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"This study was aimed to determine maturity and ripeness of sawo (Achras sapota L.) based on near infrared (NIR) spectroscopy using artificial neural network. The NIR system was developed and applied to 120 sawo samples at the wavelength range from 1400 - 1995 nm, the data was recorded in 5 nm interval. The samples were separated into three group, i.e. mature, ripe, and over ripe based on their harvest time. The principal component analysis (PCA) was used to reduce dimension of NIR reflectance data that has been smoothed with moving average method. The 5, 10, 15 principal component was fed into the neural network model as input and the level of maturity and ripeness as output. The result recommended the use of 10 and 15 principal component as input on various nodes in hidden layer that would provided the highest accurateness of 100% in classifying the sawo based on its maturity and ripeness"

"ABSTRAKBelimbing manis merupakan buah yang memiliki kualitas rasa dan tekstur yangoptimal jika berada pada tingkat kematangan yang tepat. Pada penelitian ini,sebuah pencitraan hiperspektral telah dirancang untuk memprediksi nilai solublesolids content (SSC) dan firmness serta memprediksi tingkat kematangan buahbelimbing yang diklasifikasikan dalam tiga kelas yaitu mentah, matang dan terlalumatang. Pengklasifikasian ini akan dilakukan berdasarkan informasi spasial,informasi spektral dan kombinasi informasi spektral dan spasial dari citrahiperspektral dengan wilayah panjang gelombang 400-1000 nm. Tahapan-tahapanpengolahan citra yang dilakukan adalah akuisisi citra, koreksi citra, segmentasi,ekstraksi dan seleksi fitur, pemodelan kuantitatif menggunakan algoritma principalcomponent regression (PCR) dan partial least square regression (PLSR) sertapemodelan kualitatif menggunakan algoritma support vector machines (SVM).Pengujian kinerja model kualitatif untuk memprediksi tingkat kematangan dapatdilihat berdasarkan nilai error klasifikasi dan pengujian kinerja model kuantitatifuntuk memprediksi nilai SSC dan firmness dapat dilihat dari nilai koefisien korelasidan root mean square error. Model kualitatif terbaik diperoleh dengan errorklasifikasi 6,5%. Model kuantitatif untuk memprediksi SSC diperoleh denganmengimplementasikan PLSR dengan nilai koefisien korelasi dan RMSE sebesar0,98 dan 0,42. Model kuantitatif untuk memprediksi firmness diperoleh denganmengimplementasikan PLSR dengan nilai koefisien korelasi dan RMSE sebesarserta 0,94 dan 4,72.

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ABSTRACTStarfruit is a fruit that has a quality of taste and texture optimal if it is at the rightlevel of ripeness. In this study, a hyperspectral imaging has been designed to predictthe soluble solids content (SSC) and firmness values and to predict the starfruitripenesslevels classified in three classe unripe, ripe and overripe. This classificationwill be based on spatial information, spectral information and a combination ofspectral and spatial information from hyperspectral image with the region of thewaveleght 400-1000 nm. Steps of image processing are image acquisition, imagecorrection, segmentation, feature extraction and selection, quantitative modelingusing principal component regression (PCR) and partial least square regression(PLSR) algorithms and qualitative modeling using support vector machines (SVM)algorithm . Qualitative model performance test to predict ripeness level can be seenbased on classification error value and quantitative model performance test topredict the value of SSC and firmness can be seen from the correlation coefficientand root mean square error. The best qualitative model is obtained with aclassification error of 6.5%. The quantitative model for predicting SSC wasobtained by implementing PLSR with correlation coefficient and RMSE of 0.98and 0.42. Quantitative models for predicting firmness are obtained by implementingPLSR with correlation coefficient and RMSE of 0.94 and 4.72."

"Skripsi ini bertujuan menganalisa penyebab kegagalan implementasi perjanjian gencatan senjata Lusaka (LCA) di Republik Demokrasi Kongo yang disetujui pada 10 Juli 1999. LCA disepakati untuk mengakhiri Perang Kongo II yang merupakan konflik terbesar di Afrika, melibatkan sembilan negara Afrika pada puncaknya, dan memiliki skala konflikdan korban jiwa terbesar sejak perang dunia kedua. LCA awalnya diharapkan mampu meredakan Perang Kongo II, yang memiliki karakter Perang sipil namun mengalami internasionalisasi dikarenakan berbagai kepentingan negara tetangga. Namun LCA terus dikritik karena kontribusinya yang minimal terhadap upaya resolusi konflik Kongo II sebelum akhirnya digantikan persetujuan-persetujuan lain yang lahir dari proses negosiasi paska LCA. Penelitian ini merupakan penelitian kuantitatif dengan metode deskriptif eksplanatif yang menggunakan studi dokumentasi dan literatur. Hasil penelitian ini menunjukan bahwa perjanjian gencatan senjata Lusaka dibuat dalam situasi konflik yang belum matang dimana potensi tinggi terhadap eskalasi konflik paska penandatanganan, membuat perjanjian ini sulit diimplementasikan dan menjadi tidak lagi relevan bagi berbagai pihak yang bertikai serta bagi proses resolusi konflik di Republik Demokrasi Kongo.

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This undergraduate thesis seeks to analyze the cause of failure in implementation of Lusaka Ceasefire Agreement (LCA) in the Democratic Republic of Congo which was agreed in July 1999 to end the second Congo conflict, the largest conflict in Africa involving nine countries in its apex with the worst record of violence and casualties which is only surpassed by the second world war. LCA is intended to resolve the second Congo war which has the character of a local conflict being internationalized due to myriads of interest from its neighboring countries. However is often criticized for its lack of contribution due to its slow and almost non-existent implementation efforts done by both the belligerent parties and the international society. This research is done in a quantitative method using literature and document examinations.

The result of this research shows that when the Lusaka Ceasefire Agreement was made, conflict in Congo had not reached its ripe moment. Therefore, rendering the implementation of the treaties, making it especially hard to be implemented and thus becoming more and more irrelevant for the disputed parties and for conflict resolution process in the Democratic Republic of Congo."