  tinggi  dalam  menentukan kebijakan  preventif  terkait  pencegahan  dini  kasus drop  out. Lama masa studi setiap mahasiswa bisa disebabkan dengan berbagai faktor.  Dengan  menggunakan <em>data mining</em> algoritma <em>naive bayes</em> dan <em>neural network</em> dapat  dilakukan  prediksi  kelulusan  mahasiswa di  STMIK  Widya  Cipta  Dharma (WiCiDa) Samarinda . Atribut yang digunakan yaitu, umur saat masuk kuliah, klasifikasi kota asal Sekolah Menengah Atas, pekerjaan ayah, program studi, kelas, jumlah saudara, dan Indeks Prestasi Kumulatif (IPK). Sampel mahasiswa yang lulus dan <em>drop-out</em> pada tahun 2011 sampai 2019 dijadikan sebagai data <em>training</em> dan data <em>testing</em>. Sedangkan angkatan 2015–2018 digunakan sebagai data target yang akan diprediksi masa studinya. Sebanyak 3229 mahasiswa, 1769 sebagai data <em>training</em>, 321 sebagai data <em>testing</em>, dan 1139 sebagai data target. Semua data diambil dari data mahasiswa program strata 1, dan tidak mengikut sertakan data mahasiswa D3 dan alih jenjang/transfer.  Dari data <em>testing </em>diperoleh tingkat akurasi hanya 57,63%. Hasil penelitian menunjukkan banyaknya kelemahan dari hasil prediksi <em>naive bayes</em> dikarenakan tingkat akurasi kevalidannya tergolong tidak terlalu tinggi. Sedangkan akurasi prediksi <em>neural network</em> adalah 72,58%, sehingga metode alternatif inilah yang lebih baik. Proses evaluasi dan analisis dilakukan untuk melihat dimana letak kesalahan dan kebenaran dalam hasil prediksi masa studi.</p><div><div><p><em><strong>Abstract</strong></em></p><p class="Abstract"><em>Graduation predictions are required by the higher education institution preventive policies related to the early prevention of drop-out cases. The duration of study, for each student can be caused by various factors. By using the data mining algorithm Naive bayes and neural network, the student graduation in STMIK Widya Cipta Dharma (WiCiDa) can be predicted. The attributes used are as follows: age at admission, classification of cities from high school, father’s occupation, study program, class, number of siblings, and grade point average (GPA). Samples of students who graduated and dropped out between year 2011 and 2019 were used as training data and testing data. While the year class of 2015to 2018 is used as the target data, which will be predicted during the study period. According to the data mining algorithm Naive bayes, there are 3229 students; 1769 as training data, 321 as testing data, and 1139 as target data. All data is taken from students enrolled in undergraduate program and does not include data on diploma students and transfer student. From the testing data, an accuracy rate only 57.63%. The other side, prediction accuracy of the neural network is 72.58%, so this alternative method is the best chosen. The research results show the many weaknesses of the results of prediction of Naive bayes because the level of accuracy of its validity is not high. The evaluation and analysis process are conducted to see where the errors and truths are in the results of the study period predictions.</em></p><p><em><strong><br /></strong></em></p></div></div>

This investigation's goal is to examine how foreign investment and labour have an impact on Indonesia's economic development. Quarterly data for the years 2000 to 2020 are the ones that were used. GDP per capita serves as a proxy for economic growth, with labour and foreign investment serving as independent variables. Auto-regressive Distributed Lag (ARDL), which may examine the link between the independent variable and the dependent variable in both the long- and short-term, is the data analysis technique that is utilized. Thus, whereas labour has no effect on economic growth over the long term, it has a negative and considerable impact on it in the short-term economic growth is positively and significantly impacted by foreign direct investment, but long-term effects are negligible.

Research on the improvement of environmental consulting services with the development of the CV website. Fahmi  Jaya is a research to make it easier for the public to obtain complete and up-to-date information because information is felt to be very important in making decisions and in achieving goals. In addition to obtaining complete and up-to-date information, the website can also send and publish information to the wider community online. The system development method used in this research is the System Development Life Cycle (SDLC) method, or better known as the system development life cycle in system engineering and software engineering, is the process of making and changing systems and the models and methodologies used to develop these systems. The results of the research are expected that this system can publish its activities for more recent information so that the public can find out the activities that have been carried out, the ease of information about CV FAHMI JAYA.

The research to build Website Profile of Tenggarong Kelurahan is a study to facilitate the public to obtain complete and up-to-date information because the information is felt to be very important in decision making and in achieving goals. In addition to obtaining complete and up-to-date information, the website can also send and publish information to the wider community online. The system development method used in this research is the System Development Life Cycle (SDLC) method, or better known as the system development life cycle in system engineering and software engineering, is the process of making and changing systems and the models and methodologies used to develop these systems. The long-term goal to be achieved is that it is hoped that this system will be able to publicize its activities for more up-to-date information so that the public can find out about the activities that have been carried out, ease of information on the procedures for handling correspondence in the Melayu Tenggarong village to the public at large. So that the specific target of using the Tenggarong Kelurahan website as an effective medium for delivering information can be achieved.

Penelitian ini dibuat untuk mengatasi berbagai kendala yang dihadapi oleh Madrasah Aliyah Negeri 1 Samarinda , dalam membangun website ini didukung sistem database MySQL dan menggunakan Dreamweaver sebagai web editor yang didukung Apache sebagai web server, serta bantuan dari alat bantu pengembangan system flowchart serta menggunakan   bahasa PHP ( PHP Hypertext Preprocessor ) yang memiliki fasilitas diantaranya halaman utama, galery ,sejarah dan informasi lainnya yang berkaitan dengan sekolah . Metode yang digunakan dalam pengembangan web ini adalah waterfall sedangkan metode pengujian yang dipakai adalah blackbox dan beta . Dengan dibangunnya website ini maka akan diperoleh manfaat yang besar bagi sekolah , juga memberikan kemudahan dalam menerima dan memberi informasi-informasi yang dibutuhkan oleh setiap Siswa , guru dan Seluruh Masyarakat pada umumnya.