The Development and Operations (DevOps) method is develops tasks that are operationalized by IT staff including server management. DevOps is a server, coding, and tester bridge so that it can be activated automatically so that the programmer does not need to do it repeatedly. Server management is still mostly done manually by doing repetitive settings on one server and another server so that it is inefficient and requires a relatively long time, the solution by adding several employees will increase the work of making users and user management on all servers, the occurrence of human errors and burdens costs for the company. Ansible is one type of configuration management tools that can be used for the infrastructure management process from a manual program to an automatic. In this study the implementation and testing of Ansibel was done in server management. Ansibel can configure and manage user account settings on all servers automatically.

Anemia is a lack of blood condition with reduction in hemoglobin as one of indicator.  According to data from the Basic Health Research in 2013, the prevalence of anemia sufferers in Indonesia was high at 37.1%. The figure was almost close to severe public health problems with an anemia prevalence limit of more than 40%. However, this was not accompanied by low public knowledge about anemia.Therefore, researcher created an anemia mobile learning application based on android to increase people knowledge about anemia in everytime.There were quizzes randomly issued using the Linear Congruent Method algorithm. Linear Congruent Method algorithm, which was an algorithm that produced random permutations from a finite set. Testing Linear Congruent Method (LCM) algorithm was able to produce an effective randomization problem, where there was no repetition of the same value if the value of the declared variable meets the determination parameters of the existing LCM Algorithm i.e. the increment value and modulus must be relatively prime.  

The ability to produce a scientific work both journals, scientific articles and thesis is needed to support the competence of undergraduate students in a university. The existence of a thesis course in a number of universities is one of the efforts to train students in producing a scientific work. To arrive at the stage of making a thesis, a student must first study various kinds of courses in each study program. Choosing a thesis topic is one of the most difficult stages in the preparation of a thesis. This is because there are still many students who do not understand and know their interest and ability in one of the courses which will later be used as a topic in thesis preparation. The focus of this research is a decision support system that is able to answer student problems in determining thesis topics according to their abilities. The method used is a waterfall within the SDLC (system development life cycle) framework starting from system requirement, data collection, design, implementation, testing, and maintenance. The result of this research is the ability of the decision support system to provide recommendations for thesis topics according to the abilities of students. The greatest weight is for A5 students for Computer Networking interest of 1,410 while the smallest weight is for A4 students for Multimedia interest of 0.080.

Geographically Semarang regency as one of the regencies in Central Java province has an area of 95,020.67 hectares. In this study, the sub-district areas in Semarang regency is calculated using Circle Approach method and Karney s Polygon method using Google Earth and GADM database in the form of latitude and longitude coordinates. The results of the study show that the land area of 19 districts in Semarang regency is 11.61% more than of the reference areas based on the coordinates of the latitude and longitude on Google Earth using the circle approach method. While the percentage for the area referring to GADM data using the Karney s Polygon method is 9.71% more than of the reference areas and the difference is 13.55% more than the reference areas using Circle Approach. The results of the three comparisons show that GADM data using the Karney s Polygon method can produce better results than other methods.

Android smartphone is one of the items that really help humans in living life today.A person gets information through an internet connection using an Android smartphone whenever and wherever he is. Home Services is a vehicle repair service on site. Thus, customers still get service without leaving activity. The Home Service System is still manual so that it gives customers the opportunity to find out about ordering and scheduling vehicle services. Therefore, the researchers tried to build an Android-based Home Service application using the First Come First Served algorithm to facilitate scheduling. Analytical methods conducted by researchers by collecting data through Literature Studies and Interviews. Thus, resulting in an easier, practical, simple, and efficient Home Services application where customers can schedule vehicle services via an Android Smartphone.

Prediction of student satisfaction with academic services needs to be done to evaluate the performance of higher education institutions in the academic field, especially at Pandanaran University. In this study, using the Decision Tree C4.5 algorithm data mining method in classifying student data through a questionnaire on aspects of tangible, reliability, assurance, responsiveness and empathy. The results of classifying student data using the Decision Tree C4.5 algorithm produce a decision tree model with an accuracy value of 87.92% and AUC 0.990.

Pengenalan karakter plat nomor kendaraan memiliki peran penting untuk tujuan identifikasi secara resmi, penerapanya telah banyak dilakukan untuk identifikasi otomatis seperti pada tol elektronik, tempat parkir, dsb. Penelitian berkaitan dengan pengenalan karakter setidaknya memiliki fase-fase seperti segmentasi, fitur extraksi dan klasifikasi dimana tiap fase memiliki proses yang rumit. Keberhasilan dalam proses pengenalan karakter sangat tergantung dalam proses fitur ekstraksi, Sehingga pemilihan metode fitur ekstraksi yang dapat mengekstrak fitur-fitur yang relevan perlu dilakukan agar tingkat akurasi sistem pengenalan karakter dapat ditingkatkan. discrete wavelet transform telah banyak digunakan sebagai metode untuk ekstraksi fitur, metode ini melakukan ekstraksi dengan melakukan dekomposisi pada  ruang vektor ke dalam ruang vektor bersarang dengan resolusi yang berbeda. Dalam penelitian ini metode discrete wavelet transform dikombinasikan dengan support vector machine untuk meningkatkan akurasi pengenalan karakter. Penelitian dilakukan dengan mengukur tingkat akurasi dari 100 citra plat nomor, dengan penambahan metode discrete wavelet transform dan support vector machine tingkat akurasi klasifikasi mencapai 92% yang artinya   mendapatkan peningkatan akurasi sebesar 8% dibanding klasifikasi menggunakan SVM standar.

Agriculture is a pillar of the economy a nation, with the system and the implementation of good agricultural, so will go the nation economic.One of the causes of the lack of agricultural productivity in Indonesian that is some farmers in Indonesian still relied on climate change rain without blemish. Climate change has caused planting patterns the farmers, so that in the end agricultural products planted could not stable , any process planting .The instability caused the price of agricultural products to be very significant plant at a certain season.This is what causes the thing farmers have to produce more energy and the cost of extra do watering manually so that of the trees can grow fertile and can be harvest pakcoy especially in plants .To overcome the problems hence writers try to make sprinkler system plant with using microcontroller Wemos D1 R1 of experiment to the republic of Indonesian that in arable land plant with using soil moisture capacitive sensors that is going to be the moisture the ground in plants can be monitored over long distances through the android application named Blynk. The system will shut when discharging is out of danger at the boundary moisture expected means of sensors the humidity and turn off water pump.

Indonesia adalah negara tropis yang memiliki keanekaragaman jenis tumbuhan. Tumbuhan terdiri atas tiga organ dasar yaitu akar, batang dan daun. Daun merupakan salah satu bagian yang sering digunakan untuk mengklasifikasikan tanaman, karena setiap jenis tanaman memiliki ciri yang berbeda. Bentuk tepian daun bisa digunakan untuk acuan klasifikasi daun. Otak manusia memiliki keterbatasan dalam mengolah atau mengignat informasi jenis-jenis tanaman yang berdasarkan daun. Oleh karena itu dibutuhkan peralihan pengetahuan manual ke suatu sistem digital. Maka dalam penelitian ini dibuat sistem yang mampu melakukan pengenalan daun menggunakan ekstraksi ciri pada daun menggunakan metide Linear Discriminant Analysis ( LDA ) dan jarak Minkowski.Proses pengenalan pola citra daun diawali dengan pengambilan citra daun, kemudian masuk ke tahap prapengolahan untuk membedakan objek dengan latar belakang. Setelah itu masuk ke tahap ekstraksi ciri menggunakan Linear Discriminant Analysis (LDA ) untuk mendapatkan karakteristik ciri dari citra dan Jarak Minkowski untuk melakukan pengenalan dari pola daun.                       Berdasarkan hasil penelitian dengan jumlah data sebanyak 40 kelas dengan masing-masing kelas sebanyak 6 citra, dengan citra latih sebanyak 160 citra daun dan citra uji sebanyak 80 citra daun. Saat pengenalan menggunakan jarak minkowski menggunakan 3 koefisien yaitu koefisien minkowski 1, 2, dan 3. Dari ­ ­masing-masing koefisien minkowski didapatkan persentase keakurasian. Persentasi keakurasian saat menggunakan koefisien minkowski 1 sebesar 41,25%, koefisien minkowski 2 sebesar 33,75%, dan koefisien minkowski 3 sebesar 30%. Persentase keakurasian pada penelitian ini tidak dapat menghasilkan diangka 80% dikarenakan jumlah data sangat mempengaruhi hasil persentase, semakin banyak data yang ada maka nilai persentase juga akan semakin kecil.

Customer loyalty is an important factor to the survival of a company. The problem facting today is related to the descreasing number of customer loyalty that happened to PT MNC Play. If this is allowed   to continue it is not impossible this will endanger the continuity of the company s business.Keep in mind the factors that cause customers to have loyal and disloyal status, data mining classification techniques can be used to classify loyal and disloyal customers. Many data mining classification algorithms can be used, so it needs to be comparative to know the accuracy of each algorithm, the algorithem used is C4.5 and Na ve Bayes. The data used were 28,899MNC Play customer of Semarang City.The results of the classification   process were evaluated using cross validation, confusion matrix, ROC Curve to find the more accurate data mining classification algorithm to determine loyal and disloyal customers.Keywords: Classification, Customers Loyalty, Na ve Bayes, C4.5.