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"Counting bacteria colonies uses Total Plate Count (TPC) method which isgenerally done by seeing, counting, naked eyes and time consuming. The aim of research is to make an image processing algorithm that is able to count the total bacteria colonies on the TPC method which is can be applied without any special equipment, and to provide informations about the best configuration in its application. This research was done by making an image processing algorithm based on gray-scale image segmentation, using MATLAB, and testing its accuracy in counting bacteria colonies. The result showed that the optimal threshold value for black background is between 0.67 and 0.79, and the optimal threshold value for white background was between 0.01 and 0.09. This experiment revealed that low value o f disk shape morphological structuring element could give the optimal detection of bacteria colonies. In conclutions, the total numbers of bacteria colonies which was counted by gray-scale image segmentation which one of image processing algorithm method was not statistically different compared to manual counting. Automation is one side o f technology that can help human doing something with easiness and simplicity. Digital image processing is one kind o f automation. Counting bacteria colonies using Total Plate Count (TPC) commonly done by counting bacteria colonies manually, it was very time consuming. The aim of thisresearch is to make an image processing algorithm that able to count total bacteria colonies on the TPC method which can be applied without require special equipment, and to provide information about best configuration in its application. This research was done by making an image processing algorithm based on color image segmentation using MATLAB, and testing its accuracy in counting bacteria colonies. The results showed that the total numbers of bacteria colonies as the result o f counting by image processing algorithm based on color image segmentation were not different statistically compared to manual counting. A good detection o f bacteria colonies was depends on the configuration o f some parameters, such as color sampling, value o f color tolerance, shape and value o f morphological structuring element."

"[Belum optimalnya kegiatan pemasaran dan belum adanya kerjasama dengan BPJS Kesehatan mengakibatkan sedikitnya jumlah pasien baru dibandingkan pasien lama dan menurunnya jumlah kunjungan poliklinik anak. Penelitian ini bertujuan untuk mendapatkan informasi mengenai segmen pasar sebagai dasar analisis segmentasi, target dan posisi pasar poliklinik anak RSIA Buah Hati Ciputat pada tahun 2015. Penelitian ini menggunakan jenis penelitian deskriptif dengan pendekatan kuantitatif dan kualitatif. Hasil penelitian ini adalah segmen pasar yang dibagi berdasarkan variabel geografis, demografis, psikografis dan perilaku. Target pasar yang paling sesuai merupakan hasil segmen pasar yang dianggap potensial yaitu, ibu usia produktif dan berpendidikan tinggi yang memiliki anak usia 3-5 tahun dengan penghasilan keluarga 2-5 juta perbulan. Posisi pasar yang terbentuk adalah pelayanan kesehatan anak yang ekonomis dengan tenaga kesehatan berkualitas di Wilayah Kota Tangerang Selatan.

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The marketing activities in RSIA Buah Hati Ciputat has not optimal and there are no coorporation with BPJS Kesehatan that has been targeted and has result least number of new patients compare to number of old patients and decreasing the

number of visits in pediatric polyclinic. This study aims to get information about market segments as the basis for the analysis of market segmentation, target and market position of pediatric polyclinic of RSIA Buah Hati Ciputat 2015. The types

of this study is descriptive with quantitative and qualitative. The result of this study are market segments which is divided by the variable geographic, demographic,

psychographic and behavioral. Target market is the potential of market segments is young mother and well educated who have children between 3-5 years old, with family income between 2-5 million rupiahs each month. The market position are the child health care which economical with qualified health personnel in South Tangerang City., The marketing activities in RSIA Buah Hati Ciputat has not optimal and there are

no coorporation with BPJS Kesehatan that has been targeted and has result least

number of new patients compare to number of old patients and decreasing the

number of visits in pediatric polyclinic. This study aims to get information about

market segments as the basis for the analysis of market segmentation, target and

market position of pediatric polyclinic of RSIA Buah Hati Ciputat 2015. The types

of this study is descriptive with quantitative and qualitative. The result of this study

are market segments which is divided by the variable geographic, demographic,

psychographic and behavioral. Target market is the potential of market segments is

young mother and well educated who have children between 3-5 years old, with

family income between 2-5 million rupiahs each month. The market position are

the child health care which economical with qualified health personnel in South

Tangerang City.]"

"Research on medical images becomes one of the studies that attracted many researchers, because it can help medical field to analyse the disease. One of the existing research in medical image is using dental panoramic radiographs image to detect osteoporosis. The analysed area is the width of cortical bone. Determination of the cortical bone width requires proper segmentation on the dental panoramic radiographs image. This study proposed the integration of watershed and region merging method based on statistical features for cortical bone segmentation on dental panoramic radiographs. Watershed segmentation process perform using gradient magnitude value from the input image. The watershed image that has excess segmentation can be solved by region merging based on statistical features. Statistical features used in this study is mean, standard deviation, and variance. The similarity of adjacent regions measure with weighted Euclidean distance from the statistical feature of the regions. Merging process will run by incorporating the background regions as many as possible, while keeping the object regions from being merged. Results of segmentation has succeeded in forming contour of the cortical bone. The average value of accuracy is 93.211%, the average value of sensitivity is 93.858%, and the average value of specificity is 93.071%.

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Penelitian terhadap citra medis menjadi salah satu penelitian yang banyak diminati karena dapat membantu dokter untuk menganalisa penyakit. Salah satu penelitian yang ada dalam citra medis adalah menggunakan citra dental panoramic radiographs untuk mendeteksi osteoporosis. Daerah yang dianalisis adalah lebar dari cortical bone. Segmentasi yang tepat sangat dibutuhkan untuk me-nentukan lebar cortical bone pada dental panoramic radiographs. Pada penelitian ini diusulkan inte-grasi metode watershed dan metode region merging berbasis fitur statistik untuk segmentasi cortical bone pada dental panoramic radiographs. Citra masukan berupa cortical bone dilakukan proses gradient magnitude kemudian dilanjutkan dengan proses segmentasi menggunakan watershed. Citra hasil proses watershed yang masih memiliki segmentasi berlebih dilakukan proses region merging berbasis fitur statistik. Selanjutnya kemiripan antar region dihitung dengan menggunakan weighted Euclidean distance dari fitur statistik setiap region. Fitur statistik yang digunakan adalah mean, vari-ance, dan standar deviasi. Proses merging akan berjalan dengan melakukan penggabungan pada dae-rah background telebih dahulu selanjutnya sisa region yang dihasilkan akan digabungkan sebagai dae-rah objek. Hasil segmentasi yang dilakukan telah berhasil membentuk contour dari cortical bone. Da-ri hasil uji coba didapatkan rata-rata akurasi 93,211%, rata-rata sensitifitas 93,858%, dan rata-rata spesifisitas 92,071%."

"As part of an attempt to improve computer-based test scoring on traditional grid answer sheets, which are used by 76.36% of interrogated schools in Thailand, this paper proposes an algorithm to segment the problematic handwritten-style student identification number. The method used is based on profile features supported by digit width-height ratio analysis. Non-touching digits are segmented by vertical histograms and the flood fill algorithm. Touching digits are segmented by considering the distances between upper and lower profiles as well as the derivatives of consecutive points of their profiles. Among 231 six-digit image sequences, the average segmentation accuracy rate was 98.20%, which is considered satisfactory. The results showed that an increased number of consecutive cursive digits decreased the segmentation accuracy, and was significant from 5 connecting digits."

"Penelitian ini mengembangkan Computer Aided Diagnosis CAD radiografi paru anak dengan menggunakan metode segmentasi Particle Swarm Optimization PSO untuk membantu dokter mendeteksi paru yang abnormal. Metode PSO mencari abnormalitas berdasarkan nilai piksel. Metode PSO dikerjakan dengan dua variasi metode yaitu FCM Wienerfilter PSO dan FCM Adaphisteq PSO. Evaluasi dilakukan dengan menghitung ROC Receiver Operating Characteristics citra segmentasi tiap metode terhadap citra acuan evaluasi dokter. Metode FCM Wienerfilter PSO memiliki nilaiROC paling baik. Overall error metode ini yaitu 11.43 1.6 dibanding dengan metode FCM Adapthisteq PSO yaitu 28.57 1,6. Hal ini menggambarkan bahwa banyak kesalahan deteksi yang dilakukan pada metode FCM Adapthisteq PSO. Metode FCM Wienerfilter PSO ini memiliki nilai akurasi 88,57, sensitifitas 90,00, spesifitas 85,00, dan presisi 93,75 lebih tinggi dibanding dengan semua parameter ROC metode FCM Adaphisteq PSO yaitu akurasi 71,43, Sensitivitas 80,00, Spesifitas 50,00, dan Presisi 80.00. Hal ini membuktikan bahwa hasil deteksi metode FCM Wienerfilter PSO lebih banyak memiliki tingkat keberhasilan yang sesuai dengan evaluasi dokter dan lebih baik dalam mendeteksi citra abnormal. Pada citra abnormal nilai piksel metodeFCM wienerfilter PSO memiliki rentang 209-255, dan nilai piksel metodeAdapthisteq PSO memiliki rentang 206-255.

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The study developed Computer Aided Diagnosis CAD children pulmonary radiography using Particle Swarm Optimization PSO segmentation method to help doctors detect abnormal lung. The PSO method searched abnormalities by value of the image pixel. PSO method used two variations method, namely FCM Wienerfilter PSO and FCM Adaphisteq PSO. The evaluation was done by calculating the ROC Receiver Operating Characteristics segmentation of each image against the reference image evaluation doctors. FCM Wienerfilter PSO method has better ROC value. Overall error of this method is 11.43 1.6 compared with the method of FCM Adapthisteq PSO is 28.57 1.6. This explain that many of the error detection on FCM Adapthisteq PSO method.

ROC FCM Wienerfilter PSO results show the value of accuracy 88,57, sensitivity 90,00, specificity 85,00, and precision 93,75 is relatively higher than all parameter of ROC FCM Adaphisteq PSO method that isaccuracy 71,43, sensitivity 80,00, specificity 50,00, and precision 80.00. This proves that the results of the detection method of FCM Wienerfilter PSO has more success rates in accordance with doctor rsquo s evaluation and better at detecting abnormal image. Abnormal lung pixel values by the method of FCM wienerfilter PSO is 209 255, andAbnormal lung pixel values by the FCM Adapthisteq PSO methodis 206 255."

"ABSTRAKPenelitian ini menjelaskan mengenai penerapan segmentasi konsumen berdasarkan CLV agar dapat menghasilkan profil konsumen bagi perusahan untuk memberikan perlakuan yang tepat bagi masing ndash; masing konsumen. Dalam memproses data yang akan digunakan, penelitian ini mengunakan segmentasi RFM sebagai langkah awal untuk mengidentifiksi data dan dilanjutkan dengan klasterisasi menggunakan K-Means agar mendapatkan gambaran data konsumen yang lebih jelas. Hasil dari penelitian ini menunjukan adanya lima jenis profile konsumen yang berbeda berdasarkan perhitungan RFM dan K-Means. Setiap kelompok memiliki karakteristik yang berbeda yang dapat digunakan oleh perusahaan untuk membentuk strategi dalam memberikan pendekatan kepada konsumen. Terdapat juga perbandingan antara kelompok konsumen yang akan dihasilkan apabila perusahaan menggunakan segmentasi konsumen menggunakan CLV dengan saat tidak menggunakan CLV. Dengan memberikan perlakuan yang tepat bagi konsumen yang dapat memberikan keuntungan bagi perusahaan dimasa yang akan datang, maka perusahaan dapat membentuk strategi yang lebih efektif dan tepat sasaran.

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ABSTRACTThis research focus on how to make a consumer segmentation based on CLV in order to create a customer profile for the company to provide appropriate treatment for each consumer. In order to process the data, this research uses RFM segmentation as the first step to identify the data and continued with K Means clustering to get a better interpretation of consumer data. The results of this research show five different types of consumer profiles based on RFM and K Means calculations. Each cluster has a different characteristic that can be used for a company to define a better strategy in order to approach their customer. There is also a comparison between the consumer groups if the company uses consumer segmentation using CLV or when not using CLV. By providing the right treatment for profitable customer, the company can form an effective and targeted strategy in the future. "

"Dampak terhadap lingkungan yang semakin tinggi menuntut industri untuk mengintegrasikan pemikiran lingkungan ke dalam manajemen rantai pasok. Salah satunya dengan memiliki pemasok berwawasan lingkungan, karena pemasok memiliki peran yang sangat penting dalam rantai pasok. Penelitian ini bertujuan untuk menilai pemasok pada salah satu hotel di Bogor, Indonesia. Metode yang digunakan dalam penelitian ini adalah Analytical Hierarchy Process (AHP) untuk memperoleh bobot kriteria penilaian pemasok, dan Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) untuk memperoleh nilai akhir dari setiap pemasok yang akan menjadi dasar dalam mensegmentasi pemasok berdasarkan dimensi kemampuan dan dimensi kesediaan. Hasil dari penelitian ini adalah pengelompokkan 31 pemasok hotel ke dalam empat segmen berbeda, serta rekomendasi strategi pengelolaan yang sesuai untuk setiap segmen pemasok.

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The increasing impact on the environment requires the industry to integrate environmental issues into their supply chain. One of them by having green supplier, because suppliers play a key role in the supply chain. This study aims to evaluate supplier in one of the hotel in Bogor, Indonesia. The method used in this study is Analytical Hierarchy Process (AHP) to obtain the weight of supplier evaluation criteria, as well as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to obtain the final score of each supplier which will be the basis for segmenting suppliers based on capabilities and willingness dimensions. The result of this study are classifying 31 suppliers of hotel into four different segments, and recommendations of suitable action plans for each segment."

"Poli Jantung Eksekutif merupakan salah satu poli yang sedang menjadi target bagian pemasaran RS Hermina Depok dalam peningkatan kualitasnya. Jumlah pasien poli Jantung Eksekutif mengalami peningkatan dan penurunan setiap bulannya yang menyebabkan Poli Jantung Eksekutif belum stabil. Tujuan penelitian ini adalah untuk menentukan strategi pemasaran berdasarkan STP ( Segmentasi, Target, dan Posisi ) pasar Rawat Jalan Poli Jantung Eksekutif RS Hermina Depok pada tahun 2019. Penelitian ini menggunakan jenis penelitian deskriptif analisis dengan pendekatan kuantitatif dan kualitatif. Hasil penelitian ini adalah Segmen pasar yang dibagi berdasarkan variabel geografis, demografis, psikografis, perilaku, dan loyalitas. Target pasar yang paling sesuai merupakan hasil segmen pasar yang dianggap potensial yaitu, Lansia berusia 45 tahun ke atas yang tinggal di daerah kota Depok dan sekitarnya dengan pendapatan 2,5 juta-5 juta perbulannya . Posisi pasar yang terbentuk adalah Pelayanan kesehatan poli jantung eksekutif dengan tenaga kesehatan berkualitas dan fasilitas lengkap serta tetap mengutamakan Service Excellent kepada pelanggan.

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Excecutive Heart Clinic is one of the clinic that is being targeted by the marketing division of Hermina Hospital Depok for improving it’s quality. The number of Executive Heart Clinic patients has increased and decreased for each month which causes Executive Heart Clinic has not been stable. The purpose of this study was to determine a marketing strategy based on STP (Segmentation, Targeting, and Positioning) of the Outpatient Excecutive Heart Clinic market in Hermina Hospital Depok 2019. This research uses descriptive analysis research with quantitative and qualitative approaches. The results of this study are market segments which are divided based on geographical, demographic, psychographic, behavioral, and loyalty variables. The most appropriate target market is the result of a market segment that is considered potential, elderly aged 45 years and over who live in Depok and the surrounding areas with an income of 2.5 million-5 million each month. The market position is Excecutive Heart Clinic health services with qualified health workers and complete facilities and also do the prioritize Service Excellence to customers."

"

Salah satu permasalahan utama yang sedang dihadapi oleh Kementrian Kelautan dan Perikanan Republik Indonesia (KKP) adalah maraknya kejadian Illegal, Unreported, and Unregulated (IUU) fishing yang terjadi pada perairan Indonesia. Kejadian ini menimbulkan banyak kerugian bagi Indonesia, terutama dalam aspek sosial, ekologi, dan ekonomi. Untuk mengatasi masalah ini, terutama unreported fishing, dirancanglah sebuah sistem yang dapat digunakan untuk memonitor penangkapan ikan, sekaligus melakukan deteksi dan klasifikasi terhadap jenis ikan hasil tangkapan di atas kapal. Sistem dirancang menggunakan konsep object detection dan instance segmentation, dua bidang dari machine learning, menggunakan model YOLOv5 dan varian-variannya yang merupakan salah satu model dari keluarga YOLO (You Only Look Once) yang paling baik dari segi kecepatan dan akurasi. Dengan adanya sistem tersebut, diharapkan bahwa hasil tangkapan kapal di perairan Indonesia dapat bersifat lebih legal, teratur, dan sesuai dengan yang dilaporkan kepada KKP. Sistem terbaik dari penelitian ini dihasilkan menggunakan model instance segmentation yang mendapatkan nilai mAP50 0,834, mAP50-95 0,544, F1-score 0,848, dan kecepatan inferensi 232,6 fps untuk partisi validation, dan mAP50 0,797, mAP50-95 0,531, F1-score 0,802, dan kecepatan inferensi 250,0 fps untuk partisi testing pada hasil bounding box, serta nilai mAP50 0,739, mAP50-95 0,36, F1-score 0,789, dan kecepatan inferensi 232,6 fps untuk partisi validation, dan mAP50 0,711, mAP50-95 0,335, F1-score 0,746, dan kecepatan inferensi 250,0 fps untuk partisi testing pada hasil segmentation mask. Selain itu, model tersebut juga mendapatkan akurasi 60% pada tahapan perbandingan dengan model object detection.

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One of the main problems the Indonesian Ministry of Marine Affairs and Fisheries (KKP) is currently facing is the abundance of Illegal, Unreported, and Unregulated (IUU) fishing instances happening in Indonesian waters. This phenomenon creates a lot of problems for Indonesia, mainly in the social, ecological, and economical aspects. To overcome these problems, mainly unreported fishing, a system that can be used to not only monitor the fishing process, but also to detect and classify the types of fish that are caught by that boat was created. This system is based on object detection and instance segmentation, both fields of machine learning, using the YOLOv5 model and its variants, which are some of the fastest and most accurate models from the YOLO (You Only Look Once) family. With this system, it is hoped that fish caught in Indonesian waters can be more legitimate, regulated, and reported correctly to the KKP. The best system from this research is created using an instance segmentation model with mAP50 0.834, mAP50-95 0.544, F1-score 0.848, and inference speed 232.6 fps for validation scores, and mAP50 0.797, mAP50- 95 0.531, F1-score 0.802, and inference speed 250.0 fps for testing scores on the bounding box results, as well as mAP50 0.739, mAP50-95 0.36, F1-score 0.789, and inference speed 232.6 fps for validation scores, and mAP50 0.711, mAP50-95 0.335, F1-score 0.746, and inference speed 250.0 fps on the segmentation mask results. The model also achieved an accuracy of 60% in the comparison phase against the object detection model.

"

"Recognition of handwritten mathematical expressions has been an important topic for many researchers for decades. It remains one of the most challenging and exciting areas in pattern recognition. In the recognition process of offline handwritten mathematical expressions, segmentation is the most important process. Problems in ambiguities of identifying superscript and subscript in complex offline mathematical expressions remain one of the most important problem. To the best of our knowledge little work has been done in the segmentation of offline handwritten mathematical expressions with respect to superscript and subscript. In this paper an efficient segmentation technique for superscript, subscript and main characters within offline handwritten mathematical expressions has been proposed. This technique is based on the generation of predictions for superscript, subscript and main characters within handwritten mathematical expressions, which helps for the reconstruction of mathematical expressions during the recognition process with their spatial interrelationship. The proposed system was conducted as an experiment with a database of 300 samples of scanned mathematical expressions that comprised 2,000 symbols out of which there were 31 different types of Mathematical Symbols. The classification of the elements was carried out by the K-NN-classifier based on density features. This experiment shows remarkable results."