53 research outputs found
Kontroversi Program Pesbukers Di ANTV (Studi Deskriptif Kualitatif Pada Mahasiswa Sistem Informatika Fakultas Ilmu Komputer Universitas Pembangunan Panca Budi)
No full textPesbukers adalah sketsa realita yang digawangi oleh artis-artis terkenal
Indonesia, seperti Raffi Ahmad, Jessika Iskandar, Ayu Ting-ting, dan masih
banyak lainnya. ANTV merupakan stasiun televisi yang menayangkan program
ini. Pesbukers diketahui mengawali acaranya pada tahun 2011 hingga sekarang.
Semenjak tahun pertama pesbukers telah menerima penghargaan dari panasonic
gobel awards. Tetapi pesbukers juga kerap mendapatkan teguran dari KPI karena
di nilai melanggar norma-norma yang ada. Yang terakhir pada bulan ramadhan
yang lalu pesbukers di tegur KPI karena dinilai telah melanggar ketentuan dari
KPI. Tanggapan pro dan kontra bermunculan di masyarakat tanpa terkecuali
mahasiswa. Maka peneliti disini menggunakan mahasiswa sebagai
narasumbernya. Teori yang di gunakan dalam penelitian ini adalah teori
komunikasi massa, dan opini publik. Peneliti menggunakan metode deskriptif
dengan pendekatan kualitatif lalu dilanjutkan pengumpulan data dengan
wawancara secara terstruktur. Peneliti menggunakan beberapa aspek dalam
meneliti seperti segmen program, atitude artis yang ditampilkan, prestasi,
wanprestasi. Hasil dari pengumpulan data melalui beberapa aspek dengan
wawancara pada mahasiswa sistem informatika fakultas ilmu komputer
universitas pembangunan panca budi menghasilkan tanggapan positif dan negatif
terkait program pesbukers. Segmen program ada yang menarik dan tidak menarik,
atitude artis yang ditampilkan ada yang layak dan tidak layak, prestasi dinilai
layak menerima penghargaan panasonic gobel awards,namun disisi lain tidak
layak karena banyak kerap terkena tegur KPI, dan wanprestasinya dinilai buruk
dan harus tutup programnya karena kerap terkena teguran KPI namun di sisi lain
tidak harus ditutup program nya karena masih menghibur dan bisa berbenah.
Masalah terkait program pesbukers telah banyak diangkat oleh mahasiswa dalam
bentuk karya ilmiah. Namun hingga saat ini fenomena pesbukers masih saja
terjadi di tengah masyarakat
Clustering Of Students Into A Specialization Of Expertise Using Genetic Algorithms
No full textClustering mahasiswa kedalam keminatan keahlian merupakan salah satu upaya yang perlu dilakukan oleh pihak jurusan untuk menjamin mahasiswa memperoleh pendidikan yang sesuai dengan keahliannya. Saat ini, terdapat banyak metode clustering yang sudah dikembangkan oleh pakar. Umumnya metode clustering mampu mengelompokkan objek-objek yang memiliki tingkat kesamaan ciri yang tinggi, tetapi tidak mampu membatasi jumlah objek yang boleh masuk kedalam suatu kelompok. Kasus klasterisasi mahasiswa kedalam keminatan keahlian merupakan kasus clustering yang membatasi jumlah objek yang boleh masuk kedalam suatu kelompok. Dengan kondisi tersebut, metode clustering yang ada tidak dapat digunakan untuk kasus ini. Peneliti mencoba melihat kasus ini dari sudut pandang optimasi, yaitu bagaimana mengoptimalkan pembentukan kelompok keminatan mahasiswa dengan tingkat ketidaksesuaian bakat yang rendah. Untuk penyelesaian kasus ini, peneliti menggunakan algoritma genetika sebagai metode untuk penyelesaian masalah. Algoritma genetika dibagi kedalam beberapa jenis, yaitu: algoritma genetika dengan prinsip elitisme dan non elitisme, algoritma genetika dengan persentase mutasi 0.01, 0.03 dan 0.05. Berdasarkan penelitian yang dilakukan, diperoleh bahwa algoritma genetika mampu melakukan clustering mahasiswa kedalam keminatan keahlian yang disediakan oleh jurusan. Algoritma genetika dengan prinsip elitisme mampu menemukan solusi optimum yang lebih baik sebesar 39% dibandingkan dengan algoritma genetika non elitisme. Algoritma genetika dengan persentase mutasi 0.05 menghasilkan solusi optimum terbaik, namum memiliki konsumsi waktu yang paling besar dibandingkan dengan persentase 0.01 dan 0.03
Clustering Of Students Into A Specialization Of Expertise Using Genetic Algorithms
No full textClustering mahasiswa kedalam keminatan keahlian merupakan salah satu upaya yang perlu dilakukan oleh pihak jurusan untuk menjamin mahasiswa memperoleh pendidikan yang sesuai dengan keahliannya. Saat ini, terdapat banyak metode clustering yang sudah dikembangkan oleh pakar. Umumnya metode clustering mampu mengelompokkan objek-objek yang memiliki tingkat kesamaan ciri yang tinggi, tetapi tidak mampu membatasi jumlah objek yang boleh masuk kedalam suatu kelompok. Kasus klasterisasi mahasiswa kedalam keminatan keahlian merupakan kasus clustering yang membatasi jumlah objek yang boleh masuk kedalam suatu kelompok. Dengan kondisi tersebut, metode clustering yang ada tidak dapat digunakan untuk kasus ini. Peneliti mencoba melihat kasus ini dari sudut pandang optimasi, yaitu bagaimana mengoptimalkan pembentukan kelompok keminatan mahasiswa dengan tingkat ketidaksesuaian bakat yang rendah. Untuk penyelesaian kasus ini, peneliti menggunakan algoritma genetika sebagai metode untuk penyelesaian masalah. Algoritma genetika dibagi kedalam beberapa jenis, yaitu: algoritma genetika dengan prinsip elitisme dan non elitisme, algoritma genetika dengan persentase mutasi 0.01, 0.03 dan 0.05. Berdasarkan penelitian yang dilakukan, diperoleh bahwa algoritma genetika mampu melakukan clustering mahasiswa kedalam keminatan keahlian yang disediakan oleh jurusan. Algoritma genetika dengan prinsip elitisme mampu menemukan solusi optimum yang lebih baik sebesar 39% dibandingkan dengan algoritma genetika non elitisme. Algoritma genetika dengan persentase mutasi 0.05 menghasilkan solusi optimum terbaik, namum memiliki konsumsi waktu yang paling besar dibandingkan dengan persentase 0.01 dan 0.03
PENGARUH PENGANGGARAN PARTISIPATIF, GAYA KEPEMIMPINAN DAN PERILAKU PENYUSUN ANGGARAN TERHADAP SLACK ANGGARAN (STUDI PADA SKPK PEMERINTAH ACEH SELATAN)
No full textABSTRAKPenelitian ini bertujuan untuk menguji pengaruh penganggaran partisipatif, gaya kepemimpinan dan perilaku penyusun anggaran terhadap slack anggaran . Penelitian ini merupakan penelitian pengujian hipotesis dengan sumber data yang dikumpulkan melalui kuesioner dan dianalisis dengan menggunakan analisis regresi berganda. Populasi dalam penelitian ini adalah seluruh SKP K di Pemerintah Kabupaten Aceh Selatan (31 SKPK), dengan responden berjumlah 93 orang yang bertanggungjawab atas pengelolaan keuangan daerah pada masing-masing SKPK. Hasil penelitian menunjukkan bahwa penganggaran partisipatif, gaya kepemimpinan dan perilaku penyusun anggaran berpengaruh terhadap Slack Anggaran pada SKPK di Pemerintah Kabupaten Aceh Selatan baik secara bersama-sama maupun parsial.Kata kunci: Penganggaran partisipatif, gaya kepemimpinan, perilaku penyusun anggaran, slack anggaran
GROUP DECISION SUPPORT SYSTEM FOR DETERMINING THE ELIGIBILITY OF PROVIDING HOUSING ASSISTANCE TO POOR FAMILIES
No full textIt is very difficult to determine the eligibility of recipients of housing assistance for poor families, especially in gampongs, based on the number of gampong residents who apply. the large number of people who applied for assistance made it difficult for village officials and decision-makers to make decisions. The existence of a model analysis in the eligibility of recipients of housing assistance so that there is no subjectivity in the provision of assistance. The purpose of this research is to identify beneficiaries of housing assistance for underprivileged communities who meet the requirements using the Analytical Network Process (ANP) and Borda models. The variables used are parents' work (C1), number of parental dependents (C2), sources of income costs (C3), housing conditions (C4), status (C5) and education (C6). The results of selecting the ANP model were that Aminah got a score of 1.445, Hasanah (A2) 1.415, Baihaki (A3) 1.6148, Fakri (A4) 1.53. The recommendation from the ANP model analysis is baihaki with a value of 1.6148. while from the borda model the total values are A1:355, A2:355, A3:212, A4:381 A5:254, A6:209, with a weight value of 0.201, A2 weight: 0.201, A3 weight 0.120, A4 weight 0.216, A5 weight 0.144 and the weight of A6 0.118. The conclusion from the research results gives priority to the community for the highest value in obtaining housing assistance. this study which received priority baihaki with a value of 1.6148 for the results of the ANP model and the results of the value of the model group was A3 with a value of 0.272
The Determination of the Action towards the Patient’s Psychological Therapy in the Post-accident Using Case-based Reasoning
No full textThe accident that occurred to somebody will give much suffering; moreover, if the accident gives the serious injury, such as a broken bone which needs to get more seriously treatment. Not only does the patient need the action towards his/her injury, but also he/she needs the psychological therapy in facing the problems happened which is suggested by a psychologist. One of the reasoning method in expert systems is Case-Based Reasoning (CBR). In Case-Based Reasoning, a case-based consists of various cases in conditions or symptoms and solution (the psychological therapy) given. To find out the solution from a new problem given, the system will find any cases in the case-based which have higher the degree of similarity between the cases. This research develops a case-based reasoning system to decide the action of the psychological therapy towards the patients in the post-accident who needs seriously treatment. The psychological therapy involves in giving assistance, consultation, psychiatrist support, and the compound of various actions as well. A case study was conducted from the medical records of psychological treatment at ‘Dr Soeharso’ hospital in Surakarta. Based on the result of the research developed, the action of psychological therapy upon the patient has successfully determined. They have accuracy rates of 60% in the threshold 50% compared to the treatments resulted from the psychologist. The result was found by calculating the degree of similarity between the new issue and all cases existing in the case base.</jats:p
Analyze the Clustering and Predicting Results of Palm Oil Production in Aceh Utara
No full textPT. Perkebunan Nusantara 1 is engaged in oil palm production with a total land area of 1,144 Ha. The formulation of this research can determine productive land clusters based on land area, number of trees, number of stages, and palm oil production. Methodological steps include plantation area data and oil palm production data. This study can compare the C-means and K-means groups. As for predictions using the Backpropagation Neural Network (BPNN) algorithm and Fuzzy time series for production results. The results of grouping Cot girek palm oil production data for the 2019-2022 period from January to December were 1,365,530, while in 2022 it reached 1,768,720. The analysis used a land grouping method of 1,144 hectares, which resulted in 800.4 hectares of productive land and 343.6 hectares of less effective land. The results of the C-menas clustering model are more than K-meas with shorter iterations while for predictions it has an accuracy rate of 90.77%. As a comparison, the level of accuracy of the fuzzy time series is 81.27%. The results of this study can be used as recommendations for companies in the analysis of productive land grouping analysis and forecast results from these lands
The Nutritional Classification of Pregnant Women Using Support Vector Machine (SVM)
No full textDetermining the nutritional status of pregnant women is one of the efforts to control the condition of pregnant women so that they can adjust their health conditions properly. The health condition of pregnant women can affect the condition of the baby who will be born. This study aims to apply the SVM method to a web-based application to classify the nutritional status of pregnant women based on data obtained from several health centers in the city of Lhokseumawe. SVM functions as the core of the application in charge of classifying the nutritional status of pregnant women based on several features including: age, weight, height, lila, hemoglobin and BMI. While the data class consists of 3 categories, namely: undernourished, normal nutrition and normal nutrition + overweight. Primary data obtained from the field amounted to 355 data which were then divided into two parts with a ratio of 70% training data and 30% testing data. Based on the research conducted, it was found that the application of different kernels in the Support Vector Machine (SVM) will have a different performance impact in classifying data. In this study, the linear kernel has the best performance with an accuracy value of 0.84, the RBF kernel has an accuracy value of 0.83, the polynomial kernel has an accuracy value of 0.72, and the sigmoid kernel has the worst performance with an accuracy value of 0.5
Naïve Bayes Classification Algorithm Application on Nutritional Status of Pregnant Women in Lhokseumawe City
No full textThe nutritional status of pregnant women is a measure of success in fulfilling nutrition for pregnant women. Poor nutritional status of pregnant women will cause an imbalance of nutrients which can cause nutritional problems in pregnant women. Therefore, we need a system that can predict the nutritional status of pregnant women. This can be implemented by utilizing the naïve Bayes classification algorithm. This research was carried out with the aim of further studying how to apply the Naïve Bayes algorithm to predict the nutritional status of pregnant women, and how the success of this application is based on the accuracy value of the resulting calculations. Based on data on the prevalence and condition of pregnant women in Lhokseumawe and calculations using a series of formulas for mean, standard deviation, probability, and gaussian values, it was found that 50 pregnant women were predicted to have normal nutritional status, while 19 others had nutritional status. not enough. From the results of the accuracy carried out, it was found that the error value (error) of the application used was 48% while the accuracy value of the application was 53% or low. That way, the calculation formula developed in this study needs to be further developed to encourage the accuracy of the application made so that the application results are reliable in real life
Decision Support System for Plantation Land Suitability Assessment Using A Combination of AHP (Analytical Hierarchy Process) and Profile Matching Method
No full textDetermining the suitability of plantation land is a crucial factor in enhancing productivity and sustainability in the agricultural sector. However, existing studies often lack comprehensive approaches that integrate both the prioritization of criteria and precise evaluation of land suitability. This study addresses this gap by developing a decision support system (DSS) for plantation land suitability using a combination of the Profile Matching and Analytic Hierarchy Process (AHP) methods. The AHP method is employed to assign weights to various criteria based on their relative importance, while the Profile Matching method evaluates land suitability based on the generated profiles. The results indicate that this integrated approach provides accurate and detailed land suitability recommendations. Specifically, Buket Rata land is suitable for Clove (preference score: 3.821), Oil Palm, and Tea (3.596); Reulet land is suitable for Cocoa (3.22) and Coconut (3.16); Geulanggang Kulam land is suitable for Clove (3.41), Cocoa (3.35), and Oil Palm (3.29); Sawang land is suitable for Clove (3.41), Oil Palm (3.17), and Cocoa (2.99); and Pesisir Laut land is suitable for Sugarcane (3.353) and Clove (3.173). This DSS not only aids decision-makers in optimizing land use and managing sustainable plantations but also contributes to the broader field of agricultural decision-making by demonstrating the effectiveness of combining AHP and Profile Matching methods
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