Judul: Application of the Perceptron Algorithm in  Predicting the Timely Graduation of IPB Mathematics Students
Abstrak: Tiap tahun mahasiswa baru yang mendaftar di Departemen Matematika IPB meningkat, sehingga total mahasiswa aktif semakin bertambah jumlahnya. Padahal tidak semua mahasiswa dapat lulus tepat waktu. Untuk meningkatkan jumlah mahasiswa lulus tepat waktu, Departemen Matematika IPB mengambil kebijakan untuk memberikan bantuan dan perhatian pada mahasiswa yang berpotensi lulus tidak tepat waktu. Namun hal ini memerlukan mekanisme atau metode untuk mengidentifikasi kemungkinan kelulusan tepat waktu setiap mahasiswa. Penelitian ini menerapkan algoritma perceptron untuk memprediksi kemungkinan individu mahasiswa akan lulus tepat waktu atau tidak. Algoritma ini mengklasifikasikan data dengan proses learning ke dalam dua kelas yaitu lulus tepat waktu dan lulus tidak tepat waktu. Selain itu, hasil proses testing dengan software Octave-4.4.1 memiliki tingkat akurasi sebesar 86.87%. Algoritma ini dapat melakukan pembelajaran untuk memperbaiki parameter secara periodik, sehingga memudahkan dalam memprediksi kelulusan tepat waktu mahasiswa Matematika IPB di tahun mendatang tanpa melakukan prediksi ulang., Every year the number of students enrolled in the Department of Mathematics IPB University is increased, so that the total number of active students are increasing. Meanwhile, some students graduate more than 4 years. To increase the number of students graduates on time, the Department of Mathematics IPB University take a policy to provide support and attention to students who have the potential to graduate not on time. However, this requires a mechanism or method to identify the likelihood of the timely graduation time of each student. This research applies the perceptron algorithm to predict the likelihood that individual students will graduate on time or not. In the learning stage of the algorithm, data are classified into two classes, namely graduation on time and graduation not on time. The result of the testing process by using the Octave-4.4.1 software has the accuracy rate of 86.87%. The algorithm can improve the accuracy through its learning process, making it easier to predict the timely graduation of IPB undergraduate mathematics students in the coming year without recalculating.
Keyword: graduation on time, perceptron, prediction

Judul: Penerapan Metode Rotation Forest dalam Memprediksi Status Kelulusan Mahasiswa FMIPA IPB University
Abstrak: Salah satu indikator mutu pendidikan adalah lamanya waktu yang dibutuhkan untuk menyelesaikan studi. Data yang diperoleh dari Dit-AP IPB University menyebutkan masih banyak mahasiswa FMIPA yang belum berhasil menyelesaikan studinya tepat waktu. Hal ini menjadi evaluasi bagi IPB University khususnya mahasiswa FMIPA IPB agar lebih peduli terhadap kelulusan mahasiswanya. Penelitian ini dilakukan untuk memodelkan klasifikasi data mahasiswa FMIPA IPB University tahun 2018, dengan peubah respon yaitu lulus tepat waktu dan lulus tidak tepat waktu dengan profil dan latar belakang mahasiswa sebagai peubah penjelas. Metode klasifikasi yang digunakan adalah rotation forest. Tujuan dari penelitian ini adalah untuk melihat bagaimana tingkat akurasi dalam memprediksi serta mengetahui peubah penting yang mempengaruhi status kelulusan mahasiswa. Dari hasil tersebut dapat disimpulkan bahwa rotation forest mampu memprediksi status kelulusan mahasiswa FMIPA IPB University dengan kinerja yang cukup baik. Metode ini memperoleh nilai akurasi sebesar 69,89% sebelum Synthetic Minority Oversampling Technique (SMOTE) sedangkan setelah SMOTE memperoleh nilai akurasi sebesar 76,34%. Peubah terpenting dalam model sebelum penerapan SMOTE adalah Jalur Masuk (X4), Jenis Kelamin (X1), dan IPK (X2), sedangkan setelah penerapan SMOTE adalah Jalur Masuk (X4), IPK (X2), dan UKT (X6)., One indicator of the quality of education is the length of time required to complete studies. Data obtained from Dit-AP IPB University states that there are still many FMIPA students who have not succeeded in completing their studies on time. This is an evaluation for IPB University, especially FMIPA IPB students, to be more concerned about their students' graduation. This research was conducted to model the classification of FMIPA IPB University student data in 2018, with the response variables being on-time graduation and delayed graduation with student profiles and backgrounds as explanatory variables. The classification method used is rotation forest. This study aims to assess the accuracy of prediction and to identify the variable importance that affects students' graduation status. The results show that Rotation Forest can predict the graduation status of FMIPA IPB University students with fairly good performance. This method achieved an accuracy of 69.89% before applying the Synthetic Minority Oversampling Technique (SMOTE) and 76.34% after applying SMOTE. The variable importance in the model before the implementation of SMOTE are Driveway (X4), Gender (X1), and GPA (X2), while after SMOTE implementation are Driveway (X4), GPA (X2), and Tuition Fee (X6).
Keyword: graduation status, prediction, rotation forest, variable importance

Judul: Characterizations of low alloy steel sae 4422  plated with chromic acid (Cro3)
Abstrak: Characterizations of low alloy steel SAE 4422 plated with chromic acid (CrOrO3) was use Optical Microscopy (OM), Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), RD),Energy Dispersive Analysis of X-Ray (EDAX), Hardness Test and Roughness Test. Microstructures analysis exhibits cracks and grain boundaries microcracks as a characteristics of chrome metal found at plating metal. Perlite and Ferrite as grains of steel found at base metal with grain boundaries around it. Phase analysis of plating metal appropriate to chrome metal with lattice constant (a) is 2.559 Å and phase analysis of base metal appropriate to iron ferrite with lattice constant (a) is 3.318 Å. Both plating and base metal have cubic system. Chemical analysis of plating metal at surface section exhibits that cracks area have highest value of carbon element compare with grains and grains boundaries area. While chemical analysis of base metal at cross section exhibits that perlite have highest value of carbon element compare with ferrite and grain boundaries. The hardness value of plating metal at surface section and cross section are 753 and 637 VHN. While, the hardness value of base metal and interface area at cross section are 205 and 373 VHN. The roughness value at measurement points of chrome surface for as received sample are 0.445 μm. Observation used Optical Microscopy and Scanning Electron Microscopy exhibits surface irregularities combine to form surface texture of plating metal at surface section.
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